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An Overview of the Vaccine Debate

Looking at Both Sides of the Argument

There is a wealth of research demonstrating the efficacy and safety of vaccines —including how some have virtually eradicated infectious diseases that once killed millions. However, this has done little to sway those who believe that untold harms are being hidden from the American public.

The vaccine debate—including the argument as to whether vaccines are safe, effective, or could cause conditions like autism —has received a lot of attention from the media in recent years. With so much conflicting information being publicized, it can be a challenge to discern what is true and what is not. Therefore, it is important to learn the facts before making health decisions.

Claims and Controversy

Those who are part of the anti-vaccination movement include not only non-medical professionals but several scientists and healthcare providers who hold alternative views about vaccines and vaccination in general.

Some notable examples include:

• British healthcare provider Andrew Wakefield, who in 1998 published research linking the MMR vaccine and autism . That study has since been retracted, and he was later removed from the medical registry in the United Kingdom for falsifying scientific data.
• Pediatrician Bob Sears, who wrote the bestseller "The Vaccine Book: Making the Right Decision for your Child ," which suggested that many essential childhood vaccines were "optional." However, he was subsequently put on probation by the Medical Review Board of California in 2018 for alleged medical negligence and the inappropriate writing of medical exemptions for vaccinations.
• Dr. Jane M. Orient, director of the Association of American Healthcare Providers and Surgeons, who was among the leading opponents of the COVID-19 vaccine and one of the leading proponents of using hydroxychloroquine to treat COVID-19 during the pandemic.

These opposing views and claims, along with other information promoted by the news and social media, have led some people to question whether they know everything they need to know about vaccines.

Common Concerns Regarding Vaccines

The arguments made against vaccines are not new and have been made well before the first vaccine was developed for smallpox back in the 18th century.

The following are some of the common arguments against vaccines:

• Vaccines contain "toxic" ingredients that can lead to an assortment of chronic health conditions such as autism.
• Vaccines are a tool of "Big Pharma," in which manufacturers are willing to profit off of harm to children.
• Governments are "pharma shills," meaning they are bought off by pharmaceutical companies to hide cures or approve drugs that are not safe.
• A child’s immune system is too immature to handle vaccines , leading the immune system to become overwhelmed and trigger an array of abnormal health conditions.
• Natural immunity is best , suggesting that a natural infection that causes disease is "better" than receiving a vaccine that may cause mild side effects.
• Vaccines are not tested properly , suggesting a (highly unethical) approach in which one group of people is given a vaccine, another group is not, and both are intentionally inoculated with the same virus or bacteria.
• Infectious diseases have declined due in part to improved hygiene and sanitation , suggesting that hand-washing and other sanitary interventions are all that are needed to prevent epidemics.
• Vaccines cause the body to "shed" virus , a claim that is medically true, although the amount of shed virus is rarely enough to cause infection.

The impact of anti-vaccination claims has been profound. For example, it has led to a resurgence of measles in the United States and Europe, despite the fact that the disease was declared eliminated in the U.S. back in 2000.

Studies have suggested that the anti-vaccination movement has cast doubt on the importance of childhood vaccinations among large sectors of the population. The added burden of the COVID-19 pandemic has led to further declines in vaccination rates.

There is also concern that the same repercussions may affect COVID-19 vaccination rates—both domestically and abroad. Ultimately, vaccine rates must be high for herd immunity to be effective.

According to a study from the Centers for Disease Control and Prevention (CDC), the rate of complete recommended vaccination among babies age 5 months has declined from 66.6% in 2016 to 49.7% by May 2020. Declines in vaccination coverage were seen in other age groups as well.

Benefits of Vaccination

Of the vaccines recommended by the CDC, the benefits of immunization are seen to overwhelmingly outweigh the potential risks. While there are some people who may need to avoid certain vaccines due to underlying health conditions, the vast majority can do so safely.

According to the U.S. Department of Health and Human Services, there are five important reasons why your child should get the recommended vaccines:

• Immunizations can save your child’s life . Consider that polio once killed up to 30% of those who developed paralytic symptoms. Due to polio vaccination, the disease is no longer a public health concern in the United States.
• Vaccination is very safe and effective . Injection site pain and mild, flu-like symptoms may occur with vaccine shots. However, serious side effects , such as a severe allergic reaction, are very rare.
• Immunization protects others . Because respiratory viruses can spread easily among children, getting your child vaccinated not only protects your child but prevents the further spread of disease.
• Immunizations can save you time and money . According to the non-profit Borgen Project, the average cost of a measles vaccination around the world is roughly $1.76, whereas the average cost of treating measles is $307. In the end, the cost of prevention is invariably smaller than the cost of treatment.
• Immunization protects future generations . Smallpox vaccinations have led to the eradication of smallpox . Rubella (German measles) vaccinations have helped eliminate birth defects caused by infection of pregnant mothers in the developed world. With persistence and increased community uptake, measles could one day be declared eliminated (again) as well.

A Word From Verywell

If you have any questions or concerns about vaccinations, do not hesitate to speak with your healthcare provider or your child's pediatrician.

If a vaccine on the immunization schedule has been missed, speak to a healthcare provider before seeking the vaccination on your own (such as at a pharmacy or clinic). In some cases, additional doses may be needed.

Vaccines Healthcare Provider Discussion Guide

Get our printable guide for your next healthcare provider's appointment to help you ask the right questions.

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Eggerton L.  Lancet retracts 12-year-old article linking autism to MMR vaccines .  CMAJ . 2010 Mar 9; 182(4):e199-200. doi:10.1503/cmaj.109-3179

Park A. Doctor behind vaccine-autism link loses license . Time .

Offit PA, Moser CA.  The problem with Dr Bob's alternative vaccine schedule .  Pediatrics.  2009 Jan;123 (1):e164-e169. doi:10.1542/peds.2008-2189

Before the Medical Board of California, Department of Consumer Affairs, State of California. In the Matter of the Accusation Against Robert William Sears, M.D., Case No. 800-2015-012268 .

Stolberg SG. Anti-vaccine doctor has been invited to testify before Senate committee . The New York Times.

Wolfe RM, Sharp LK.  Anti-vaccinationists past and present . BMJ. 2002;325(7361):430-2. doi:10.1136/bmj.325.7361.430

Agley J, Xiao Y. Misinformation about COVID-19: Evidence for differential latent profiles and a strong association with trust in science . BMC Public Health. 2021;21:89. doi:10.1186/s12889-020-10103-x

Centers for Disease Control and Prevention. Measles history .

Hussain A, Ali S, Ahmed M, Hussain S. The anti-vaccination movement: a regression in modern medicine .  Cureus . 2018;10(7): e2919. doi:10.7759/cureus.2919

Bramer CA, Kimmins LM, Swanson R, et al. Decline in child vaccination coverage during the COVID-19 pandemic — Michigan Care Improvement Registry, May 2016–May 2020 . MMWR. 2020 May;69(20):630-1. doi:10.15585/mmwr.mm6920e1

Centers for Disease Control and Prevention. Why vaccinate .

Centers for Disease Control and Prevention. Poliomyelitis .

Centers for Disease Control and Prevention. Making the vaccine decision .

Borgen Project. What is the cost of measles in the developed world? .

By Vincent Iannelli, MD  Vincent Iannelli, MD, is a board-certified pediatrician and fellow of the American Academy of Pediatrics. Dr. Iannelli has cared for children for more than 20 years. 

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• Volume 47, Issue 2
• Good reasons to vaccinate: mandatory or payment for risk?
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• http://orcid.org/0000-0003-1691-6403 Julian Savulescu 1 , 2 , 3
• 1 Faculty of Philosophy , University of Oxford , Oxford , UK
• 2 Murdoch Childrens Research Institute , Parkville , Victoria , Australia
• 3 Melbourne Law School , University of Melbourne , Melbourne , Victoria , Australia
• Correspondence to Professor Julian Savulescu, Faculty of Philosophy, University of Oxford, Oxford, UK; julian.savulescu{at}philosophy.ox.ac.uk

Mandatory vaccination, including for COVID-19, can be ethically justified if the threat to public health is grave, the confidence in safety and effectiveness is high, the expected utility of mandatory vaccination is greater than the alternatives, and the penalties or costs for non-compliance are proportionate. I describe an algorithm for justified mandatory vaccination. Penalties or costs could include withholding of benefits, imposition of fines, provision of community service or loss of freedoms. I argue that under conditions of risk or perceived risk of a novel vaccination, a system of payment for risk in vaccination may be superior. I defend a payment model against various objections, including that it constitutes coercion and undermines solidarity. I argue that payment can be in cash or in kind, and opportunity for altruistic vaccinations can be preserved by offering people who have been vaccinated the opportunity to donate any cash payment back to the health service.

• behaviour modification
• technology/risk assessment
• philosophical ethics
• public health ethics

This is an open access article distributed in accordance with the Creative Commons Attribution 4.0 Unported (CC BY 4.0) license, which permits others to copy, redistribute, remix, transform and build upon this work for any purpose, provided the original work is properly cited, a link to the licence is given, and indication of whether changes were made. See: https://creativecommons.org/licenses/by/4.0/ .

https://doi.org/10.1136/medethics-2020-106821

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Introduction

We are in the midst of a global pandemic with COVID-19 and there is a race to develop a vaccine. At the time of writing, there are 53 vaccines in clinical trials on humans (plus five that have bypassed the full trial process) and at least 92 preclinical vaccines under active investigation in animals. There are a number of different approaches: (1) genetic—using mRNA to cause the body to produce viral proteins; (2) viral vector—using genetically modified viruses such as adenovirus to carry sections of coronavirus genetic material; (3) protein—delivering viral proteins (but not genetic material) to provoke an immune response; (4) inactivated or attenuated coronavirus; (5) repurposing existing vaccines, eg, BCG (bacillus Calmette–Guérin). 1

Given the mounting number of deaths globally, and the apparent failure of many countries to contain the pandemic without severely damaging or problematic lockdowns and other measures, there have been calls to make a vaccine, if it were approved, mandatory. 2 Mandatory vaccination has not been ruled out within the UK. 3

The first part of this article asks when, if ever, a vaccine should be mandatory. I will create a set of criteria and a decision algorithm for mandatory vaccination. I will argue that in the case of COVID-19, some of these criteria may not be satisfied. The second part of the article argues that in the case of COVID-19, it may be ethically preferable to incentivise vaccine uptake. I will justify incentivisation and discuss different kinds of incentives.

Ethics of mandatory COVID-19 vaccination

There is a large body of literature on the justification for the use of coercion in public health and infectious disease in particular. Mandatory vaccination is typically justified on Millian grounds: harm to others. According to John Stuart Mill, the sole ground for the use of state coercion (and restriction of liberty) is when one individual risks harming others. 4 The most prominent arguments from bioethicists appeal to preventing harm to others. 5–7 In the case of children, significant risk of harm to the child is also a ground for state protection. Bambery et al 8 give the example of a child taking a box of toxic bleach to school, potentially harming himself and other children. Teachers are entitled to restrain the child and remove the poison both because of risk to the child and to other children. 8 Flanigan uses a similar example of a person shooting a gun into a crowd. 5

The Nuffield Council of Bioethics produced an influential report on public health which considers when coercion and mandatory vaccination might be justified:

When assessing whether more directive policies are acceptable, the following factors should be taken into account: the risks associated with the vaccination and with the disease itself, and the seriousness of the threat of the disease to the population. In the case of incentivised policies, the size of the incentive involved should be appropriate so that it would not unduly compromise the voluntariness of consent. We identified two circumstances in which quasi-mandatory vaccination measures are more likely to be justified. First, for highly contagious and serious diseases, for example with characteristics similar to smallpox. Second, for disease eradication if the disease is serious and if eradication is within reach. 9

I will elaborate on these brief suggestions and provide a novel structured algorithm for when vaccination should be mandatory.

COVID-19 is almost unique because of the gravity of the problem at the global level: not only is there cost in terms of lives from COVID-19, there is also the extraordinary economic, health and well-being consequences of various virus-control measures, including lockdown, which will extend into the future. Probably never before has a vaccine been developed so rapidly and the pressure to use it so great, at least at the global level.

There is a strong case for making any vaccination mandatory (or compulsory) if four conditions are met:

There is a grave threat to public health

The vaccine is safe and effective

Mandatory vaccination has a superior cost/benefit profile compared with other alternatives

The level of coercion is proportionate.

Each of these conditions involves value judgements.

Grave threat to public health

So far, there have been over 1 million deaths attributed to COVID-19 globally (as of 30 September 2020). 10 In the UK alone, it was predicted in influential early modelling that 500 000 would have died if nothing was done to prevent its spread. Even with the subsequent introduction of a range of highly restrictive lockdown measures (measures which could themselves come at a cost of 200 000 non-COVID-19 lives according to a recent UK government report), 11 more than 42 000 (as of 30 September 2020) 12 have died in the UK within 28 days of a positive test.

The case fatality rate was originally estimated to be as high as 11%, but (as is typical with new diseases) this was quickly scaled down to 1.5% or even lower. 13 The infection fatality rate (IFR, which accounts for asymptomatic and undiagnosed cases) is lower still as it has become clear that there are a large number of asymptomatic and mild cases. For example, the Centre for Evidence Based Medicine reports that “In Iceland, where the most testing per capita has occurred, the IFR lies somewhere between 0.03% and 0.28%”. 14

Of course, how you define “grave” is a value judgement. One of the worst-affected countries in the world in terms of COVID-19-attributed deaths per million is Belgium. The mortality is (at the time of writing) around 877 per million population, which is still under 0.1%, and the average age of death is 80. Of course, Belgium and most other countries have taken strict measures to control the virus and so we are not seeing the greatest possible impact the virus could have. Yet others such as Brazil and Sweden have intervened to a much lesser degree, yet (currently) have rates of 687 and 578 deaths per million respectively. Sweden’s April all-cause deaths and death rate at the peak of its pandemic so far, while extremely high, were surpassed by months in 1993 and 2000. 15

The data are complex and difficult to compare with different testing rates, and ways of assigning deaths and collecting data differing from country to country. For example, Belgium counts deaths in care homes where there is a suspicion that COVID-19 was the cause (without the need for a positive test) and, until recently, the UK counted a death which followed any time from a COVID-19 positive test as a COVID-19 death. Moreover, there have been huge behavioural changes even in countries without legally enforced lockdowns. Furthermore, the IFR varies wildly by age-group and other factors. Even among survivors, there is emerging evidence that there may be long-term consequences for those who have been infected but survived. Long COVID-19 health implications may present a grave future public health problem. Nevertheless, some might still argue that this disease has not entered the “grave” range that would warrant mandatory vaccination. The Spanish influenza killed many more (50–100 million), 16 and it afflicted younger rather than older people, meaning even more “life years” were lost. It is not difficult to imagine a Superflu, or bioengineered bug, which killed 10% across all ages. This would certainly be a grave public health emergency where it is likely mandatory vaccination would be employed.

Deciding whether COVID-19 is sufficiently grave requires both more data than we have and also a value judgement over the gravity that would warrant this kind of intervention. But let us grant for the sake of argument that COVID-19 is a grave public health emergency.

Vaccine is safe and effective

There are concerns that testing has been rushed and the vaccine may not be safe or effective. 17

First, although the technology being used in many of these vaccine candidates has been successfully used in other vaccines, no country has ever produced a safe and effective vaccine against a coronavirus. So in one way, we are all in uncharted waters.

Second, any vaccine development will be accelerated in the context of a grave public health emergency.The inherent probabilistic nature of the development of any biologic means that no vaccine could be said to be 100% safe. There will be risks and those risks are likely to be greater than with well-established vaccines.

Thirdly, some side effects may take time to manifest.

This is not to support the anti-vaccination movement. Vaccines are one of the greatest medical accomplishments and a cornerstone of public health. There are robust testing procedures in place in most jurisdictions to ensure that licensed COVID-19 vaccines are both effective and safe. It is only to acknowledge that everything, including vaccination, has risks. Perhaps the biggest challenge in the development of a vaccine for COVID-19 will be to be honest about the extent of those risks and convey the limitations of confidence in safety and efficacy relative to the evidence accrued.

There is an ethical balance to be struck: introducing a vaccine early and saving more lives from COVID-19, but risking side effects or ineffectiveness versus engaging in longer and more rigorous testing, and having more confidence in safety and efficacy, but more people dying of COVID-19 while such testing occurs. There is no magic answer and, given the economic, social and health catastrophe of various anti-COVID-19 measures such as lockdown, there will be considerable pressure to introduce a vaccine earlier.

To be maximally effective, particularly in protecting the most vulnerable in the population, vaccination would need to achieve herd immunity (the exact percentage of the population that would need to be immune for herd immunity to be reached depends on various factors, but current estimates range up to 82% of the population). 18

There are huge logistical issues around finding a vaccine, proving it to be safe, and then producing and administering it to the world’s population. Even if those issues are resolved, the pandemic has come at a time where there is another growing problem in public health: vaccine hesitancy.

US polls “suggest only 3 in 4 people would get vaccinated if a COVID-19 vaccine were available, and only 30% would want to receive the vaccine soon after it becomes available.” 18

Indeed, vaccine refusal appears to be going up. A recent Pew survey suggested 49% of adults in the USA would refuse a COVID-19 vaccine in September 2020. 19

If these results prove accurate then even if a safe and effective vaccine is produced, at best, herd immunity will be significantly delayed by vaccine hesitancy at a cost both to lives and to the resumption of normal life, and at worst, it may never be achieved.

There remain some community concerns about the safety of all pre-existing vaccines, including many that have been rigorously tested and employed for years.

In the case of COVID-19, the hesitancy may be exacerbated by the accelerated testing and approval process which applies not only to Sputnik V (the controversial “Russian vaccine”). Speaking about America’s vaccine programme, Warp Speed, Donald Trump applauded its unprecedented pace:

…my administration cut through every piece of red tape to achieve the fastest-ever, by far, launch of a vaccine trial for this new virus, this very vicious virus. And I want to thank all of the doctors and scientists and researchers involved because they’ve never moved like this, or never even close. 20

The large impact on society means the vaccine will be put to market much more quickly than usual, perhaps employing challenge studies or other innovative designs, or by condensing or running certain non-safety critical parts of the process in parallel (for example, creating candidate vaccines before its approval).

While the speed is welcomed by politicians and some members of the public, the pressure to produce a candidate vaccine, and the speed at which it has been done, may be also perceived (perhaps unfairly) to increase the likelihood of the kind of concerns that lead to vaccine hesitancy: concerns over side-effects that are unexpected or rare, or that take longer to appear than the testing process allows for, or that for another reason may be missed in the testing process.

The job to be done will not only be to prove scientifically that the vaccine is safe and effective, but also to inform and reassure the public, especially the group who are willing to take the vaccine in theory—but only after others have tried it out first.

The question remains of how safe is safe enough to warrant mandatory vaccination. It is vanishingly unlikely that there will be absolutely no risk of harm from any biomedical intervention, and the disease itself has dramatically different risk profiles in different groups of the population. In an ideal world, the vaccine would be proven to be 100% safe. But there will likely be some risk remaining. Any mandatory vaccination programme would therefore need to make a value judgement about what level of safety and what level of certainty are safe and certain enough. Of course, it would need to be very high, but a 0% risk option is very unlikely.

A COVID-19 vaccine may be effective in reducing community spread and/or preventing disease in individuals. Mandatory vaccination is most justifiable when there are benefits to both the individual and in terms of preventing transmission. If the benefits are only to individual adults, it is more difficult to support mandatory vaccination. One justification would be to prevent exhaustion of healthcare services in an emergency (eg, running out of ventilators), which has been used a basis of restriction of liberty (it was the main justification for lockdown). It could also be justified in the case of protection of children and others who cannot decide for themselves, and of other adults who either cannot be vaccinated for medical reasons.

Better than the alternatives

It is a standard principle of decision theory that the expected utility of a proposed option must be compared with the expected utility of relevant alternatives. There are many alternatives to mandatory vaccination. See figure 1 for a summary of the range of strategies for preventing infectious disease.

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Strategies for prevention of infectious disease.

A popular position, especially among medical professionals, 7 is that we don’t need mandatory vaccination because people are self-interested or altruistic enough to come forward for vaccination. We can reach herd immunity without mandatory vaccination.

If this were true, all well and good, but the surveys mentioned above cast doubt on this claim with regard to the future COVID-19 vaccine. Moreover, reaching herd immunity is not good enough.

First, how fast we reach herd immunity is also important. In a pandemic, time is lives. If it takes a year to reach herd immunity, that could be thousands or tens of thousands of lives in one country.

Second, herd immunity is necessary because some people cannot be vaccinated for medical reasons: they have allergies, immune problems, or other illnesses. The elderly often don’t mount a strong immune response (that is why it is better to vaccinate children for influenza because they are the biggest spreaders of that disease 7 —although COVID-19 appears to be different on the current evidence). And immunity wanes over time—so even people previously vaccinated may become vulnerable.

Even when national herd immunity is achieved, local areas can fall below that level over time, causing outbreaks, as happened with measles recently. This is especially likely to happen where people opposed to vaccines tend to cluster toghether—for example, in the case of certain religious communities. So ideally we need better than herd immunity to ensure that people are protected both over time and in every place.

These are thus reasons to doubt whether a policy of voluntary vaccination will be good enough, though it remains to be seen.

There are other policies that might obviate the need for mandatory vaccination. South Korea has kept deaths down to about 300 (at the time of writing) with a population of 60 000 000 with a vigorous track and trace programme (although it was criticised for exposing extra-marital affairs and other stigmatised behaviours). 21 Other countries have enforced quarantine with tracking devices. There could be selective lockdown of certain groups, 22 or for intermittent periods of time.

The long-term costs and benefits of such policies would have to be evaluated. That is, we should calculate the expected utility of mandatory vaccination (in combination with other policies) and compare it to alternative strategies (or some other combination of these). How utility should be evaluated is an ethical question. Should we count deaths averted (no matter how old), life years lost or lost well-being (perhaps measured by quality adjusted life years)? 23 Should we count loss of liberty or privacy into the other side the equation?

It may be that a one-off mandatory vaccination is a significantly smaller loss of well-being or liberty than these other complex resource intensive strategies.

So we cannot say whether a mandatory policy of COVID-19 vaccination is ethically justified until we can assess the nature of the vaccine, the gravity of the problem and the likely costs/benefit of alternatives. But it is certainly feasible that it could be justified.

It is important to recognise that coercive vaccination can be justified. This is easy to see by comparing it to other coercive interventions in the public interest.

Conscription in war

In the gravest emergencies, where the existence and freedom of the whole population is at stake, people are conscripted to serve their country, often with high risk of death or permanent injury. We often analogise the pandemic to a war: we are fighting the virus. If people can be sent to war against their will, in certain circumstances some levels of coercion are justified in the war on the virus. Notably, in conditions of extreme emergency in past wars (graver than currently exist for COVID-19), imprisonment or compulsion have even been employed. 24

A more mundane example is the payment of taxes. Taxes benefit individuals because tax revenue allows the preservation of public goods. But if sufficient numbers of others are paying their taxes, it is in a person’s self-interest to free ride and avoid taxes. Indeed, paying taxes may result in harm in some circumstances. 24 In the USA, where there is a large private healthcare sector, paying your taxes may mean you cannot pay for lifesaving medical care that you would otherwise have been able to afford. Still, taxes are mandatory based on considerations of fairness and utility.

Seat belts are mandatory in the UK and many other countries, whereas they were previously voluntary. Interestingly, 50% or so of Americans initially opposed making seat belts mandatory, but now 70% believe mandatory laws are justified. 25

Seat belts reduce the chance of death if you are involved in a car accident by 50%. They are very safe and effective. Notably, they do cause injuries (seat belt syndrome) and even, very occasionally, death. But the chances of being benefitted by wearing them vastly outweigh these risks, so they are mandatory, with enforcement through fines . I have previously likened vaccination to wearing a seat belt. 25

Pre-existing mandatory vaccination

Mandatory vaccination policies are already in place in different parts of the world. Mandatory vaccination policies are those that include a non-voluntary element to vaccine consent and impose a penalty or cost for unjustified refusal (justified refusal includes those who have a contraindicating medical condition, or those who already have natural immunity). There are a range of possible penalties or costs which can coerce people. Australia has the “No Jab, No Pay” scheme which withholds child benefits if the child is not vaccinated, and a “No Jab, No Play” scheme which withholds kindergarten childcare benefits. Italy introduced fines for unvaccinated children who attend school. In the USA, state regulations mandate that children cannot attend school if they are not vaccinated, and healthcare workers are required to vaccinate. Some US states (eg, Michigan) make exemptions difficult to obtain by requiring parents to attend immunisation education courses 26 (see also 27 28 ).

Figure 2 summarises the range of coercive policies that can constitute mandatory vaccination.

Cost of mandatory/coercive vaccination.

Coercion is proportionate

In public health ethics, there is a familiar concept of the “least restrictive alternative”. 28 The least restrictive alternative is the option which achieves a given outcome with the least coercion (and least restriction of liberty).

This is a very weak principle: it uses liberty as tie breaker between options with the same expected utility. More commonly, however, we need to weigh utility against liberty. That is, a more restrictive policy will achieve more expected utility—but is it justified?

According to a principle of proportionality, the additional coercion or infringement in liberty is justified if it is proportionate to the gain in expected utility of the more coercive intervention compared with next best option. That is, additional coercion is justified when the restriction of liberty is both minimised and proportionate to the expected advantages offered by the more coercive policy.

As we can see from the previous section and figure 2, there are a variety of coercive measures. (The Nuffield Council has created a related “Intervention Ladder”, 29 though this includes education and incentives, as well as coercive measures.) Penalties can be high. In war, those who conscientiously objected to fighting went to jail or were forced to perform community service (or participate in medical research). In France, parents were given a suspended prison sentence for refusing to vaccinate their child. 30

While there are legitimate concerns that the effectiveness of these policies in different contexts has been inadequately investigated, a number of these policies have been shown to increase vaccination rates. 31

Notably, the fine or punishment for avoiding taxes varies according to the gravity of the offence. The fine for not wearing a seat belt is typically small. A modest penalty for not being vaccinated in a grave public health emergency could be justifiable. For example, a fine or restriction of movement might be justified.

Figure 3 combines these four factors into an algorithm for justified mandatory vaccination.

Algorithm for mandatory vaccination.

These four factors can be justified in several ways. They represent a distillation and development of existing principles in public health ethics, for example, the least restrictive alternative. They can also be justified by the four principles of biomedical ethics.

For example, justice is about the distribution of benefits and burdens across a population in a fair manner. Justice and beneficence, in the context of vaccination policies, both require that the problem addressed is significant and vaccination is an effective means of addressing it. Non-maleficence requires that the risk imposed on individuals be small. Respect for autonomy and justice both require that coercion be applied only if necessary and that it be proportionate to additional utility of mandatory vaccination (and that such coercion be minimised, which is a feature of proportionality).

It is important to recognise that vaccines may have benefits both to the individual and to others (the community). If the vaccine has an overall net expected utility for the individual, beneficence supports its administration.

How great a sacrifice (loss of liberty or risk) can be justified? The most plausible account is provided by a duty of easy rescue: when the cost to an individual is small of some act, but the benefit or harm to another is large, then there is a moral obligation to perform that act. I have elsewhere argued for a collective duty of easy rescue: where the cost of some act to an individual is small, and the benefit of everyone doing that act to the collective is large, there is a collective duty of easy rescue. 32 Such a principle appropriately balances respect for autonomy with justice.

Whether mandatory vaccination for any disease can be justified will depend on precise facts around the magnitude of the problem, the nature of the disease and vaccination, the availability and effectiveness of alternative strategies and the level of coercion. Elsewhere I compare mandatory vaccination for influenza and COVID-19 in more detail. 27

Better than coercion? Payment for risk

Given the risks, or perceived risks, of a novel COVID-19 vaccine, it would be practically and perhaps ethically problematic to introduce a mandatory policy, at least initially (when uncertainty around safety will be greater). Is there a more attractive alternative?

The arguments in favour of vaccination, particularly for those at lower risk (children, young people and those previously infected) can be based on a principle of solidarity. After all, “We are in this together” has been a recurrent slogan supporting pandemic measures in different countries. Those at low risk are asked to do their duty to their fellow citizens, which is a kind of community service. Yet they have little to personally gain from vaccination. The risk/benefit profile looms large for those at lowest risk.

However, another way of looking at this is that those at low risk are being asked to do a job which entails some risk., so they should be paid for the risk they are taking for the sake of providing a public good. And although it may be unlikely to influence so-called 'anti-vaxxers', it may influence a good portion of the 60% of American adults who responded in a March 2020 poll that they would either delay vaccination or didn’t know about vaccination. 33

I have previously argued that we should reconceive live organ donation and participation in risky research, including challenge studies, 34 as jobs where risk should be remunerated, much like we pay construction workers and other dangerous professions both for the job and for the risk involved. 35 36 While the risk profile for approved vaccinations means that it differs from these examples, it could be compared to a job such as social work as a further argument in favour of payment. People may legitimately be incentivised to take on risks, as the Nuffield Council recognises in its Intervention Ladder. 29

The advantage of payment for risk is that people are choosing voluntarily to take it on. As long as we are accurate in conveying the limitations in our confidence about the risks and benefits of a vaccine, then it is up to individuals to judge whether they are worth payment.

Of course, that is a big ask. It would require government to be transparent, explicit and comprehensive in disclosure of data, what should be inferred and the limitations on the data and confidence. This has often not been the case—one only has to remember the denial of the risks of bovine spongiform encephalopathy (BSE) at the height of the crisis by the British government, when in 1990 the Minister for Agriculture, Fisheries and Food, John Gummer proudly fed his 4-year-old daughter, Cordelia, a hamburger in front of the world’s media, declaring British beef safe. (Gummer was awarded a peerage in 2010 and is now Lord Deben.) 37

There is also a danger that payment might signal lack of confidence in safety. That is a real risk and one that I will address in the “payment in kind” section below.

But the basic ethical point (public acceptability aside) is that, if a vaccine is judged to be safe enough to be used without payment, then it is safe enough to be used with payment. 36 Payment itself does not make a vaccine riskier. If a vaccine is considered too risky to be administered to the population, then it should not be administered, no matter whether coercively, through incentives, or through some other policy.

A standard objection to payment for risk (whether it is risky research or live organ donation) is that it is coercive: it forces people to take risks against their better judgement. In Macklin’s words:

The reason for holding that it is ethically inappropriate to pay patients to be research subjects is that it is likely to be coercive, violating the ethical requirement that participation in research should be fully voluntary. 38

As I have previously argued, 39 this demonstrates deep conceptual confusion. Coercion exists when an option which is either desired or good is removed or made very unappealing. The standard example is a robber who demands “Your money or your life”. This removes the most desired and best option: your money and your life. The Australian “No Jab, No Pay”scheme arguably does constitute coercion as it removes an option that one is entitled to, that is, non-vaccination with the “Pay”. So too is the Italian scheme of fines coercive.

However, paying people is not coercive. Adding an option, like payment, without affecting the status quo is not coercive. If a person chooses that option, it is because they believe that overall their life will go better with it, in this case, with the vaccination and the payment. The gamble may not pay off: some risk might eventuate and then it wasn’t worth it. But that is life—and probability.

It is true that the value of the option might exercise force over our rational capacities, but that is no different from offering a lot of money to attract a favoured job applicant.

What can be problematic about offers is exploitation. Exploitation exists where one offers less than a fair deal and a person only accepts it because of vulnerability from background injustice.

There are two ways to prevent exploitation. First, we can correct any background injustice that might cause it. In this case, the person would have little reason to accept the offer. Second, we can pay a fair minimum price for risk, as when we pay construction workers danger money. Paradoxically, this requires paying more, rather than less. 40

But there is an important additional feature of vaccination. If a vaccine were deemed to be safe enough to offer on a voluntary basis without payment, it must be safe enough to incentivise with payment because the risks are reasonable. It may be that those who are poorer may be more inclined to take the money and the risk, but this applies to all risky or unpleasant jobs in a market economy. It is not necessarily exploitation if there are protections in place such as a minimum wage or a fair price is paid to take on risk.

So payment for vaccination which passes independent safety standards (and could reasonably be offered without payment) is not exploitation, if the payment is adequate.

Undue influence?

A related concern is undue influence. Undue influence means that because of the attractiveness of the offer, I can’t autonomously and rationally weigh up the risks and benefits. It is sometimes understood as “were it not for the money, he would not do it”.

But that formulation is too broad—were it not for the money, many people would not go to work. Rather what the concept of ‘undue influence’ intends to capture is that the offer, usually money, bedazzles a person so that he or she makes a mistake in weighing up the risks and benefits. Someone offers Jones a million dollars to take on a risk of 99.99% of dying in a dangerous experiment. He just focuses on the money and takes a deal which is unfair and unreasonable. However, taking such an offer might be rational. If Jones’ daughter is about to die without a million dollars and he values her life more than his own, it might be both autonomous and rational to take the deal.

Because we cannot get into people’s minds, it is difficult in practice to unravel whether undue influence is occurring—how can you differentiate it from a rational decision? In practice, if it would be acceptable to be vaccinated for nothing, it is acceptable to do it for money. Concerns about undue influence are best met by implementing procedures to minimise bias and irrational decision making, such as cooling off periods, information reframing, and so on.

There remains a lurking concern that a decision where payment is involved may not be fully autonomous or authentic. For example, racial and ethnic minorities are among the groups most gravely affected by COVID-19, but given concerns about systemic racism in research and medicine, these communities may have good reason to distrust the medical machine. Is it acceptable to use payment to get over those concerns?

All we can do practically to address concerns about autonomy and authenticity is to redouble efforts: to ensure we do know the risks and they are reasonable (and that the underpinning research is not itself subject to concerns about systemic racism), and try to foster trust with such public education campaigns. This can work alongside a payment scheme. People still need to understand what the facts are. They still need to make as autonomous and authentic a decision as possible.

Practical advantages

A payment model could also be superior to a mandatory model from a practical point of view. There may be considerable resistance to a mandatory model which may make it difficult, expensive and time-consuming to implement, with considerable invasion of liberty. In a payment model, people are doing what they want to do.

A payment model could also be very cheap, compared with the alternatives. The cost of the UK’s furlough scheme is estimated to reach £60 billion by its planned end in October, 41 and the economic shut down is likely to cost many billions more, as well as the estimated 200 000 lives expected to be lost as a result. 11 It would make economic sense to pay people quite a lot to incentivise them to vaccinate sooner rather than later—which, for example, would speed up their full return to work.

It may be that payment is only required to incentivise certain groups. For example, it may be that young people require incentivising because they are at lower risk from the disease itself. On the other hand, justice might require payment for all taking the risk. Although the elderly and those at higher risk have more to gain personally, they are also providing a service by being vaccinated and not using limited health resources. (There is an enormous backlog of patients in the NHS—another grave threat to public health.)

One particularly difficult case is paying parents to vaccinate their children. It is one thing to pay people to take on risk for themselves; it is quite another to pay them to enable their children to take on risks, particularly when the children have little to gain as they are at lowest risk. In part, the answer to this issue is determined by how safe the vaccine is and how confident we can be in that assessment. If it were safe, to a level that even a mandatory programme would be justified, it may be appropriate to instead incentivise parents to volunteer their children for vaccination. If safety is less certain, payment for risk in this group is the most problematic.

It is true that some mandatory vaccination programmes already fine parents for failure to vaccinate their children. However, in those cases vaccination is clearly in the child’s best interest, as the child receives the benefit of immunity to diseases such as measles, that pose a greater risk to that child than we currently believe COVID-19 does. Moreover, they are for vaccines that have been in place for many years and have a well-established safety profile.

A standard objection to paying people to do their duty, particularly civic duty, is that it undermines solidarity, trust, reciprocity and other community values. This is the argument given by Richard Titmuss for a voluntary blood donation scheme. 42

The UK does not pay donors for blood or blood products, but does purchase blood products from other countries, including Austria where donors are paid a “travel allowance” for plasma donation. In Australia, which runs a donor system, more than 50% of the plasma comes from paid donors in the USA. 43 Altruism is insufficient. Germany recently moved to paying for plasma donors. It does not appear to have undermined German society.

In the end, the policy we should adopt towards COVID-19 vaccination will depend on the precise risks and benefits of the vaccine (and our confidence in them), the state of the pandemic, the nature of the alternatives, and particularly the public appetite for a vaccine.

In the right circumstances, mandatory vaccination could be ethically justified, if the penalty is suitably proportionate.

Payment for vaccination, perhaps, has even more to be said for it.

For those attached to the gift of altruism, the vaccinated could be offered the opportunity to donate their fee back to the NHS (or similar health service provider). This combined “payment-donation” model would be a happy marriage of ethics and economics. It would give altruists a double chance to be altruistic: first by vaccinating and second by donating the fee. It would also couple self-interest with morality for free-riders (as they would have greater self-interest to do what is moral), and it would give those who face obstacles to vaccination an additional reason to overcome these.

Payment in kind

Of course, benefits can come in cash or kind. An alternative “payment” model is to pay those who vaccinate in kind. This could take the form of greater freedom to travel, opportunity to work or socialise. With some colleagues, I have given similar arguments in favour of immunity passports. 44

One attractive benefit would be the freedom to not wear a mask in public places if you carried a vaccination certificate, and not to socially distance. Currently, everyone has to wear a mask and practise social distancing. Relaxing this requirement for those who have been vaccinated (or otherwise have immunity) would be an attractive benefit. Moreover, it would help ameliorate the risks the unvaccinated would pose to others.

Payment in kind has one advantage over cash in that it might not send the signal that vaccination is perceived to be unsafe. A cash payment may paradoxically undermine vaccination uptake by introducing unwarranted suspicion (though this is an intuition that may need to be tested). Benefits in kind are less susceptible to this concern because they are directly linked to the benefit provided by the vaccine itself: the vaccinated person is no longer a threat to others.

Some might object that this represents a form of shaming the non-vaccinators (some of whom might be excluded from vaccination for health reasons), just as presenting those who evaded conscription with a white feather was a method of shaming perceived free-riders. But this could be managed through an education campaign about the justification for face covering requirements. There is a good reason to require the non-vaccinated to continue to wear masks and practice social distancing, regardless of whether their refusal is justified—they do represent a greater direct threat to others.

It is quite possible that some mixture of altruism, financial and non-financial benefits will obviate the need to introduce mandatory vaccination. It is better that people voluntarily choose on the basis of reasons to act well, rather than being forced to do so. Structuring the rewards and punishments in a just and fair way is one way of giving people reasons for action.

Mandatory vaccination can be ethically justified (see figure 3), but when risks are more uncertain, payment for vaccination (whether in cash or kind) may be an ethically superior option.

Acknowledgments

This piece builds on a previous piece I published on the JME blog, Good Reasons to Vaccinate: COVID19 Vaccine, Mandatory or Payment Model? [ https://blogs.bmj.com/medical-ethics/2020/07/29/good-reasons-to-vaccinate-covid19-vaccine-mandatory-or-payment-model/ ]. I would like to thank an anonymous reviewer for very many helpful and constructive comments. I would also like to thank Alberto Giubilini for his help.

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Supplementary materials

• Press release 

Contributors Sole authorship.

Funding JS is supported by the Uehiro Foundation on Ethics and Education. He received funding from the Wellcome Trust WT104848 and WT203132. Through his involvement with the Murdoch Children’s Research Institute, he has received funding through from the Victorian State Government through the Operational Infrastructure Support (OIS) Program.

Competing interests None declared.

Patient consent for publication Not required.

Provenance and peer review Not commissioned; externally peer reviewed.

Data availability statement No data are available.

Linked Articles

• Response Persuasion, not coercion or incentivisation, is the best means of promoting COVID-19 vaccination Susan Pennings Xavier Symons Journal of Medical Ethics 2021; 47 709-711 Published Online First: 27 Jan 2021. doi: 10.1136/medethics-2020-107076

Read the full text or download the PDF:

Other content recommended for you.

• Spoonful of honey or a gallon of vinegar? A conditional COVID-19 vaccination policy for front-line healthcare workers Owen M Bradfield et al., Journal of Medical Ethics, 2021
• The unintended consequences of COVID-19 vaccine policy: why mandates, passports and restrictions may cause more harm than good Kevin Bardosh et al., BMJ Global Health, 2022
• Exploring vaccine hesitancy in care home employees in North West England: a qualitative study Amelia Dennis et al., BMJ Open, 2022
• Persuasion, not coercion or incentivisation, is the best means of promoting COVID-19 vaccination Susan Pennings et al., Journal of Medical Ethics, 2021
• COVID-19 vaccine boosters for young adults: a risk benefit assessment and ethical analysis of mandate policies at universities Kevin Bardosh et al., Journal of Medical Ethics, 2022
• Vaccine mandates for healthcare workers beyond COVID-19 Alberto Giubilini et al., Journal of Medical Ethics, 2022
• No Jab, No Job? Ethical Issues in Mandatory COVID-19 Vaccination of Healthcare Personnel Rachel Gur-Arie et al., BMJ Global Health, 2021
• Evaluating potential unintended consequences of COVID-19 vaccine mandates and passports Maxwell J Smith, BMJ Global Health, 2022
• Healthcare workers’ (HCWs) attitudes and related factors towards COVID-19 vaccination: a rapid systematic review Mei Li et al., Postgraduate Medical Journal, 2021
• Covid-19: Is the UK heading towards mandatory vaccination of healthcare workers? Jacqui Wise, BMJ, 2021

Should COVID-19 vaccines be mandatory? Two experts discuss

Senior Research Fellow, Oxford Uehiro Centre for Practical Ethics, University of Oxford

NIHR Academic Clinical Fellow in Public Health Medicine, UCL

Disclosure statement

Alberto Giubilini receives funding from the Arts and Humanities Research Council/UK Research and Innovation (AHRC/UKRI) and has previously received funding from the Wellcome Trust.

Vageesh Jain is affiliated with Public Health England under an honorary contract as a speciality registrar.

University College London provides funding as a founding partner of The Conversation UK.

University of Oxford provides funding as a member of The Conversation UK.

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To be properly protective, COVID-19 vaccines need to be given to most people worldwide. Only through widespread vaccination will we reach herd immunity – where enough people are immune to stop the disease from spreading freely. To achieve this, some have suggested vaccines should be made compulsory , though the UK government has ruled this out . But with high rates of COVID-19 vaccine hesitancy in the UK and elsewhere , is this the right call? Here, two experts to make the case for and against mandatory COVID-19 vaccines.

Alberto Giubilini, Senior Research Fellow, Oxford Uehiro Centre for Practical Ethics, University of Oxford

COVID-19 vaccination should be mandatory – at least for certain groups. This means there would be penalties for failure to vaccinate, such as fines or limitations on freedom of movement.

The less burdensome it is for an individual to do something that prevents harm to others, and the greater the harm prevented, the stronger the ethical reason for mandating it.

Being vaccinated dramatically reduces the risk of seriously harming or killing others. Vaccines such as the Pfizer , AstraZeneca or Moderna ones with 90-95% efficacy at preventing people from getting sick are also likely to be effective at stopping the virus from spreading, though possibly to a lower degree. Such benefits would come at a very minimal cost to individuals.

Lockdown is mandatory. Exactly like mandatory vaccination, it protects vulnerable people from COVID-19. But, as I have argued in detail elsewhere, unlike mandatory vaccination, lockdown entails very large individual and societal costs. It is inconsistent to accept mandatory lockdown but reject mandatory vaccination. The latter can achieve a much greater good at a much smaller cost.

Also, mandatory vaccination ensures that the risks and burdens of reaching herd immunity are distributed evenly across the population. Because herd immunity benefits society collectively, it’s only fair that the responsibility of reaching it is shared evenly among society’s individual members.

Of course, we might achieve herd immunity through less restrictive alternatives than making vaccination mandatory – such as information campaigns to encourage people to be vaccinated. But even if we reach herd immunity, the higher the uptake of vaccines, the lower the risk of falling below the herd immunity threshold at a later time. We should do everything we can to prevent that emergency from happening – especially when the cost of doing so is low.

Fostering trust and driving uptake by making people more informed is a nice narrative, but it’s risky. Merely giving people information on vaccines does not always result in increased willingness to vaccinate and might actually lower confidence in vaccines. On the other hand, we’ve seen mandatory vaccination policies in Italy recently successfully boost vaccine uptake for other diseases.

Mandatory seatbelt policies have proven very successful in reducing deaths from car accidents, and are now widely endorsed despite the (very small) risks that seatbelts entail. We should see vaccines as seatbelts against COVID-19. In fact, as very special seatbelts, which protect ourselves and protect others.

Vageesh Jain, NIHR Academic Clinical Fellow in Public Health Medicine, UCL

Mandatory vaccination does not automatically increase vaccine uptake. An EU-funded project on epidemics and pandemics, which took place several years before COVID-19, found no evidence to support this notion. Looking at Baltic and Scandinavian countries, the project’s report noted that countries “where a vaccination is mandatory do not usually reach better coverage than neighbour or similar countries where there is no legal obligation”.

According to the Nuffield Council of Bioethics, mandatory vaccination may be justified for highly contagious and serious diseases. But although contagious, Public Health England does not classify COVID-19 as a high-consequence infectious disease due to its relatively low case fatality rate.

COVID-19 severity is strongly linked with age, dividing individual perceptions of vulnerability within populations. The death rate is estimated at 7.8% in people aged over 80, but at just 0.0016% in children aged nine and under. In a liberal democracy, forcing the vaccination of millions of young and healthy citizens who perceive themselves to be at an acceptably low risk from COVID-19 will be ethically disputed and is politically risky.

Public apprehensions for a novel vaccine produced at breakneck speed are wholly legitimate. A UK survey of 70,000 people found 49% were “very likely” to get a COVID-19 vaccine once available. US surveys are similar . This is not because the majority are anti-vaxxers.

Despite promising headlines, the trials and pharmaceutical processes surrounding them have not yet been scrutinised. With the first trials only beginning in April , there is limited data on long-term safety and efficacy. We don’t know how long immunity lasts for. None of the trials were designed to tell us if the vaccine prevents serious disease or virus transmission.

To disregard these ubiquitous concerns would be counterproductive. As a tool for combating anti-vaxxers – estimated at around 58 million globally and making up a small minority of those not getting vaccinated – mandatory vaccines are also problematic. The forces driving scientific and political populism are the same . Anti-vaxxers do not trust experts, industry and especially not the government. A government mandate will not just be met with unshakeable defiance, but will also be weaponised to recruit others to the anti-vaxxer cause.

In the early 1990s, polio was endemic in India , with between 500 and 1,000 children getting paralysed daily. By 2011, the virus was eliminated. This was not achieved through legislation. It was down to a consolidated effort to involve communities, target high-need groups, understand concerns, inform, educate, remove barriers, invest in local delivery systems and link with political and religious leaders.

Mandatory vaccination is rarely justified. The successful roll-out of novel COVID-19 vaccines will require time, communication and trust. We have come too far, too fast, to lose our nerve now.

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• Coronavirus
• Vaccine hesitancy
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Open Access

Peer-reviewed

Research Article

Attitudes on voluntary and mandatory vaccination against COVID-19: Evidence from Germany

Roles Conceptualization, Formal analysis, Writing – original draft, Writing – review & editing

Affiliation DIW Berlin / SOEP, Berlin, Germany

* E-mail: [email protected] (CSP); [email protected] (CS)

Affiliation Karlsruhe Institute of Technology, Karlsruhe, Germany

Affiliations DIW Berlin / SOEP, Berlin, Germany, Freie Universität Berlin, Berlin, Germany

• Daniel Graeber, 
• Christoph Schmidt-Petri, 
• Carsten Schröder

• Published: May 10, 2021
• https://doi.org/10.1371/journal.pone.0248372
• Reader Comments

Several vaccines against COVID-19 have now been developed and are already being rolled out around the world. The decision whether or not to get vaccinated has so far been left to the individual citizens. However, there are good reasons, both in theory as well as in practice, to believe that the willingness to get vaccinated might not be sufficiently high to achieve herd immunity. A policy of mandatory vaccination could ensure high levels of vaccination coverage, but its legitimacy is doubtful. We investigate the willingness to get vaccinated and the reasons for an acceptance (or rejection) of a policy of mandatory vaccination against COVID-19 in June and July 2020 in Germany based on a representative real time survey, a random sub-sample (SOEP-CoV) of the German Socio-Economic Panel (SOEP). Our results show that about 70 percent of adults in Germany would voluntarily get vaccinated against the coronavirus if a vaccine without side effects was available. About half of residents of Germany are in favor, and half against, a policy of mandatory vaccination. The approval rate for mandatory vaccination is significantly higher among those who would get vaccinated voluntarily (around 60 percent) than among those who would not get vaccinated voluntarily (27 percent). The individual willingness to get vaccinated and acceptance of a policy of mandatory vaccination correlates systematically with socio-demographic and psychological characteristics of the respondents. We conclude that as far as people’s declared intentions are concerned, herd immunity could be reached without a policy of mandatory vaccination, but that such a policy might be found acceptable too, were it to become necessary.

Citation: Graeber D, Schmidt-Petri C, Schröder C (2021) Attitudes on voluntary and mandatory vaccination against COVID-19: Evidence from Germany. PLoS ONE 16(5): e0248372. https://doi.org/10.1371/journal.pone.0248372

Editor: Valerio Capraro, Middlesex University, UNITED KINGDOM

Received: October 19, 2020; Accepted: February 25, 2021; Published: May 10, 2021

Copyright: © 2021 Graeber et al. This is an open access article distributed under the terms of the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: Our analyses rely on the German Socio-Economic Panel (SOEP), an independent scientific data infrastructure established in 1984. We, as users, cannot send the data to the journal and make them publicly available, as this is against SOEP's statutes (and most likely against the statutes of all providers of micro data). However, this should not be a hurdle, as researchers from scientific institutions around the globe can access the data (free of costs) once they have signed a user contract. The scientific use file of the SOEP with anonymous microdata is made available free of charge to universities and research institutes for research and teaching purposes. The direct use of SOEP data is subject to the provisions of German data protection law. Therefore, signing a data distribution contract is the single precondition for working with SOEP data. The data distribution contract can be requested with a form which can be downloaded from: http://www.diw.de/documents/dokumentenarchiv/17/diw_01.c.88926.de/soep_application_contract.pdf .

Funding: The data collection of the SOEP-CoV Study was financially supported by the German Federal Ministry of Education and Research. We acknowledge support by the KIT-Publication Fund of the Karlsruhe Institute of Technology. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

Competing interests: The authors have declared that no competing interests exist.

Introduction

Great efforts have been made worldwide to develop a vaccine against COVID-19. When we first drafted this article, in October 2020, 35 different potential vaccines were in clinical trials and 145 were still in the pre-clinical stage. In February 2021, several vaccines have been approved in many countries and are being rolled out, 74 are in clinical trials, and 182 are in the pre-clinical stage [ 1 ].

These developments are very encouraging, as a wide availability of vaccines is seen by many as a prerequisite for a return to a “normal” pre-COVID-19 type of social and economic life. With the growing availability of vaccines comes the hope that coercive measures such as restrictions on international trade, contact restrictions, and travel bans, etc., which cause enormous economic and social costs, may soon be removed and will not need to be reimplemented.

Of course, any vaccine is only an effective contribution to a return to normal life if a sufficiently high number of people are actually vaccinated, yielding herd immunity. If so, vaccination secures a public good: protection from COVID-19 for everyone. From a microeconomic perspective, this raises a well-known problem, free-riding: If the vaccination is freely available but not obligatory, then citizens’ individual decisions determine the extent to which this public good is made available. In order to make that decision, they will weigh their own costs and benefits. These costs include the time sacrificed, physical unpleasantness, possible side effects of a vaccination, etc. The benefits to a particular individual are primarily, but not necessarily exclusively, the reduction in risk to that person’s own health or material well-being. From a welfare perspective, if individuals do not take into account the positive externalities on third parties that their own vaccination triggers, there will be an undersupply of the public good. Following [ 2 , 3 ], individuals’ utility function may also include other-regarding preferences and hence yield a direct benefit from contributions to a public good. In our context, people could therefore benefit from a ‘warm glow of vaccinating’, because by vaccinating themselves they also reduce the risks of others. But even so there is certainly no guarantee that the social optimum will be reached [ 4 ] or that a sufficiently high number of people will freely choose to get vaccinated.

It is frequently argued that vaccination should be made mandatory because of the free-rider problem [ 5 ]: While vaccinated individuals have incurred private costs in terms of discomfort or money and receive the private benefit of a reduced risk of getting the disease, the major collective benefit, the reduced incidence of disease, is public. If enough other people produce the public benefit, and the circulation of the virus decreases accordingly, an individual might rationally decide to free-ride on others’ decisions. A policy of mandatory vaccination would prevent this.

[ 6 ] argue that such a policy would not be necessary: “If vaccinations are perfect, then if one is vaccinated he or she does not care whether others are vaccinated, so there is no longer any public good problem” ([ 6 ], p. 70). Hence there would not be a case in favor of mandatory vaccination, as under such a policy, individuals who would have favored not to be vaccinated are made worse off, while those who anyway would get vaccinated are not better off.

However, by definition, ‘perfect’ vaccination means that everyone vaccinated is perfectly immune [ 6 ]. In the current situation, it can neither be taken for granted that a perfect vaccination is being or will be provided soon, nor that everyone who wants to also will have the possibility to be vaccinated (both financially and in terms of health). If perfect vaccination is not feasible, however, mandatory vaccination is not dominated by a laissez faire solution [ 6 ].

Extensions of this theoretical public good analysis emphasize the relevance of behavioral aspects not typically considered in classical models. The empirical literature also highlights a number of factors that matter for vaccine uptake. For instance [ 7 ], show that social norms matter for an individual’s willingness to get a vaccination and that such norms can suppress vaccine uptake even in the presence of frequent disease outbreaks. Further [ 8 ], show that the design of public vaccination policies should also take intergroup interactions into account. Other-regarding preferences can explain voluntary vaccination uptake, as argued by [ 9 ]. For example [ 10 ], show that the presence of individuals who cannot get vaccinated, like babies and the elderly, increases the willingness to get vaccinated. The static model in [ 6 ] also does not reflect interactive processes [ 9 , 11 ]. show that vaccination is the individually best response until a certain vaccination rate is reached in the population and becomes a social dilemma only from this vaccination rate until herd immunity is maximized. Communicating the social benefits of vaccination can have positive effects, particularly when this protects vulnerable groups, but it can also invite free-riding [ 12 ]. Those people who cannot get vaccinated themselves for medical reasons are particularly vulnerable: they cannot protect themselves even if they wanted to and, hence, depend on their fellow citizens to protect them by preventing the spread of the virus through their vaccination. Children, too, need to be considered separately. Since they cannot give informed consent to a voluntary vaccination themselves, they might have to be protected from their parents (who might be unwilling to get them vaccinated) in case of particularly serious diseases (see [ 13 , 14 ]).

There is, in summary, hope that the public goods problem may be overcome, as social and behavioral science offers a wide array of potential policy options to influence people’s perceptions and reactions to the pandemic (for an extensive up-to-date overview, see [ 15 ]). It is not clear, however, how the research on well-established vaccines carries over to the current pandemic, and recent developments seem to indicate that the willingness to get vaccinated against the novel coronavirus is currently rather low. We therefore chose to investigate two fundamental questions at the opposite extremes of the spectrum of policy options: would a sufficient number of people voluntarily undergo vaccination to achieve herd immunity? Or would a mandatory vaccination against COVID-19 be acceptable to achieve herd immunity?

A legal duty to be vaccinated against COVID-19 could be an alternative to other coercive measures if one assumes that a high-risk, unregulated, laissez faire approach is not a realistic policy option: it seems irresponsible to lift all restrictions because the virus would soon spread through the entire population. Coercive measures of some kind therefore seem inevitable. Mandatory vaccination could be preferable to other coercive measures, provided the interference with bodily integrity would be considered less socially costly in the long run than the effects of prolonged lockdowns. Emotions run high where vaccination policies are concerned, but because mandatory vaccination might become a realistic scenario, it is worth investigating what the general population thinks about such a policy.

It is important to emphasize that a legal duty to vaccinate against COVID-19 would not imply a legal (or even moral) duty to vaccinate against other diseases. The novel coronavirus is a special case in many respects: In contrast to influenza, for example, the population does not have a background immunity from past infections. In addition, many infected people do not show symptoms (a recent meta-study estimates this to be one in six infected [ 16 ]) and, hence, cannot protect others from being infected through voluntary self-quarantining. Thus, people with COVID-19 represent a much higher risk of infection for others than, for example, people who come down with influenza, assuming that these would normally stay at home. Therefore, a vaccination against COVID-19 is much more important from the social perspective than e.g. a vaccination against influenza: not for self-protection, but to protect other people from unintentional infection. Although classic liberal positions (cf. [ 17 ]) would reject a paternalist legal obligation to protect oneself through vaccination, they plausibly would favor a policy of mandatory vaccination in the case of COVID-19 to protect others from being harmed. In modern philosophical discussions, even some libertarians are in favor of mandatory vaccination against serious diseases for similar reasons (see [ 18 ] and for an overview [ 19 ]).

Though there are philosophical reasons supporting a policy of mandatory vaccination, we want to emphasize that we are not advocating it as a concrete policy option for Germany at this moment. Our aim is to understand whether the general public would consider such a policy acceptable, or which sections of the population, and why. To this end, we study the willingness to get vaccinated and the acceptance of a policy of mandatory vaccination against COVID-19 in June and July 2020 in Germany. We use unique real time survey data from a sub-sample (SOEP-CoV) of the German Socio-Economic Panel (SOEP, see [ 20 ]). A set of questions about vaccination was part of the later stages of SOEP-CoV, an ongoing research project initiated in April 2020. This so-called ‘vaccination module’ included questions on the willingness to get vaccinated voluntarily and the acceptance of a policy of mandatory vaccination against COVID-19. In addition, individuals could indicate reasons for their preference regarding the second question. Using the rich data of the SOEP, pre-pandemic income, education, household context, personality, political preferences etc., which can be directly linked with SOEP-CoV, we are able to provide a detailed picture on who intends to get vaccinated and who does not.

The most important result of our study is that about 70 percent of adults in Germany would get vaccinated voluntarily against COVID-19 if a vaccine without significant side effects was available. Further, about half of adults in Germany are in favor, and half against, a policy of mandatory vaccination against COVID-19. The approval rate for mandatory vaccination is significantly higher among those who would get vaccinated voluntarily (around 60 percent) than among those who would not get vaccinated voluntarily (27 percent). However, 22 percent of the individuals would disapprove of both a voluntary and a mandatory vaccination and 8 percent can be characterized as ‘passengers’ (they are not willing to get vaccinated but do support a policy of mandatory vaccination, but they might not all be ‘free-riders’ in the standard sense). In this group, surprisingly, 86 percent state that, without a mandatory vaccination, too few individuals would get vaccinated and about 87 percent indicate that most people underestimate how dangerous COVID-19 is. In general, the willingness to get vaccinated is significantly lower for female, younger, and less educated respondents as well as those with lower income. A policy of mandatory vaccination is rejected with higher probability by women and favored by older people and those living in the eastern federal states.

Data, measures, and methods

Data: soep and soep-cov.

The German Socio-economic Panel (SOEP) is among the largest and longest-running representative panel surveys worldwide and is recognized for maintaining the highest standards of data quality and research ethics [ 20 ]. In 2020, the survey covers about 30,000 adults in 20,000 households. Since the same individuals and households participate in the study every year, life courses of the respondents can be tracked and intertemporal analyses can be carried out at the individual and at the household level. The data contain information on the respondents’ household situation, education, labor market outcomes, and health, among others (see [ 20 , 21 ]).

To better understand the effects of the corona pandemic, a special survey called SOEP-CoV was conducted within the framework of the SOEP, which consisted of a random sample of about 6,700 SOEP respondents, (see [ 21 , 22 ]). SOEP-CoV was surveyed in nine staggered tranches from early April to the end of July 2020 and collected data on the following topics: a) Prevalence, health behavior, and health inequality; b) Labor market and gainful employment; c) Social life, networks, and mobility; d) Mental health and well-being; and e) Social cohesion. Over time, some new question modules were introduced within these five thematic complexes. These included the ‘vaccination module’ (see questionnaires available under www.soep-cov.de/Methodik/ ).

Measures: Preferences toward vaccination against COVID-19

The ‘vaccination module’ went into the field with tranches 7 to 9, in June and July 2020, and covered a total of 851 persons aged 19 years and older. At that moment, major research efforts were being undertaken, but it was not clear whether any vaccine would actually be found. The module hence starts with a question on the hypothetical willingness to get vaccinated against COVID-19:

• “Let us assume that a vaccine against the novel coronavirus that is shown to have no significant side effects is found. Would you get vaccinated?” The response categories are ’Yes’, ’No’, and ‘no answer’. The module contains a further question about mandatory vaccination with the same response categories:
• “Would you be in favor of a policy of mandatory vaccination against the coronavirus?” In addition, the interviewees were asked about their reasons for or against a policy of mandatory vaccination. For this purpose, a filter was used to adapt the arguments according to the respondents’ answers to question (B). The arguments given were as follows:

Argument 1: Others’ willingness to get vaccinated without mandatory vaccination

• Against mandatory vaccination: “Enough people would get vaccinated even without a policy of mandatory vaccination.”
• In favor of mandatory vaccination: “Only with a policy of mandatory vaccination would enough people get vaccinated.”

Argument 2: Misperception of risks

• Against mandatory vaccination: “Most people overestimate the dangerousness of the virus.”
• In favor of mandatory vaccination: “Most people underestimate the dangerousness of the virus.”

Argument 3: Legitimacy of a policy of mandatory vaccinations in general

• Against mandatory vaccination: “A policy of mandatory vaccination is never permissible, even in the case of very dangerous diseases.”
• In favor of mandatory vaccination: “A policy of mandatory vaccinations would make sense also for less dangerous diseases.”

Argument 4: Other reasons (without listing these reasons explicitly)

The first three arguments are of particular relevance for political decision-making. Although there is quite a lot of research on the reasons people have not to get vaccinated themselves, there is much less research on what people think about policies of mandatory vaccinations, and up to present–at least to our knowledge–none on the application to the special case of the novel coronavirus. As the reasons for the individual decision need not carry over to the policy assessment, and given the previously discussed particularities of the coronavirus, we focused on factors that are both of theoretical importance and under discussion in the general public. It would be interesting, for instance, if many people did not have the intention to get vaccinated themselves, yet believed that enough other people would get vaccinated so that mandatory vaccination would not be required. Similarly, it would be surprising if people wanted to get vaccinated yet believed that others overestimated the dangerousness of the virus. Finally, we wanted to see whether people considered mandatory vaccinations potentially legitimate at all.

Sample selection, weighting, and item non-response

Since SOEP-CoV is a random sample from the SOEP population, the SOEP-CoV data 2020 can be linked with the regular SOEP data of previous years. Thus, attitudes toward vaccination against COVID-19 that were collected during the pandemic can be linked to the characteristics of the respondents before the outbreak of the pandemic (e.g., income or educational level). Since these characteristics were collected before the pandemic, they can be considered unaffected by the pandemic event and, hence, exogenous ( S1 File provides definitions of all dependent and independent variables used in the empirical analyses).

The response rate in the vaccination module was high. Altogether, only 4.58 percent of the 851 respondents did not answer the question about voluntary vaccination and 3.41 percent did not answer the question about mandatory vaccination. Of those who supported (objected to) mandatory vaccination, 0.26 (1.82) percent did not provide at least one motive in the follow-up question. Hence, bias from item non-response should be small and we did not correct for it. As the focal variables are coded dichotomously (yes = 1; no = 0), there was no need to remove outliers in them from the database.

To derive population-wide estimates, the SOEP-CoV data is equipped with frequency weights. The weighting of SOEP-CoV follows the standard weighting used in SOEP [ 23 , 24 ]. Based on the SOEP household weights, weights for all persons in the participating households were generated via a marginal adjustment step and corrected for selection effects. Furthermore, the data were corrected for the fact that some SOEP subsamples were excluded from the SOEP-CoV study from the outset. To address potential selection effects and adjust frequency weights accordingly, we followed the two-step procedure recommended in [ 25 ]:

• Step 1: Estimation of a logistic regression model where the dependent variable is a dummy variable indicating whether respondents belong to the working sample of tranches 7 to 9 (dummy is equal to one) or not (dummy is zero). All variables included in the following analyses serve as explanatory variables.
• Step 2: If at least one analysis variable shows a significant (i.e., p -value below 0.05) and at the same time meaningful effect (i.e., coefficient above 0.01) with respect to the assignment to the analysis population, a correction of the SOEP-CoV weights is performed by multiplying the frequency weights by the inverse estimated probability. In other words, multiplying the SOEP-CoV weights belonging to the analysis set by the inverse predicted probability yields the sought adjusted weight that can be used to calculate population statistics. In the present case, an adjustment using the following variables is indicated: Extraversion and whether respondents live in a household in which at least one household member was tested for COVID-19. Overall, selection on observables is very minor. Unless otherwise stated, our results are weighted with the adjusted probability weights.

Statistical framework

Since the vaccination questions are answered once by each respondent, our empirical strategy is between-person. Uni- and bivariate results for our focal variable, attitudes toward vaccination, are presented as weighted means or percentages. Assessments of differences in attitudes or characteristics between-groups rely on two-tailed t-tests, with statistical significance evaluated at p <0.01, p <0.05, and p <0.10 using the survey weights explained above. Our empirical strategy involves multiple between-group tests. This raises the question of whether a correction is necessary for multiple hypotheses testing. We do not implement such a correction because we seek to compare a certain attitude or characteristic between groups and not to draw, at the end of the test series, a concluding summary of all tests results.

Willingness to get vaccinated and attitudes toward a policy of mandatory vaccination

For the questions on voluntary vaccination (A) and mandatory vaccination (B), four groups in the population may be distinguished:

• Anti-vaccination: interviewees who would not get vaccinated voluntarily against the coronavirus and who also oppose a policy of mandatory vaccination.
• Anti-duty: interviewees who would get vaccinated voluntarily but oppose a policy of mandatory vaccination.
• Passengers: interviewees who would not get vaccinated voluntarily but are in favor of mandatory vaccination. We refer to this group as ‘passengers’ because they apparently want to see the public good of herd immunity provided by mandatory vaccination, yet would not voluntarily contribute to this good. Some of these passengers might be free-riders in the standard sense, trying to benefit from the decisions of others while not voluntarily contributing themselves, while others might not be able to get vaccinated for medical reasons. If mandatory vaccination were introduced, the first group, but not the second, would also get vaccinated, of course. Neither group would actually free-ride, but the first might initially have wanted to.
• Pro-vaccination: interviewees who would get vaccinated voluntarily and are also in favor of mandatory vaccination.

Overall, 70 percent of adults in Germany would voluntarily get vaccinated against the coronavirus, provided a vaccine without significant side effects was available ( Table 1 : groups 2 and 4). This value corresponds exactly to the results of [ 26 ]. From May till September 2020, the COVID-19 snapshot monitoring (COSMO) at the University of Erfurt showed relatively constant values of between 60 and 66 percent; it was only in April that it showed an exceptionally high value of 79 percent, and it has now decreased further (cf. [ 27 ], p. 76; an overview of previous studies on the willingness to get vaccinated in Germany is provided in S2 File .). Overall, these studies paint a consistent picture, with a slight decline in the willingness in the second half of 2020.

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https://doi.org/10.1371/journal.pone.0248372.t001

Approximately half of the interviewees are against, and half are in favor of, a policy of mandatory vaccination (against: 51%, groups 1 and 2, in favor: 49%, groups 3 and 4). These values, too, coincide almost exactly with those of the COSMO monitoring since May 2020 (cf. [ 27 ], p. 78), which in April showed an approval rate for mandatory vaccination of 73 percent, but later discontinued this question (till July 2020, and it has been decreasing since; see S2 File ). The agreement with a policy of mandatory vaccination is clearly higher, namely almost 60 percent (41/(41+29) = 0.59) among those who would get vaccinated voluntarily than with those who would not let themselves be vaccinated voluntarily, i.e. approximately 27 percent (8/(8+22) = 0.27).

Attitudes toward a policy of mandatory vaccination

The four groups differ noticeably in how they assess the arguments presented to them. This is shown in Table 2 , which gives the group-specific approval rate for each argument in combination with the p-values of t-tests in S3.1 Table in S3 File .

https://doi.org/10.1371/journal.pone.0248372.t002

Argument 1.

The groups differ markedly in how likely they think it is that others will get vaccinated. Among the two groups that are against a policy of mandatory vaccination, 56 percent of the ‘anti-vaccination’ group (who would not get vaccinated voluntarily) think that their fellow citizens would get vaccinated sufficiently frequently such that mandatory vaccinations would not be necessary. Almost 80 percent of the ‘anti-duty’ group (the members of which would get vaccinated voluntarily) think the same. Among the two groups that are in favor of mandatory vaccination, 85 percent of the ‘passengers’ (who would not voluntarily get vaccinated) think that the others would not voluntarily get vaccinated either, as do slightly more than 90 percent of the ‘pro-vaccination’ group (who would also get vaccinated voluntarily).

Argument 2.

These results run in parallel with the assessment of the dangerousness of the virus. Even though the analysis is not causal, we can see that about 50 percent of the ‘anti-vaccination’ group and 30 percent of the ‘anti-duty’ group think that most people overestimate the dangerousness of SARS-CoV-2. Exactly the opposite, that most people underestimate the dangerousness, is believed by nearly 90 percent of the ‘passenger’ group and by slightly more than 80 percent of the ‘pro-vaccination’ group. Summarizing the numbers differently, one could say that groups 2 and 4, who would voluntarily get vaccinated, probably have similar opinions about whether their fellow citizens correctly assess the danger posed by the virus. About 80 percent of the members of the ‘pro-vaccination’ group think that most people underestimate the danger. Of the members of the ‘anti-duty’ group, we only know with certainty that 30 percent of them believe that most people overestimate the danger–we do not know, however, how the remaining 70 percent are divided between ’underestimate’ and ’correctly estimate’. The difference between the corresponding values for groups 1 and 3 is significantly higher.

Looking at arguments 1 and 2, we may conclude that there is a high level of disagreement among the population about the dangerousness of the virus. This disagreement probably explains why people have such different attitudes toward getting vaccinated and toward the necessity (or not) of a policy of mandatory vaccination.

The position of the group of the ‘passengers’ is hard to understand. On the one hand, they favor a policy of mandatory vaccination, presumably because, as they do believe, the dangerousness of the virus is often underestimated. On the other hand, they probably assume that they themselves do not underestimate that dangerousness, but nevertheless would not get vaccinated voluntarily. One reason for this could be their medical condition: they might be willing but unable to get vaccinated for medical reasons. If so, they would not be trying to free-ride. It is unclear, however, how much weight the appeal to such a hypothetical medical contraindication should have, given that at the time of the interviews, no vaccine was even available. Some, but not all, of the ‘passengers’ are probably free-riders in the standard sense.

Argument 3.

Approximately 40 percent of both the ‘anti-vaccination’ group and the ‘anti-duty’ group agree with the statement that a mandatory vaccination is never permissible, not even with very dangerous diseases. Since these two groups reject mandatory vaccination against COVID-19, this means that for the remaining 60 percent of the group, mandatory vaccination may well be permissible–but apparently only for diseases that they would have to consider as even more dangerous than COVID-19. Conversely, well over 60 percent of the ‘passenger’ group and just over 70 percent of the ‘pro-vaccination’ group agree with the statement that a policy of mandatory vaccination would also make sense for less dangerous diseases. In combination with the results for argument 2, these two groups could therefore believe that their fellow citizens also underestimate the danger of such other diseases. It is interesting to note that, overall, people in Germany estimate the probability that the novel coronavirus will cause a life-threatening disease within the next twelve months to be high (cf. [ 20 ]). This probability is around 25 percent across our four groups. In group 1 it is 20 percent, in group 2 around 27 percent, in group 3 it is 30 percent and in group 4 it is 25 percent (see Table 3 ).

https://doi.org/10.1371/journal.pone.0248372.t003

Other reasons (which were not further broken down in the questionnaire for capacity reasons) are important primarily among those respondents who would not themselves get vaccinated and also oppose mandatory vaccination. Although questions (A) and (B) explicitly assume that a vaccine would not have any significant side effects, this could be due to a deeper skepticism about vaccination, which we hope to be able to explore in future research (on ’vaccine denialism’ see [ 28 ]).

Characteristics of the ‘anti-vaccination’, ‘anti-duty’, ‘passenger’, and ‘pro-vaccination’ groups

Description of the individual characteristics of the groups..

We would like to know in more detail who is in favor of a policy of mandatory vaccination against COVID-19 and who is opposing it, as well as what the socio-economic characteristics of those who would get vaccinated and of those who would not are. Table 3 shows how the four groups defined above differ across various socio-demographic characteristics (measured before the pandemic), personality (measured before the pandemic), health (before and during the pandemic), and political orientation (measured before the pandemic). Statistical t-tests for the significance of differences in characteristics between groups are shown in S3.2 Table in S3 File assuming equal variances across groups. S3.3 Table in S3 File provides supporting evidence: tests for equality of variance across groups provides support for this assumption in about 90% of the cases, and as S3.4 Table in S3 File . shows, relaxing the equality of variances assumption does not change our conclusions.

Socio-demographic characteristics . Almost 60 percent of the ‘anti-vaccination’ group are female, they are on average 48 years old, 12 percent of them have a university degree and their monthly net household income in 2019 averaged just under EUR 2,800. Around 27 percent have children under 16 and around 17 percent live in the eastern German states. ‘Passengers’ do not differ in their characteristics statistically significantly from this group. The members of the ‘anti-duty’ group, by contrast, are much more likely to be male and more often have a university degree. In comparison to the ‘anti-vaccination’ group, the members of the ‘pro-vaccination’ group are also more often male and older, and are also more likely to have a university degree. In particular, older interviewees are more likely to be in groups that favor mandatory vaccination and persons with a university education in groups comprising those who would get vaccinated voluntarily.

Personality traits . SOEP collects the personality traits of the respondents using a battery of questions that measure the five dimensions of the so-called ’Big Five’ [ 29 ]. The Big Five are the five most important groups of character traits in personality research: ’openness’, ’conscientiousness’, ’extraversion (sociability)’, ’tolerance’, and ’neuroticism’. Furthermore, risk attitude is surveyed. We see that members of the ‘anti-vaccination’ group tend to be more sociable but less open than the other groups. Their willingness to take risks is similar to that of the members of the ‘anti-duty’ and of the ‘pro-vaccination’ groups, but is significantly higher than that of ‘passengers’. Members of the ‘anti-duty’ group are particularly unsociable compared to the other groups, but open to new experiences. The ‘passengers’ are, like the members of the ‘pro-vaccination’ group, less neurotic. They are particularly tolerable and the least willing to take risks of the four groups.

Health . As far as the health of those surveyed is concerned, statistically significant differences are only evident in the number of illnesses: Members of the ‘anti-vaccination’ group have significantly fewer risk diseases than ‘passengers’ and members of the ‘pro-vaccination’ group. ‘Anti-duty’ members, on the other hand, have significantly fewer diseases than the ‘passengers’. Thus, overall, it may be said that those who refuse a policy of mandatory vaccination have fewer risk diseases at the time of the survey. There are no differences between the groups in terms of whether a member of the respondent’s household has already undergone a test for an infection with corona. It should be noted, however, that the number of cases of those tested for an infection is comparatively small.

Political orientation . As far as the political orientation of the respondents is concerned, no systematic significant differences between the four groups are identified. Only the members of the ‘anti-vaccination’ group seem to be positioned somewhat more to the right in the party spectrum than the members of the ‘anti-duty’ group.

Multivariate description of the characteristics of the four groups.

The differences and similarities with regard to group composition described above always refer to a single characteristic, i.e. they are univariate. Additionally, the relationships between individual characteristics of the respondents–after taking other characteristics into account–and their attitude toward mandatory or voluntary vaccination are explained below using a multivariate model (logistic estimation; see Eq ( 1 )). The dependent variable is either an indicator that describes the respondent’s own willingness to get vaccinated voluntarily (value 1 = yes; 0 = no; Table 4 ) or an indicator (value 1 = yes; 0 = no) that describes whether the respondents favors a policy of mandatory vaccination ( Table 5 ). As our interest is the explanation of data structures, we do not use survey weights in the multivariate analysis.

https://doi.org/10.1371/journal.pone.0248372.t004

https://doi.org/10.1371/journal.pone.0248372.t005

With regard to the willingness to voluntarily get vaccinated ( Table 4 ), some significant differences in socio-demographic characteristics are observed. If all other characteristics are kept constant, the willingness to vaccinate is about 10 percentage points lower in women than in men. It is positively associated with age (0.4 percentage points per year of life), education (13 percentage points if respondents have a university degree compared to the other education categories), and household income (2.5 percentage points per 1,000 euros). The personality traits of the Big Five do not correlate with the respondents’ willingness to vaccinate; only openness is slightly positively associated with the willingness to vaccinate. In the health block, there is also only one significant variable that correlates with the willingness to get vaccinated: The higher the respondents estimate the probability that the virus could trigger a life-threatening disease in them, the more willing they are to be vaccinated.

A policy of mandatory vaccination ( Table 5 ) is also rejected with higher probability by women, but favored by older people and those living in the eastern federal states, ceteris paribus . Approval is negatively associated with neuroticism, i.e. emotional instability, and positively associated with the subjective probability of contracting life-threatening COVID-19.

The tables presenting the logit estimations include an initial model diagnostic: the Pseudo- R 2 . In S4 File , we present two additional model diagnostics: First, the linktest for both logit models does not find any evidence for model misspecifications. Second, a receiver operator characteristic (ROC) analysis provides evidence that the predictive power of our two models is acceptable. In addition, to assess multicollinearity, we have computed variance inflation factors (VIF) in S5 File . As a rule of thumb, a variable whose VIF values exceeds 10 may merit further investigation. In both regressions, the VIF of none of the explanatory variable exceeds 7.7 and the average VIF over all variables is below 2.1. It should also be noted that the two separate logit models do not model correlation and heteroscedasticity between the two outcomes (vaccinate voluntarily or obligatorily). Hence, in S6 File , as a robustness check, we have estimated a multivariate probit model using Stata’s mvprobit command that relies on simulated maximum likelihood [ 30 ]. S6.1-S6.6 Tables in S6 File compare the coefficients of the multivariate probit with the two separate models. Overall, there are some changes in the magnitude of the coefficients, but no changes in the signs of the regression coefficients or significance levels.

It is possible that respondents who did not give an answer about their vaccination preferences–for example, because they are still undecided–would decide to vaccinate or support mandatory vaccination after an adequate vaccination campaign. In a robustness check, we followed this argument by assigning respondents who refused to answer the question about voluntary or mandatory vaccination to the ‘yes’ category and repeated the logit estimation. This does not change our results (see S7.1 and S7.2 Tables in S7 File , S8 File provides our Stata code, which prepares the data and conducts all the statistical analyses, as well as the outputs of the multivariate estimations).

Finally, Table 6 provides a statistical comparison of the marginal effects from the model on willingness to get vaccinated ( Table 4 ) and attitudes toward mandatory vaccinations ( Table 5 ). We find no significant differences in marginal effects between the two models except for two variables: tertiary education and eastern federal states. The marginal effect for tertiary education is significantly larger for the willingness to get vaccinated model while the opposite is true for eastern federal states.

https://doi.org/10.1371/journal.pone.0248372.t006

Politicians must make decisions which are based on incomplete information yet have far-reaching consequences for public health, personal freedom, and economic prosperity. It seems that many citizens are prepared to behave responsibly in the sense that they are prepared to endure a ‘little sting’ for the good of all: a vast majority of the German population (70 percent) state that they would get vaccinated as soon as a vaccine against COVID-19 was available. This means that under favorable conditions, a legal duty to get vaccinated to achieve herd immunity might not be necessary. It should, however, be noted that the question was asked in a stylized context: Potential side effects or ineffectiveness of the then hypothetical vaccine were assumed away. Though there is no reason to believe the vaccines currently being administered are more problematic in this respect than any other vaccines in use, neither can strictly be guaranteed in reality. In addition, the time required for a vaccination, the process of the vaccination itself (i.e. the injection), bureaucratic administration (e.g. making an appointment with the family doctor) or any necessary co-payment should de facto reduce the willingness to get vaccinated. Furthermore, at the time of writing, not only is it still unclear how quickly a vaccine can even be produced in the quantity required and administered to enough people, it is also unclear how long its effect will last. It is not even clear what percentage of the population would have to be vaccinated to achieve herd immunity, as this also depends on individual behavior and legal (or ethical) norms which are likely to continue to change (e.g. an explicit or implicit obligation to wear a mask of a specific variety in public transport or a testing obligation for people returning from trips abroad) [ 31 , 32 ]. Hence, a sufficiently high willingness to get vaccinated in the ‘best case’ scenario investigated here is an idealization and in any case only one relevant factor among many.

We observed there to be gender differences in the willingness to get vaccinated: women are less willing to get vaccinated, and also less willing to support a policy of mandatory vaccination. This is surprising, given that men are generally less likely to engage in preventive behavior [ 33 ] and women have been shown to be more willing to engage in preventive behavior in the pandemic, for instance by wearing face masks when recommended [ 34 ], and they also seem to be more compliant with other measures in general [ 35 ]. However, men are also more severely affected by the coronavirus [ 36 ] and women generally more skeptical about vaccinations, especially against COVID-19 [ 37 ]. We don’t know whether our interviewees frame their decision to get vaccinated or not as a situation of a social dilemma, but if so, previous results on gender differences in cooperation suggest men and women might have to be addressed differently to influence their decisions [ 38 , 39 ]. We also observed that income and education increase the willingness to get vaccinated voluntarily. It has also been shown recently that the willingness to pay for a vaccine against Covid-19 is positively impacted by, among other variables, income [ 40 ].

A mandatory vaccination would almost certainly achieve herd immunity against COVID-19, since all those for whom there is no medical contraindication would also get vaccinated. About half of the respondents approve and disapprove, respectively, of such a mandatory vaccination policy. In this context, the strong disagreement among the participants of the study regarding the dangerousness of the virus is particularly striking. Many of those who reject a policy of mandatory vaccination assume the dangerousness of the virus is being overestimated by others, while those who approve of a policy of mandatory vaccination seem to believe the exact opposite. This is highly problematic: at most one of the two groups can be right. Plausibly, the interviewees themselves differ in how dangerous they think the virus is. This yields a concrete and important policy recommendation (see also [ 40 , 41 ]): we need more reliable data on the dangerousness of SARS-CoV-2 and to communicate this data more clearly to the general public. Though the ‘knowledge-deficit’ explanation of low vaccine uptake might not work for well-established vaccines [ 42 ], we have found evidence that this might be different for COVID-19.

We are not recommending a policy of mandatory vaccination in this paper, but merely investigating the attitudes of people towards it. A policy of mandatory vaccination would be an extreme solution to solve the potential problem of low vaccine uptake, and a lot may be said in favor of less extreme policies (as outlined in [ 15 ], for instance). Vaccination could also be made mandatory only for certain groups of people (e.g. nurses, physicians, physiotherapists, people working in confined spaces, people travelling on public transport etc.), or only after time has conclusively shown that not enough people actually get vaccinated. It might also turn out that people are unwilling to take the second dose of a two-dose vaccine, or not accept refresher doses, which would further complicate the situation and might require subtle intertemporal strategy choice. Before making any vaccination mandatory, people could also be paid or incentivized in other ways to accept it [ 43 ]. If, as we hope, people take the external effects of their action into account, and a sufficiently high number of people get vaccinated as a result, mandatory vaccination won’t be necessary.

This article investigates the willingness to get vaccinated and the acceptance of a policy of mandatory vaccination against COVID-19 in June and July 2020 in Germany. Our first main result is that a large majority of about 70 percent of adults in Germany would voluntarily get vaccinated against the novel coronavirus if a vaccine without side effects was available. Our second result is that about half of this population is in favor of, and half against, a policy of mandatory vaccination. Our third main result is that the individual willingness to get vaccinated and acceptance of a policy of mandatory vaccination correlates systematically with several socio-demographics (gender, age, education, income) but, overall, not with psychological characteristics of the respondents.

When interpreting the results from our survey, it should be noted that preferences were elicited in an ideal-typical situation: a vaccine which is effective and free of side effects is immediately available for the entire population at zero cost. Future research will have to show how actual vaccination behavior differs in real-life situations that deviate from this ideal-typical situation.

Supporting information

S1 file. variable definitions..

https://doi.org/10.1371/journal.pone.0248372.s001

S2 File. Comparison with further studies in Germany.

https://doi.org/10.1371/journal.pone.0248372.s002

S3 File. Complementary estimation results.

https://doi.org/10.1371/journal.pone.0248372.s003

S4 File. Additional diagnostics for the logit models.

https://doi.org/10.1371/journal.pone.0248372.s004

S5 File. Multicollinearity across explanatory variables.

https://doi.org/10.1371/journal.pone.0248372.s005

S6 File. Functional form assumptions and simultaneity.

https://doi.org/10.1371/journal.pone.0248372.s006

S7 File. Imputation.

https://doi.org/10.1371/journal.pone.0248372.s007

S8 File. Stata code.

https://doi.org/10.1371/journal.pone.0248372.s008

Acknowledgments

We thank Thomas Rieger for his outstanding research assistance.

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• Open access
• Published: 09 November 2023

To vaccinate or not to vaccinate? The interplay between pro- and against- vaccination reasons

• Marta Caserotti 1 ,
• Paolo Girardi 2 ,
• Roberta Sellaro 1 ,
• Enrico Rubaltelli 1 ,
• Alessandra Tasso 3 ,
• Lorella Lotto 1 &
• Teresa Gavaruzzi 4  

BMC Public Health volume  23 , Article number:  2207 ( 2023 ) Cite this article

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By mid 2023, European countries reached 75% of vaccine coverage for COVID-19 and although vaccination rates are quite high, many people are still hesitant. A plethora of studies have investigated factors associated with COVID-19 vaccine hesitancy, however, insufficient attention has been paid to the reasons why people get vaccinated against COVID-19. Our work aims to investigate the role of reasons in the decision to get vaccinated against COVID-19 in a representative sample of 1,689 adult Italians (March–April 2021) balanced in terms of age, gender, educational level and area of residence.

Through an online questionnaire, we asked participants to freely report up to three reasons for and against COVID-19 vaccination, and the weight each had in the decision to get vaccinated. We first investigated the role of emotional competence and COVID-19 risk perception in the generation of both reasons using regression models. Next, we studied the role that the different reasons had in the vaccination decision, considering both the intention to vaccinate (using a beta regression model) and the decision made by the participants who already had the opportunity to get vaccinated (using a logistic regression model). Finally, two different classification tree analyses were carried out to characterize profiles with a low or high willingness to get vaccinated or with a low or high probability to accept/book the vaccine.

High emotional competence positively influences the generation of both reasons (ORs > 1.5), whereas high risk perception increases the generation of positive reasons (ORs > 1.4) while decreasing reasons against vaccination (OR = 0.64). As pro-reasons increase, vaccination acceptance increases, while the opposite happens as against-reasons increase (all p  < 0.001). One strong reason in favor of vaccines is enough to unbalance the decision toward acceptance of vaccination, even when reasons against it are also present ( p  < 0.001). Protection and absence of distrust are the reasons that mostly drive willingness to be vaccinated and acceptance of an offered vaccine.

Conclusions

Knowing the reasons that drive people’s decision about such an important choice can suggest new communication insights to reduce possible negative reactions toward vaccination and people's hesitancy. Results are discussed considering results of other national and international studies.

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Introduction

By mid 2023 the European Union reached nearly 75% vaccine coverage for the primary vaccine cycle against COVID-19, with countries such as Croatia, Slovakia, and Poland falling short of 60% and others such as France, Portugal, and Italy close to 90% [ 1 ]. Although vaccination rates are, on average, quite high, many people are still hesitant. Vaccine hesitancy indicates the delay or refusal of a vaccine despite availability in vaccine services [ 2 , 3 ] and is a multidimensional construct, resulting from the interaction between individual, social, and community aspects [ 4 ]. In the last two years, a plethora of studies have investigated factors associated with COVID-19 vaccine hesitancy showing, for example, that vaccine hesitancy is higher in women [ 5 , 6 ], in young people [ 5 , 7 , 8 ], in people with low education [ 8 , 9 ], low trust in authorities [ 10 , 11 ], and strong conspiracy beliefs [ 5 , 12 , 13 ]. However, to the best of our knowledge no one has investigated the interplay that pro- and against- vaccination reasons may play in the choice to get vaccinated, namely what happens when a person has both pro- and against-vaccine considerations. Trying to fill this gap in the literature, our work aims to investigate how different reasons and the importance people place on them are likely to influence the decision to get vaccinated against COVID-19.

In line with the vaccine hesitancy continuum defined by SAGE [ 2 ], while extremely pro-vax people are likely to express only reasons pro-vaccination and extremely no-vax people are likely to express only reasons against vaccination, individuals who fall between the two extreme end-points are likely to feel some doubts. This large number of people offer us the unique opportunity to assess which category of reasons (pro- vs. against- vaccination) is more impactful in driving people's vaccination decisions. As it is reasonable to imagine, among the reasons for choosing to get (or not) vaccinated some reasons are more rational, while others are more related to affect. For example, there are people who rationally recognize the importance of vaccines but at the same time are frightened by the side effects. Thus, the decision to get (or not) vaccinated is the result of a complex process, in which costs and benefits are weighed more or less rationally. Indeed, while several studies have pointed out that the decision to vaccinate is due to cognitive rather than emotional processes [ 14 , 15 , 16 , 17 ], others have highlighted the role of affect and risk perception in the vaccination decision [ 18 , 19 , 20 ]. Thus, the intention to accept the vaccine is driven by emotional and affective feelings as much as by cognitive and rational judgments. Particular attention to what people feel and think about vaccine-preventable diseases and vaccination in general is paid in the model developed by the “Measuring Behavioral and Social Drivers of Vaccination” (BeSD), a global group of experts established by the World Health Organization [ 21 ]. This model encompasses two groups of proximal antecedents of vaccination, namely, what people think and feel (e.g., perceived risk, worry, confidence, trust and safety concerns) and social processes (e.g., provider recommendation, social norms and rumors). Antecedents affect vaccination motivation (i.e., vaccination readiness, willingness, intention, hesitancy), which can then be strengthened or weakened by practical issues (such as vaccine availability, convenience and cost but also requirements and incentives), resulting in acceptance, delay or refusal of vaccination (vaccination behavior).

Although some studies have considered whether the cognitive or affective component has greater weight in determining the intention to vaccinate, no one, to the best of our knowledge, has studied the interplay between pro- and against- vaccination reasons, nor the weight these have in the choice to vaccinate. In addition to the drivers already studied in the literature [ 5 , 6 , 7 , 8 , 11 , 12 ], we believe that the focus on this interaction may be relevant to better understand the complex phenomena related to vaccine hesitancy. Few recent studies have attempted to investigate the complexity of vaccination choice by studying the reasons why people choose to get (or not) vaccinated against COVID-19. Fieselmann and colleagues [ 22 ] highlighted that among the reasons that reduce adherence to vaccination are a low perception of its benefits, a low perception of the risk of contracting COVID-19, health concerns, lack of information, distrust of the system, and spiritual or religious reasons. Another study, instead, shed light on the reasons that encourage hesitant people to consider vaccination, such as protecting themselves, their family, friends and community from COVID-19, and being able to return to normal life [ 23 ].

In the present study we asked the participants to spontaneously come up with their own reasons to get (or not) vaccinated, without limiting or influencing them with a set of predefined options to choose from, thus aiming to obtain more genuine answers that may better capture the intuitive aspect of people’s opinions (for a similar reasoning see [ 24 ]). The procedure we used has been implemented by Moore et al. [ 23 ], the only study, as far as we know, that asked for reasons with an open-ended question. Critically, in their study, participants were asked to report only reasons in favor of vaccination (e.g., "What are your reasons for getting the COVID-19 vaccine?"), excluding reasons against. By contrast, we asked participants to freely report up to three reasons in favor and up to three reasons against COVID-19 vaccination and to rate on a 5-point Likert scale their weight in the decision about getting (or not) vaccinated.

From a theoretical point of view, the reasons pro- and against vaccination may be seen within the framework of prospect theory [ 25 , 26 ] which suggests that people evaluate the outcome of a choice based on a reference point, against which losses and gains are determined: the former below this point, the latter above this point. Importantly, especially in this specific context, losses and negative consequences are weighted more than gains and benefits, making us hypothesize that if a person has one reason for and one reason against the vaccine, which are of equal importance, they will more likely lean toward choosing not to vaccinate. Consistently, it is known that negative experiences have a greater impact than neutral or positive ones (i.e., the negativity bias [ 27 ]).

Besides delving into the reasons that may influence the choice to get (or not) vaccinated, it would be interesting to also look at the individual differences that may determine the reporting of pro- and against- vaccination reasons and their valence. In this regard, the literature suggests that risk perception and emotion regulation can both have a great impact in the decision to get vaccinated. For instance, studies conducted during H1N1 influenza have shown that perception of disease-related risk is one of the strongest predictors of vaccine adherence [ 28 , 29 ]. Additional insights have been provided by more recent studies investigating the role of COVID-19 risk perception in the decision to get vaccinated against COVID-19. Viswanath and colleagues [ 30 ] showed that people are more willing to vaccinate themselves and those under their care to the extent to which they feel more vulnerable to COVID-19 and rate the consequences of a possible infection as severe. Such a relationship between COVID-19 risk perception and intention to vaccinate was confirmed by another study using a cross-sectional design, which focused on the early months of the pandemic [ 31 ]. This study also examined how risk perception changed during the pandemic phases and showed that during the lockdown, compared to the pre-lockdown phase, also those who reported some hesitancy were more likely to get vaccinated when they perceived a strong COVID-19 risk.

With regard to emotion regulation, the literature suggests that people react differently to affective stimuli [ 32 ] and that their decisions are influenced by their abilities to regulate emotions [ 33 , 34 ]. Recent works investigating the relationship between hesitancy in pediatric vaccinations and the emotional load associated with vaccinations, have shown that a negative affective reaction is one of the factors leading to lower vaccine uptake [ 35 , 36 ]. Specifically, Gavaruzzi and colleagues [ 36 ] showed that concerns about vaccine safety and extreme views against vaccines are associated with vaccine refusal. Interestingly, they also showed that parents' intrapersonal emotional competences, i.e., their ability to manage, identify, and recognize their own emotions, is critical to vaccine acceptance for their children. Therefore, in our study we measured people's risk perception and emotional competencies to assess their possible role in the production of reasons in favor and against vaccination.

As described in Fig.  1 , the relationship between different domains of interest can be hierarchically structured, using a directed acyclic graph, starting from the risk perception and emotion regulation, to the generation of pro- and against- vaccination reasons and their valence, and finally to the vaccination willingness/adherence. With respect to the mentioned structure, we are interested to investigate the following research hypotheses:

The number and weight associated with reasons pro- and against-vaccination should be influenced by individual differences in the ability to regulate emotions;

The number and weight associated with pro-vaccination reasons should be influenced by individual differences in COVID-19 risk perception;

A higher number of strong (i.e., with high weight) reasons pro- (vs. against-) vaccination should correspond to a more (vs. less) likelihood to accept the vaccination.

Generating an equal number of reasons in favor and against vaccination should lead to a weaker likelihood to accept the vaccination.

Directed Acyclic Graph (DAG) between variables considered in the study (PEC: Short Profile of Emotional Competence scale)

As we conducted the study between March and April 2021, a time when vaccinations were being progressively rolled out, we decided to consider the role of personal reasons on both the intention to get vaccinated (for those who had not yet had the opportunity to get vaccinated) and the choice already made (e.g., vaccine received or booked vs. refused).

Finally, through a non-parametric classification analysis, we will explore how specific pro- and against-vaccination reasons impact the decision to get (or not) vaccinated. Specifically, we will investigate the role that different categories of reasons play in the choice to vaccinate.

Participants

Data collection was commissioned to a survey and market research agency (Demetra Opinions.net), with the aim of securing a representative sample of the adult (+ 18) Italian population, estimated at 49.8 million [ 37 ]. The sample was balanced in terms of age, gender, educational level (middle school or lower, high school, degree or higher), and area of residence (North, Center, South, and Islands). The agency distributed via email the survey link to its panelists, who freely decided whether to participate in the study in exchange for financial compensation. Out of 1,833 participants who started the questionnaire, 77 (4%) were excluded because they did not complete the survey and 16 (0.9%) were excluded since they reported offensive content in open-ended questions. Finally, 124 (6.8%) participants were excluded because of missing information. Thus, the final sample consisted of 1,689 participants. The project was approved by the ethical committee for Psychology Research of the University of Padova (Italy), with protocol number 3911/2020 and informed consent was obtained for all participants.

We developed an ad-hoc questionnaire including a series of open-ended and closed questions (see Additional file 1 : Appendix 2 for the full material). We first investigated the vaccination status of the participants, asking whether they already had received at least the first dose, whether they had booked it or were still ineligible, and finally whether they had refused the vaccination. Those not yet eligible were asked to rate how likely they would be to get vaccinated at the time they responded (0 =  Not at all likely , 100 =  Extremely likely ). Then, we asked participants to report a maximum of three reasons both in favor of the COVID-19 vaccine and against it (in counterbalanced order) and to rate how much each of the reported reasons weighed in their choice to vaccinate or not, on a 5-point likert scale (1 =  Not at all , 5 =  Extremely ). Due to the sparsity on the rate and the number of provided reasons we re-coded the provided information into two semi-quantitative variables, one for pro- and one for against- vaccination reasons, as following: missing/invalid reasons, low average rating (answers 1–3 on the Likert scale) and 1–3 reasons, high rating (answers 4–5 points on the Likert scale) and 1 reason, and high average rating (answer 4–5 points on the Likert scale) and 2–3 reasons.

The questionnaire also included the 20-item Short Profile of Emotional Competence scale (S-PEC; [ 38 ]) to measure intra- and inter-personal emotional competences separately. The intra-personal scale (10 items) refers to emotional competences related to oneself and it includes items such as "In my life I never make decisions based on my emotions'' or "I don't always understand why I react in a certain way". The inter-personal scale (10 items) refers to emotional competences related to other people and it includes items such as “If I wanted, I could easily make someone feel uneasy” or “Most of the time, I understand why the people feel the way they do”. All items are answered on a 7-point likert scale (1 =  Not at all agree , 7 =  Completely agree ). The internal consistency of the S-PEC scale, measured by means of Cronbach’s α, was adequate (α = 0.81). Further, we measured participants' risk perception of COVID-19 by asking them to indicate how scared they felt of the virus, how serious they think the disease is, how likely they think they are to get sick, and how worried they feel about the various mutations [ 10 , 31 ]. We then asked participants to report their age, gender, educational level, their occupation (health workers, white-collar workers, entrepreneurs, other non-health-related contract forms, and the unemployed), whether they already had COVID-19 (No or don't know, Yes asymptomatic, Yes with few symptoms, and Yes with severe symptoms). The questionnaire was pilot tested by 30 participants who filled the questionnaire first then were asked to discuss and comment on the comprehension of the wording of questions and answer options. Two questions were slightly reworded to improve clarity.

Scoring of reasons

In the first instance, a bottom-up process from reasons to categories was followed by reading a sample of both types of reasons, with the aim of constructing initial categorizing patterns. Examples of pro-vaccination reasons include protection of personal and public health, return to normality, and civic duty; while reasons against vaccination include fears for one's health, sociopolitical perplexity, and distrust of science and institutions (see Additional file 1 : Appendix 1). At this stage, response information was added to the categorizations indicating whether the responses were valid or missing/invalid. Specifically, valid responses had both a reason and the respective weight; missing/invalid responses were those where reason, weight or both were missing or with utterly unrelated concepts or meaningless strings or letters. Finally, by applying a top-down process, we constructed macro categories by merging specific conceptually assimilated categories, so as to avoid the dispersion of data into too many ramifications (see Table S 5 ).

Statistical analysis

Descriptive analysis.

All the analyses were performed only on respondents with no missing observations on the variables of interest (1,681, 92%) excluding also a limited number of those with a non-valid set of pro- or against-vaccination reasons (Table S 1 ; 0.9%). The study variables were summarized in frequency tables and figures (frequency for categorical variables, median and Interquartile Range (IQR) for continuous variables). Kruskal–Wallis tests were computed to compare the distribution of continuous variables across the categories of vaccine status. Categorical variables were compared using chi-squared or Fisher's exact test where expected frequencies in any combination were less than 10. Statistical significance was assumed at the 5% level.

COVID-19 Perceived risk—exploratory factor analysis

An Exploratory Factorial Analysis (EFA) was performed on groups of variables related to COVID-19 perceived risk: scare, severity, contagiousness, and the likelihood of mutation. Since the presence of limited support (0–100 scale) and non-normal marginal distribution, the EFA was performed using a weighted least square mean and variance adjusted (WLSMV) estimator. We extracted from the EFA only the first factor, which explained the highest percentage of variance (Table S 2 ; 61%). The estimated loadings were then used to calculate the regression factor scores. The number and the name of items included, their internal consistency (Cronbach’s α), the estimated loadings, and the proportion of deviance explained are reported in Table S 2 .

Propensity score weighting

At the time of data collection (March–April 2021), the vaccine offer was not opened to the entire population. To adjust the estimates of the following regression models for the propensity to receive the vaccine, we estimated a logistic regression model in which the dependent variable was the response to the question about a previous vaccination offer (Yes/No), while all the factors that can influence the vaccine proposal served as independent variables: age-class (young ≤ 25, young adult 26–45, adult 46–65, elderly 66–84), gender (male, female), occupational status (health worker, not at work, not health worker-employer, not health worker-entrepreneur, not health worker-other), educational level (low = middle school or lower, medium = high school, high = degree or higher), key worker status (yes, no, I don’t know), past COVID-19 contagion (no, yes asymptomatic, yes low symptoms, yes severe symptoms), and familiar status (single/in a relation, married/cohabitant, divorced/separated/other). The predicted probability was used to estimate the weights for the following regression models using a framework based on an inverse probability of treatment weighting (IPTW; for further details, see [ 39 ]).

Regression models

Our research questions can be summarized by trying to describe the relationship exploited by the directed acyclic graph in Fig.  1 . The first step regression model aims to assess how S-PEC scores (inter- and intra-personal) and COVID-19 risk perception influenced the reasons pro- and against-vaccination produced by participants while considering the presence of a set of confounders (age-class, gender, occupational status, educational level, key worker status, and familial status).

Since both the pro- and against-vaccination reasons are formed by a categorical variable with 4 levels (missing/invalid, low 1/2/3 reasons, high 1 reason, high 2/3 reasons), we evaluated whether S-PEC and COVID-19 risk perception scores influenced the distribution of pro- and against-vaccination reasons employing two different multinomial regression models including all the previously mentioned variables (S-PEC, COVID-19 risk perception, and confounders). The overall significance of a variable in the model was tested using an analysis of the variance (ANOVA).

The second step in the analyses was taken to investigate whether the generation of pro- and/or against-vaccination reasons affected the willingness to be vaccinated or the vaccine acceptance. Each participant reported their willingness to get vaccinated on a 0–100 scale or, in case a COVID-19 vaccine had been already offered, their vaccination status (done, booked, or refused). For respondents who had not yet been contacted for booking/getting the vaccination, we evaluated whether pro- and/or against vaccination reasons influenced the willingness to be vaccinated by employing a beta regression model in which the respondent variable scale (0–100) was rescaled to be a relative frequency [ 40 ]. The full models included the semi-quantitative pro- and against-vaccination reasons variables and, even if non-statistically significant, all the confounders in order to adjust for age class, gender, educational level, occupational status, familial status, and key worker status. Beta regression coefficients were estimated using a maximum likelihood estimator (MLE). Results were presented in terms of Odds Ratios (ORs) by exponentiating the estimated coefficients and producing a relative 95% Confidence Interval (95% CI).

A further regression analysis was conducted through a logistic regression model to explain which factors influenced vaccine acceptance (done/booked vs. refused) among those who already received the vaccine offers. The full model included the same variables considered in the previous beta regression model, after recoding the variables related to pro- and against-vaccination reasons into a binary form (missing/invalid vs. presence of at least one valid reason) due to low sample size and the sparsity of the response variable. As a consequence, we tested a simplified version of Hypothesis 3, considering the presence (vs. missing/invalid) of pro- or against-vaccination reasons in order to test their influence on the probability of having accepted/booked the vaccination.

Results were reported employing ORs and relative 95% Confidence Interval (95% CI).

Both the beta regression and logistic regression were weighed using an IPTW scheme to take into account the presence of a different probability of a vaccine offer among respondents.

The presence of an interaction between pro- and against-vaccination reasons was tested by means of a likelihood ratio test. The regression models were estimated through the R 4.0 program (R Core Team, 2021), and for the beta regression we employed the betareg package [ 41 ].

Classification tree analysis

Two different classification tree analyses were carried out to characterize profiles with a low or high willingness to get vaccinated (respondents who had not yet been offered a vaccine) or with a low or high probability to accept/book the vaccine (respondents who had already received a vaccine offer).

Although the dependent variables were non-normally distributed (scale 0–100 or binary 0/1), we considered them continuously distributed adopting a splitting criterion based on the analysis of the variance (ANOVA). We tested the inclusion in the model considering the type of pro- or against-vaccination reasons. A tree pruning strategy was adopted to reduce classification tree overfitting considering the overall determination coefficient (R 2 ) as an indicator and fixing that at each classification step in the tree if the R 2 did not increase by 0.5% the tree should be stopped. Classification tree analysis was performed using the rpart package [ 42 ] on R environment [ 43 ].

The main characteristics of the respondents by vaccination status (received, booked, not yet, and refused) were reported in Table 1 . Among respondents, 23.3% were offered the vaccination and, among them, 13.8% refused it (Fig. S 1 ). Among those not yet eligible, willingness to be vaccinated showed a median value of 80 points (average: 68.7). The distribution of gender was almost equal (51% females, 49% male), and the median age was 47 years old (IQR: 34–57 years). Educational level was low in 41% of the sample, while the most represented employment status was not at work (39%) followed by employed (37%), and entrepreneur (9.8%). A quarter (26%) of respondents classified themselves as key workers during the COVID-19 pandemic. The predominance of respondents (63%) were married or living with a partner, while only 9% had had a COVID-19 infection.

COVID-19 risk perception and the S-PEC score (intra- and inter-personal) were categorized into three categories according to empirical tertiles (low:1 st tertile, medium: 2 nd tertile, high: 3 rd tertile). The level of COVID-19 risk perception differed across vaccination status ( p  < 0.001). The reasons pro- and against-vaccination have a different distribution according to COVID-19 vaccination status (Table 2 ). The highest frequency of pro-vaccination reasons was reported by those who received the COVID-19 vaccination; conversely the lowest frequency of pro-vaccination reasons was generated by those who refused the vaccine, whereas, intermediate frequencies were shown by people who were not yet offered the vaccination and those who had booked the vaccine, who reported a comparable distribution of the number of pro-vaccination reasons. A reverse pattern was exhibited for against-vaccination reasons, which were generated with the highest percentage by respondents who refused the vaccine (in particular high and multiple reasons). Conversely those who have booked/done the COVID-19 vaccine showed the lowest frequency of reasons against vaccination, while respondents without a vaccine offer reported an intermediate frequency of reasons against vaccination.

The estimated results of the propensity score model for the vaccine offer are shown in Table S 3 . Respondents older than 65 years exhibited a nearly four-fold increase in the probability to be contacted for the vaccination with respect to the reference age-class (≤ 25 years). All non-health employees showed a high drop in the probability of having received the vaccination offer, while the probability increased as the educational level increased. Being a key worker during pandemic resulted in an increased probability of having received the vaccination proposal while no statistical significant influence was observed for the past COVID-19 contagion or for familial status. The distribution of the propensity score by vaccine status obtained by the model is reported in Fig. S 1 , in which it is shown that the distribution is different by vaccine offer, but the two density functions partially overlap. The discriminant power of the propensity score estimated was only discrete (ROC analysis, AUC: 71.8%).

The results of the multinomial regression models which investigated the effect of emotional competences and risk perception on the generation and the predictors of pro- and against-vaccination reasons with respect to missing/invalid level and the reference categories are presented in Table 3 (see also Fig.  1 ). Compared to the reference category (missing/invalid), high values of S-PEC-self were associated with a higher probability to report pro- and against-vaccination reasons (all ORs > 1.5), while high values of S-PEC-others were associated with a mild probability to report multiple pro-vaccination reasons (all ORs > 1.42). A high (vs. low) COVID-19 risk perception increased the frequency of one strong pro-vaccination reason while it had a null or low decremental effect on the frequency of against weak vaccination reasons. Further, medium (vs. low) COVID-19 risk perception only increased the strong pro-vaccination. Compared to the reference age-class (young), adults and elderly showed a higher probability to generate a strong unique pro-vaccination reason (adults vs. young OR: 1.72, 95%CI: 1.07–2.77); elderly vs. young OR: 2.24, 95%CI: 1.26–4.00), while lower probability to generate against vaccination reasons was observed for elderly compared to young respondents (OR: 0.48, 95%CI: 0.26–0.90). Female participants generated fewer strong pro-vaccination reasons (ORs < 0.73), and also fewer multiple weak against-vaccination reasons (OR: 0.68, 95%CI: 0.51–0.91) compared to male participants. Overall, the occupational status did not affect the generation of pro- and against-vaccination reasons (ANOVA test p  > 0.05); however an increased frequency of low 1/2/3 against-vaccination reasons emerged among the category “Other—not health workers” compared to the reference group represented by health workers (OR: 2.52, 95%CI:1.09–5.86). Pro-vaccination reasons are more frequent as the educational level becomes higher, while the relation of the educational level with against- vaccination reasons appears weaker and significantly increased only for the presence of multiple weak reasons against vaccination (High vs. Low educational level, OR: 2.10, 95%CI: 1.45–3.03). Not being a key worker is related to a higher frequency of multiple strong both pro- and against vaccination reasons. The familiar status did not seem to be related to the frequency or the strength of the reasons, except for the status of divorced/separate/other that, with respect to the reference category single/in a relation, showed a twofold increase in the frequency of a strong unique against vaccination reason.

Through a beta regression model we investigated the predictors of willingness to be vaccinated for the participants who had not yet received the vaccination offer. As shown in Table 4 , the generation of pro- and against-vaccination reasons strongly influences the willingness to be vaccinated. The predicted probability from the combination of pro- and against-vaccination reasons is shown in Fig.  2 (and Table S 4 ): respondents who did not report any reasons had an average predicted probability above 60%, while the presence of at least one reason against vaccination decreased the willingness to be vaccinated, in particular in the case of strong multiple against vaccination reasons. On the other hand, the presence of at least one pro-vaccination reason strongly increased the probability. In the end, the presence of both strong multiple pro and against vaccination reasons resulted in a high probability of getting the vaccine. Regression models adjusted by propensity score weighting allowed us to comment the influence of potential confounders: males reported an increased willingness to be vaccinated (vs. females; OR: 1.26, 95%CI: 1.11–1.42), and so did those with a high educational level (vs. low; OR: 1.22, 95%CI: 1.04–1.44) while the opposite was true among no key workers (vs. key workers; OR: 0.85, 95%CI: 0.72–0.99).

Predicted willingness to get vaccinated by interaction between pro- and against-vaccination reasons

Finally, with a logistic model we investigated the predictors of vaccine acceptance\booking. As shown in Table 5 , people who accepted or booked the COVID-19 vaccine were more likely to show pro-vaccination reasons and less likely to show against-vaccination reasons. Interestingly, when both kinds of reasons were provided, the probability of getting/booking the vaccine remained nevertheless very high (Fig.  3 ). Compared to the age class [46-65], younger age classes reported a strong reduction in the probability to have accepted/booked the vaccine. Male participants (OR: 1.53, 95%CI: 1.10–2.12) and those with a high educational level (OR: 2.65, 95%CI: 1.60–4.54) showed an increased probability of vaccine acceptance/booking when compared to females and participants with medium educational level, respectively. Being a health worker had a strong and positive influence on the probability of getting/booking the vaccine with respect to those employed as no health workers (OR: 6.61, 95%CI: 2.10–30.9).

Predicted COVID-19 vaccine acceptance/booking probability by interaction between pro- and against-vaccination reasons

Two regression tree models were estimated separately on the willingness to be vaccinated for those who had not yet received the vaccine offer and on the booking/acceptance of the vaccination in case of vaccine offer. Results are shown in Fig.  4 . Considering the willingness to be vaccinated, the presence of distrust in the vaccination was the most discriminant variable; this latter in conjunction with reasons related to protection, herd immunity, and the absence of no clinical trials guided the willingness to be vaccinated. In particular, the combination of the absence of reasons related to distrust and the presence of protection reasons showed the highest values on the intention to get vaccinated (average value = 83 points, 22% of the sample). On the other side, the presence of at least one reason related to distrust without any positive reasons concerning protection, herd immunity, and trust predicted the lowest willingness to be vaccinated (average value = 29 points, 6% of the sample).

Regression tree for the willingness to be vaccinated (left) and for COVID-19 vaccine acceptance/booking (right) by selected type of pro- and against-vaccination reasons

The sense of protection given by the vaccine or the trust in the vaccination was the main reason for vaccination acceptance/booking (average probability = 0.96 and 1.00, 33% and 5% of the sample, respectively). The combination of the absence of protective reasons and the presence of doubts about the lack of clinical studies results in the lowest likelihood of accepting/booking the vaccination (average probability = 0.40, 3% of the sample). The presence of distrust and the belief in herd immunity were the other discriminant reasons with intermediate results in terms of the probability to accept/book the vaccination.

The frequency of each category of pro- and against-vaccination reasons by COVID-19 vaccine status is shown in Table S 5 .

In the present study we aimed to investigate the reasons behind the decision to get (or not) vaccinated against COVID-19 by asking participants to report up to three reasons in favor and three reasons against the COVID-19 vaccination and to indicate the weight these reasons had in their decision. Although some researchers discourage categorization, the sparsity of the responses related to the number of reasons and their weight implies a semi-quantitative solution since a simple variable multiplication between rating and frequency (recoding to zero in case of zero reasons) is not feasible. In this case, this approach was not satisfactory as such coding would not allow differences underlying identical scores to emerge. For example, only 1 strong motivation (rating 5) would be coded in the same way as three motivations with weights 1, 2, and 2. Instead, we decided to categorize the combination of frequency-weight reasons as categorical variables (missing/invalid, low 1/2/3 reasons, high 1 reason, high 2/3 reasons) in which rating and number of reasons are combined into a single variable. This categorization allows us not only to study the weight that different categories have on the decision to get vaccinated but also to overcome the risk of imputing a specific value for missing responses.

As shown in Fig.  1 , analyses were run in two steps. The first step aimed to assess how emotional competences and risk perception impacted the generation of reasons pro- and against-vaccination (Hypotheses 1A and 1B), whereas the second step investigated how different reasons affected the intention to get vaccinated (Hypotheses 2 and 3). The results support the hypotheses that emotional competences and risk perception play a significant role. Regarding emotional competence as measured by the S-PEC, the results show that high intra-personal emotional competence positively influences the production of stronger and more numerous pro-vaccination and against-vaccination reasons (confirming Hypothesis 1A). This result suggests that greater awareness of one's emotions and of what one is feeling promotes higher fluency in the production of reasons about the vaccination. Research has shown that people can be ambivalent about vaccines and hold both positive and negative reasons [ 2 , 44 ]. It is reasonable to assume that, compared to people with low intra-personal emotional competences, those with high intra-personal emotional competences are more likely to have higher awareness of these contrasting attitudes and to embrace them without suppressing one of the two stances. Furthermore, the results showed that only high inter-personal emotional competences influence the generation of multiple strong reasons in favor of vaccination, and this appears to be related to the perception of vaccines as a public good and a tool to protect others. As for risk perception, a moderate to high perception of risk associated with COVID-19 influences the generation of strong pro-vaccination reasons (confirming Hypothesis 1B). These results are in line with the literature showing that a high perception of risk associated with COVID-19 positively influences the decision to get vaccinated [ 30 , 31 , 45 , 46 , 47 ]. In particular, perceiving a medium/high risk leads to generating a high number of reasons strongly in favor of vaccination, while reducing the number and weight of the reasons against the vaccine. The main premise of the psychological literature examining the relationship between risk perception and affect is that one’s behaviors are affected by rapid and intuitive evaluations, either positive or negative, people make while assessing things happening around them [ 48 , 49 ]. Thus, an event is evaluated not only on the basis of objective information, but also on the basis of the experienced feelings. Emotional competence, which is clearly related to affect, also modulates how we perceive and process the emotional component underlying our judgments [ 36 ].

The results also show that, compared with younger people, those over 45 more frequently produce reasons in favor of vaccines while those over 65 produce fewer reasons against vaccination. These results are in line with the fact that younger people are at lower risk of severe consequences than older people [ 50 ], but can also be explained by considering that age was particularly salient during the period of the data collection, as the vaccination campaign was phased out by age groups, starting from the elderly. As for gender, women produced less strong pro-vaccine and weak-against vaccine reasons than men. These results are congruent with the general findings in the literature on vaccine hesitancy showing that females are more hesitant than males [ 5 , 51 , 52 ]. Furthermore, medium and high educational levels favored the production of both pro- and against-vaccination reasons, whereas not being in a relationship or being divorced/separated increased the generation of a strong reason against vaccination. Consistent with previous work [ 53 ], we confirmed that non-health professionals participants or non-key workers categories showed a lower intention to get vaccinated and a higher likelihood of having refused the vaccine compared to health care and key workers.

Once the role of demographics aspects and individual differences on the generation of reasons pro and/or against vaccination had been established, we ran two additional models to assess the role that those reasons have on the decision to accept the vaccination (see Fig.  1 ). More specifically, we tested the hypothesis that a higher number of pro- (vs. against-) vaccination reasons, connoted by a higher weight, corresponded to a stronger (vs. weaker) acceptance of vaccination (Hypothesis 2). Since data collection took place between March and April 2021, when the vaccination campaign had already started in Italy, we developed two different regression models, with the first investigating the willingness to be vaccinated in participants who were not yet offered the vaccine and the second investigating the likelihood of accepting/booking or refusing the vaccine in those who already received the offer. In particular, thanks to the propensity score weighting technique, we managed to reduce the estimates bias, especially for those factors (age, occupational status, and educational level) that influenced the vaccine offer the most [ 54 ]. The results of the two models are very similar, as the intention to get vaccinated and the likelihood of having accepted/booked the vaccine are predicted by the same factors. Specifically, the production of strong positive reasons increases either the intention to get vaccinated or having accepted/booked the vaccination. In contrast, generating strong negative reasons reduces vaccination intention and predicts the refusal of the vaccination. Hypothesis 2 is thus confirmed.

Results on the interactions between reasons, pro- and against-vaccination, and vaccination intention or vaccination choice are particularly worthy of attention. The third hypothesis was derived from the literature on prospect theory [ 25 , 26 ], suggesting that at equal intensity subjective losses are more important in determining a decision than subjective gains. We therefore expected that negative reasons would count more than positive reasons in deciding whether to get vaccinated or to accept the vaccine. However, in contrast to our hypothesis, the results showed that just the generation of a single positive reason with a strong weight was enough to shift behavior and attitude in favor of the vaccination, regardless of the number and weight of negative reasons. In other words, vaccine refusal is predicted by the absence of any positive strong reasons, while when people generate both positive and negative reasons, the positive ones seem to yield a particularly important role when having a strong weight. According to prospect theory, people evaluate their goals depending on the reference point they focus on. During the pandemic, the vaccination offered an opportunity to be safer, reduced the risk of infection, and more generally appeared as the best way to re-open and get back to life as it was before COVID-19. After a year of pandemic characterized by periods of lockdown and some re-opening attempts, people were likely feeling in a state of loss (e.g., the lost freedom to go out and meet with friends and family, the lost freedom of traveling) and were looking forward to whatever chance available to recover and return to their previous lifestyle and habits. Just as those who gamble are willing to do anything to make up for a loss, so probably those who were not entirely certain about the vaccine were more willing to take risks to recover the loss in quality of life. It follows that the pandemic emergency made people forgo some of their doubts about the vaccine when, at the same time, they had reasons to get their shot. In addition, several studies [ 19 , 55 , 56 ] have highlighted the relationship between anticipated regret and vaccination, showing that anticipated regret is associated with an increased likelihood of adhering, or having one's children adhere, to vaccine offerings. Trusting that the vaccine would work, focusing less on its potential side effects, made sense for people who were looking forward to recovering what was perceived (and was indeed) a loss of quality of life and freedom, because they desired to be back doing the things had ever enjoyed doing (e.g., going to restaurants, movies, etc.). This finding is also interesting from a communicative perspective: providing positive reasons that resonate well with people and have therefore a strong weight for them could offset their doubts, yielding to a greater acceptance of COVID-19 vaccination.

Therefore, it is crucial to consider what kind of reasons drive the decision toward or against vaccination. Allowing participants to openly report their reasons pro- or against- vaccination can facilitate a freer exploration of the concerns and reservations of the most hesitant individuals [ 24 ], thus providing valuable insights for shaping future vaccine-related communications. In fact, thanks to the regression tree on vaccination intention, it emerges that positive attitudes toward vaccines are strongly determined by "Protection" and "Community Protection" reasons. The fact that the sense of individual and collective protection is among the principal determinants of the decision with respect to COVID-19 vaccines suggests that in general vaccination is seen as a means of avoiding nefarious clinical consequences. The effect of the sense of communal protection as the reason favoring vaccination and of other-oriented S-PEC in determining the generation of multiple pro-vaccine motivations confirms previous results suggesting that people often are more willing to get vaccinated primarily to protect their loved ones [ 57 , 58 , 59 ], especially when they have a good understanding of how community immunity works [ 60 , 61 ]. However, it is worth mentioning that, at the time the study was conducted (March–April 2021), there was still uncertainty about whether COVID-19 vaccines could provide sterilizing immunity (i.e., could prevent the transmission of the infection) in addition to protecting the individual. To foster people's willingness to get vaccinated, it is crucial from a public health perspective that people understand that even when vaccines do not yield sterilizing immunity, vaccination can still increase protection of others by reducing the circulation of the virus.

The reasons that influenced the willingness to be vaccinated or the vaccination acceptance/booking were generally in line with the existing literature, although they differed depending on whether respondents had already been offered a vaccine or not: among those who did not received a vaccination offer, the main reasons promoting vaccination acceptance were protection against COVID-19 for oneself, one's family, friends, and community [ 23 ], while among the main reasons that reduced vaccination adherence for those who got the vaccine offer we found the lack of clinical trials [ 62 , 63 ], as well as the distrust of institutions and science [ 22 ]. This latter emerged as the most reported negative reason by those who have refused the vaccine and those who have not yet received the vaccine offer. Thus, effective communication aimed at defusing the perception of risk regarding vaccines themselves should focus on enhancing trust in the scientific process and experimental rigor. Indeed, these reasons were deemed as very important not only by those who refused the vaccination, but also by those who had not yet been offered the vaccine, and even by those who held mixed feelings but eventually chose to get vaccinated. While it is unlikely that individuals firmly against vaccination will be persuaded by simple interventions [ 64 ], we should keep in mind that vaccine hesitancy is a dynamic process. As such, reducing hesitancy or enhancing ambivalence, for example through motivational interviewing (e.g., [ 65 , 66 ]), could potentially lead to small shifts towards greater vaccine acceptance.

Our findings are also in line with the results of other international studies that have used a qualitative approach to examine reasons for and against vaccinations. For example, Hamilton and colleagues [ 67 ] employed a qualitative content analysis to extract the main motivations for and concerns about COVID-19 vaccination from medical records obtained by 102 consults in Australia. The study was conducted in June 2021, and revealed that most consults were driven by doubts about the vaccine available and recommended at that time (i.e., ChAdOx1-S, also known as Vaxzevria), followed by need for further information regarding vaccines and vaccination, also considering specific comorbidities. Notwithstanding the peculiarity of the Australian context in which a very low number of COVID-19 infections was observed, the analysis performed by Hamilton et al. [ 67 ] revealed a set of themes that largely overlaps with the reasons identified in our study. Indeed, among the reason to get vaccinated, 5 themes emerged: a) Protection, b) Occupational or facility responsibility or requirement, c) Trust in primary healthcare physician, d) Autonomy, and e) Civic duty, likewise, concerns about vaccination were mainly in terms of: a) Perceived vaccine risks, b) Perceived vaccine performance, c) Uncertainty, d) Autonomy, and e) Fairness in access. An aspect worth noting is that after the consultation, 81% of participants received the vaccination, 19% did not. Consistent results were observed in another study by Purvis and colleagues [ 68 ] conducted in the USA, which focused specifically on “hesitant adopters”, i.e. those who accepted vaccination but showed some level of hesitancy. To note that in this study the focus was on factors influencing the decision to get the COVID-19 vaccine, not on reasons against it. The authors interviewed 49 participants as a follow up of a larger study ( N  = 2022) conducted from mid-September 2021 through mid-October 2021, to explore factors that influenced their decision-making process about COVID-19 vaccination [ 68 ]. Two main themes emerged, each with four subthemes: 1) sociocultural context (political, cultural, health professionals, employment, and media environment) and 2) individual and group influences (attitudes and beliefs related to vaccines, family and social networks, free to return to normal, and COVID-19 outcomes).

As for the Italian context, to the best of our knowledge, only one study (i.e., [ 69 ]) attempted to provide a qualitative examination of the concept associated with vaccination in general, through open-ended and closed questions. Notably, this study was conducted a year later than our own study (April–May 2022) and was administered to a non-representative sample of Italians. The authors used a combination of closed and open-ended questions to assess concepts associated with vaccination in general. Consistent with our findings, Boragno et al. reported that participants who had been vaccinated against COVID-19 (92% of the sample) frequently mentioned concepts related to protection and salvation, whereas those who were not vaccinated frequently mentioned mistrust and ambivalence as concepts associated with vaccination [ 69 ].

This study has some limitations. First, COVID-19 perceived risk score was obtained only with respect to the disease and a similar score should be of interest for the COVID-19 vaccine. Second, data were collected during a vaccine offer limited to a well-defined slice of the population and the investigation on the vaccine acceptance/booking has, as a consequence, a limited sample size. Finally, the lack of a longitudinal perspective does not allow us to evaluate how strong the association is between the willingness to get vaccinated, vaccine acceptance and potential changes in risk perception. Thus, we cannot generalize our results beyond the period of data collection and to other countries or health systems. Since the dynamics have now changed, results may not apply to the decision to get a booster shot or not or an annual shot, however it might be interesting to study what motivations are most relevant now. Likewise, it remains to be established whether our results are generalisable to other populations.

Future studies could consider how the interaction between perceived risk associated with the disease and perceived risk associated with the vaccine influences the choice to get the shot. Furthermore, it would be important to explore how we can harness the reasons that most hold back vaccination in a specific communication strategy for the most hesitant people. Moreover, at the time of data collection, the vaccination campaign was still at an early stage, and only a small portion of the population had already received their shot. Therefore, we believe that it might be of particular interest to know more in detail, with a larger sample, what are the reasons that to date, almost 2 years after the release of the vaccine, still make some people reject the vaccine. Only by knowing these reasons will it be possible to develop appropriate vaccination campaigns.

In conclusion, our work examined pro- and against-vaccination reasons and how these, and their interaction, influence the decision to get vaccinated or not. Specifically, high emotional competence and risk perception influence the generation of pro- and against-vaccination reasons and that the presence of a strong pro-vaccination reason shifts intention toward vaccination. We also highlighted the category of reasons that influence intention to vaccinate. That said, given that the discussion about the next doses is still open and that in any case the next pandemic is a matter of when and not if [ 70 ], it is of paramount importance to know the best way to counteract vaccine hesitancy, fostering more effective communication strategies.

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Centers for Disease Control and Prevention. Why it matters: The pandemic threat. Retrieved December. 2020;1:2020.

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Additional file 1: appendix 1..

Scoring for pro- and against-vaccination reasons.  Appendix 2. Structure of the questionnaire. Table S1. Selection criteria. Table S2. Number of items, internal consistency (Cronbach’s α), name of the items and their estimated loadings, total deviance explained by the loadings and proportion of variance explained by EFA for COVID-19 perceived risk. Table S3. Odds ratios (ORs) estimated by the logistic model for the propensity score weighting for the COVID-19 vaccine offer. Table S4 . Predicted willingness to get vaccinated by combination of pro- and against-vaccination reasons by category of reference.  Table S5. Frequency of reported categories of pro- and against-vaccination reasons overall, and by COVID-19 vaccine status. Figure S1. Distribution of the propensity scores by vaccine offer.

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Caserotti, M., Girardi, P., Sellaro, R. et al. To vaccinate or not to vaccinate? The interplay between pro- and against- vaccination reasons. BMC Public Health 23 , 2207 (2023). https://doi.org/10.1186/s12889-023-17112-6

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Opinion: Why COVID-19 Vaccines Should Not Be Required for All Americans

• Previous: Intro: Is It Time to Require COVID-19 Vaccines?
• Next: Yes, Nobody Has the Right to Infect Others

Should the COVID-19 Vaccine Be Required for All Americans?

As covid-19 vaccine mandates spark controversy, two public health experts debate blanket requirements..

Editor’s note: This set of commentaries was originally published in 2021. It has been republished as part of The Forum, a U.S. News series that examines multiple viewpoints on key issues. The new versions include changes to headlines and some minor text updates.

Once again, coronavirus cases are climbing nationwide. Primarily among the unvaccinated. Some 90 million eligible Americans still haven't gotten their first dose. Fueled by the highly contagious delta variant coupled with factors like vaccine hesitancy, fresh viral surges are causing renewed concern.

Vaccine mandates are sparking fierce controversy around the world. Recently President Biden announced new vaccine requirements for federal civilian workers, comprising more than 2 million Americans. Because his plan relies on the honor system – not proof of vaccination – some experts fear these steps will not be enough to curb the spread. This week, New York City went further, becoming the first major city in the country to require proof of vaccination to enter many indoor public spaces, like gyms and restaurants.

Michael Ciaglo | Getty Images

A health worker holds a dose of the Johnson & Johnson COVID-19 vaccine in Aurora, Colorado.

In this edition of The Forum, a U.S. News series examining opinions about key issues, two prominent public health doctors explore the question of whether all Americans should now be required to get the COVID-19 vaccine.

America 2024

Dr. Marty Makary: I’m pro-vaccine but blanket requirements outside of health care go too far.

COVID-19 vaccine mandates have become a hotly contested issue, as coronavirus cases and hospitalizations rebound nationwide, driven by the highly contagious delta variant and unswerving vaccine hesitancy. New York City will soon be the first major U.S. city to require proof of vaccination to enter restaurants, gyms and other indoor public spaces. Dr. Marty Makary, a professor at Johns Hopkins University School of Medicine and editor in chief of MedPage Today, argues that mandating vaccines for "every living, walking American" is, as of now, not well-supported by science. Moreover Makary, author of "The Price We Pay: What Broke American Health Care—and How to Fix It," has concerns about the two-dose vaccine regimen for young people.

As told to Lindsay Lyon as part of The Forum, a U.S. News series examining opinions about key issues. Responses have been edited for length and clarity.

U.S. News: Should all Americans be required to get the COVID-19 vaccine?

Dr. Marty Makary: No. As a physician with a lot of experience dealing with patients who don't follow what we ask them to do, I believe you win more bees with honey than fire.

The vaccines are so good at protecting against death from COVID-19 that those who are immune can feel good about living life without having to worry about becoming severely ill. Vaccines downgrade the infection to a mild seasonal virus – one we must learn to live with for years to come.

Scott Eisen | Getty Images

Anti-vaccine activists protest in front of the Massachusetts State House in Boston, Massachusetts.

Those who choose not to get vaccinated are making a poor health decision at their own individual risk. They pose no public health threat to those already immune. Would we be so stern toward people making similar or worse health choices to smoke, drink alcohol or not wear a helmet when riding a bike? Over 85,000 Americans die annually from alcohol, yet we don't have the same public health fervor or requirements to save those lives. Let's encourage vaccination rather than activate the personal liberty culture wars that result in people becoming more entrenched in their opposition.

The notion that we have to vaccinate every living, walking American – and eventually every newborn – in order to control the pandemic is based on the false assumption that the risk of dying from COVID-19 is equally distributed in the population. It's not. We have always known that it's very hard for the virus to hurt someone who is young and healthy. And that's still the case. While vaccine requirements for health care workers make sense, we would never extend those requirements outside of health care for, say, the flu shot. We'd simply state to the public: Those who avoid the flu shot do so at their own risk.

Also: Some people already have ' natural immunity ' – that is, immunity from prior COVID infection. During every month of this pandemic, I've had debates with other public researchers about the effectiveness and durability of natural immunity. I've been told that natural immunity could fall off a cliff, rendering people susceptible to infection. But here we are now, over a year and a half into the clinical experience of observing patients who were infected, and natural immunity is effective and going strong. And that's because with natural immunity, the body develops antibodies to the entire surface of the virus, not just a spike protein constructed from a vaccine. The power of natural immunity was recently affirmed in an Israeli study , which found a 6.7 times greater level of protection among those with natural immunity vs. those with vaccinated immunity.

Requiring the vaccine in people who are already immune with natural immunity has no scientific support. While vaccinating those people may be beneficial – and it's a reasonable hypothesis that vaccination may bolster the longevity of their immunity – to argue dogmatically that they must get vaccinated has zero clinical outcome data to back it. As a matter of fact, we have data to the contrary: A Cleveland Clinic study found that vaccinating people with natural immunity did not add to their level of protection.

So instead of talking about the vaccinated and the unvaccinated, we should be talking about the immune and the non-immune. Immunity is something people can test for with a simple antibody test. I would never recommend that anyone intentionally acquire the infection in order to get natural immunity, but vaccine passports and proof-of-vaccine documents should recognize it.

Now, if someone does not have natural immunity from prior infection, then they should immediately go out and get the vaccine. I'm pro-vaccine. But the issue of the appropriate clinical indication of the vaccine is not an all-or-nothing phenomenon, as we frequently see in American culture and politics.

I'm perplexed at the vitriol directed at folks who are reluctant to get vaccinated. For some, the biggest driver of their hesitancy is the U.S. Food and Drug Administration, which has failed to issue the long-overdue full approval of the COVID-19 vaccines due to stability testing which has nothing to do with safety.

The goal of our pandemic response should be to reduce death, illness and disability, but instead what you're seeing is a movement that has morphed from being pro-vaccine to vaccine fanaticism at all costs.

We have very strong population immunity in most parts of the U.S. – and these areas are resilient to the delta variant that's driving severe illness right now. This stems from a combination of natural immunity and vaccinated immunity. Roughly a third to half of Americans who are unvaccinated have natural immunity, based on an analysis of California residents. So it does change the outlook.

For example: One study conducted by the state of California this spring found that 38% of Californians and 45% of Los Angeles residents had natural immunity. And this was at a time when vaccine rollout was still too early to account for those numbers. So we're potentially talking about a large portion of the U.S. population who may be immune to COVID and not know it. They should be tested to find out, and we should concentrate our vaccination efforts on people who are not immune.

Right now, we do have a group of susceptible, non-immune Americans among whom the delta variant is raging. That's where we need to focus our attention. We have to work on making the vaccine more available – and easily available – to the non-immune in the U.S. That means going to them: Having walk-up vaccination appointments at routine points of American life.

When it comes to vaccinating healthy kids – and you could argue young people up to 25 – there is a case for vaccination but it's not strong. The COVID-19 death risk is clustered among kids with a comorbid condition, like obesity. Of the more than 330 COVID-19 deaths in kids under age 25, there's good preliminary data suggesting that most or nearly all appear to be in kids with a pre-existing condition. For kids with concurrent medical conditions, the case for vaccination is compelling. But for healthy kids?

The risk of hospitalization from COVID-19 in kids ages 5 to17 is 0.3 per million for the week ending July 24, 2021, according to the Centers for Disease Control and Prevention. We also know that the risk of hospitalization after the second vaccine dose due to myocarditis , or inflammation of the heart muscle, is about 50 per million in that same age group.

It may be that the standard two-dose regimen is a dose too high and is inducing a strong inflammatory response causing these complications. A single dose of the vaccine may be highly effective in kids, as reported by Tel Aviv University . Researchers there found that one dose was 100% effective in kids ages 12 to 15. For now, until we get better data, I recommend one dose for healthy kids who have not already had COVID-19 in the past.

I'm concerned the CDC hasn't considered whether one dose of the two-dose shots would be sufficient – and safer – for young people. The agency's Advisory Committee on Immunization Practices has vigorously recommended the two-dose vaccine regimen for all children ages 12 and up regardless of whether kids already have immunity. I take issue with that. The data the CDC used on which to base its recommendation is incomplete at best. The agency is using the Yelp of vaccine complications as a data source: a self-reported database of vaccine complications, which haven't been fact-checked by authorities. So the agency may not be fully capturing the extent of vaccine complications from the second dose in some young people.

I wish the CDC would tell us more about the deaths of Simone Scott , 19, and Jacob Clynick , 13, both of whom died shortly after getting a second vaccine dose and developed heart inflammation. There have been 19 other deaths in youth under age 25, according to the CDC. Since the clinical trials were not powered sufficiently to detect rare events like these, I want to know more about those deaths before making blanket recommendations.

Researching these events is important when issuing broad guidance about vaccinating healthy kids, including students, who already have an infinitesimally small risk of dying from COVID-19.

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• Published: 17 July 2023

Psychological profiles of anti-vaccination argument endorsement

• Dawn L. Holford   ORCID: orcid.org/0000-0002-6392-3991 1 ,
• Angelo Fasce 2 ,
• Thomas H. Costello 3 &
• Stephan Lewandowsky   ORCID: orcid.org/0000-0003-1655-2013 1  

Scientific Reports volume  13 , Article number:  11219 ( 2023 ) Cite this article

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The proliferation of anti-vaccination arguments online can threaten immunisation programmes, including those targeting COVID-19. To effectively refute misinformed views about vaccination, communicators need to go beyond providing correct information and debunking of misconceptions, and must consider the underlying motivations of people who hold contrarian views. Drawing on a taxonomy of anti-vaccination arguments that identified 11 “attitude roots”—i.e., psychological attributes—that motivate an individual’s vaccine-hesitant attitude, we assessed whether these attitude roots were identifiable in argument endorsements and responses to psychological construct measures corresponding to the presumed attitude roots. In two UK samples (total n = 1250), we found that participants exhibited monological belief patterns in their highly correlated endorsements of anti-vaccination arguments drawn from different attitude roots, and that psychological constructs representing the attitude roots significantly predicted argument endorsement strength and vaccine hesitancy. We identified four different latent anti-vaccination profiles amongst our participants’ responses. We conclude that endorsement of anti-vaccination arguments meaningfully dovetails with attitude roots clustering around anti-scientific beliefs and partisan ideologies, but that the balance between those attitudes differs considerably between people. Communicators must be aware of those individual differences.

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Introduction.

Vaccinations are one of the most successful medical inventions for controlling and preventing deaths from infectious diseases 1 . Curiously, however, opposition to vaccines remains prevalent and therefore poses a substantial threat to global health 2 . In particular, the proliferation of anti-vaccination arguments on the Internet has curtailed the benefits of many immunisation programmes 3 , 4 —with COVID-19 vaccinations offering an especially salient recent example 5 . These arguments influence individuals’ decisions to have vaccinations. Indeed, mere exposure to online vaccine misinformation may lower vaccination intentions 6 and belief in misinformation is cross-culturally associated with lower readiness to be vaccinated against COVID-19 7 . The perpetuation of misconceptions and logical fallacies by vaccine opponents have also influenced the intentions of parents to vaccinate their children 8 , 9 .

Vaccine-hesitant individuals express arguments that can range expansively from exaggerated safety concerns, to the use of fallacious logic, to reliance on misinformation, to conspiratorial beliefs, to give some examples 10 . This can make it difficult for vaccine communicators—such as fact-checkers, healthcare professionals, and scientists—to counter the many different arguments that spread rapidly on the Internet 11 . Compounding the problem, facts and evidence to debunk flawed contrarian argumentation may not be sufficient. Opposition to vaccines that stems from social and cultural factors, rather than a failure to understand the science of vaccination, will not necessarily be satisfactorily countered with scientific evidence 12 . Certain anti-vaccination arguments also target cognitive systems that are used in intuitive judgements and motivated reasoning, which can make it harder to combat those arguments with statistics, facts, and logic 13 . Further, people may be motivated to reject scientific evidence if it is in conflict with their personal interests, worldviews, or beliefs 14 , 15 . In those cases, people may engage in motivated reasoning such that they interpret scientific findings in a manner that is compliant with their existing beliefs 16 . For example 17 , found that people evaluated information compatible with their existing attitudes about flu vaccination to be more convincing than attitude-inconsistent information.

Effective rebuttal of anti-vaccination arguments therefore requires an approach that goes beyond addressing flaws in the arguments, by also considering the underlying psychological attributes, known as “attitude roots” 18 , 19 , that drive opposition to vaccines. This means looking beyond the content of arguments to assess what motivates someone to endorse an anti-vaccination argument. Such motivations could be based on very different psychological constructs, including “fears, ideologies, worldviews, and identity needs” 18 . For instance, individuals high in conspiratorial ideation (a psychological tendency) may tend to argue that one should reject vaccinations because they are part of a secret plot to control the population by implantation of microchips embedded in the vaccines, whereas individuals who are politically libertarian (a worldview) may argue that one should reject vaccinations because they are a political tool that removes people’s freedoms (e.g., through mandates). Ultimately, the attitude roots identifiable in the expression of an argument should serve as a veneer for stable individual differences (e.g., personality, values, worldviews, or emotions) that are also related to vaccine hesitancy.

Understanding the attitude root of an individual’s resistance to vaccines may thus allow vaccine communicators to align their message with the individual’s motivation for holding their position, and avoid triggering their motivation to reject the pro-vaccination message 18 , 20 . However, identifying an attitude root is no easy task. As the terminology suggests, attitude roots lie beneath a surface expression and are not always obvious to the interlocutor. Individuals may themselves lack insight into their own motivations for endorsing a particular anti-vaccination argument 18 . Further complicating matters, even the manifestations of attitude roots can overlap. As seen in the example above, a secret plot to control the population will also remove people’s freedoms. Therefore, to better understand how to address the attitude roots of vaccine opposition, there is a need for research to investigate the manifestations of anti-vaccination sentiment (i.e., arguments) and link those manifestations to underlying psychological factors. Earlier work showed that across 24 different countries, three psychological factors (conspiratorial beliefs, disgust about blood and injections, and reactance) were associated with negative attitudes about the safety and effectiveness of children’s vaccinations, suggesting that these could be potential attitude roots to investigate as motivations to reject vaccination science 20 . More recent work 21 sought to classify a wider range of anti-vaccination arguments and map them to potential attitude roots. In this work, the authors identified 2414 anti-vaccination arguments through a PRISMA-compliant systematic review of 152 scientific publications, and classified them into a hierarchical taxonomy with 11 overarching attitude roots. This classification, initially done by qualitative thematic analysis, was validated using machine learning to classify arguments based on their linguistic expression. Trained researchers classified the attitude roots in two different datasets—the arguments obtained from the systematic literature review, and an additional dataset of 582 anti-vaccination arguments obtained from a database of fact-checked COVID-19 vaccine claims circulating on the Internet. A Natural Language Processing model trained on a subset of the data was able to predict the attitude root classifications with a high level of accuracy.

This taxonomy 21 integrated decades of prior research on the typologies of anti-vaccination arguments (e.g., 10 , 22 ). It conceptualised anti-vaccination arguments, which form the base level of the taxonomy, as an expressed proposition that opposes vaccination—i.e., the given reason for not having a vaccine. The 11 attitude roots that form its top level (see Table  1 ) reflect psychological characteristics that have been found in past research to be related to vaccine hesitancy (e.g., conspiracist beliefs 23 , 24 ).

Fasce et al.’s 21 taxonomy provided the most comprehensive framework to date of a wide range of arguments and their links to the underlying attitude roots of anti-vaccination belief—i.e., their psychological motivators. We used the taxonomy as a springboard for the present investigation of the psychological factors that motivate people’s anti-vaccination attitudes. We investigated these attitude roots in two ways. First, we sought to assess whether it would be possible to observe clusters of argument endorsement that reflect correlated levels of endorsements for anti-vaccination arguments within the same attitude root. Of course, the boundary between attitude roots may be blurred, with overlaps between those that share similarities (such as religious and moral concerns 21 ). An individual could also hold more than one attitude root, thus strengthening their motivation to endorse anti-vaccination arguments 19 . Indeed, there is evidence from research into conspiracist beliefs that individuals may form monological belief systems, where belief in one conspiracy theory supports belief in others 25 , 26 .

Our second goal was to determine if argument endorsements were associated with specific psychological characteristics that were identified as individual difference measures for the attitude roots. Here, we expected that if attitude roots were discernible among argument endorsements, those clusters of argument endorsements would relate to a specific psychological determinant of vaccine hesitancy. That is, a set of different arguments that invoke conspiracies should be preferentially endorsed by people who tend to view the world through a conspiratorial lens, whereas arguments that emerge from a libertarian lens should be preferentially endorsed by free-market advocates, and so on. However, as many of these psychological constructs may themselves be intercorrelated 15 , 24 , 27 , 28 , this could hinder the ability to discern specific associations of one psychological construct with its expected argument endorsements. Nonetheless, each psychological construct should at minimum be associated with argument endorsement strength.

Factor structure of argument endorsements

We first analysed the internal structure of participants’ endorsement of the anti-vaccination arguments (66 in Sample 1, 33 in Sample 2). We started exploring both datasets through Exploratory Factor Analysis (EFA) with maximum likelihood estimation and promax rotation. In the first sample, parallel analysis suggested to retain 3 factors. However, the 3-factor solution displayed numerous cross-loadings and the factors were not interpretable from a theoretical point of view, which suggested that the 1-factor solution, which displayed acceptable item loadings in all cases ( \(> 0.34\) ), would be preferable. In the second sample, a parallel analysis suggested a 2-factor solution, with religious concerns grouped into a separate factor. As in Sample 1, a 1-factor EFA solution was viable, with all loadings \(> 0.36\) .

We then used pre-registered Confirmatory Factor Analyses (CFA) to evaluate 3 models compatible with the taxonomy of anti-vaccination arguments 21 : a 1-factor model, an 11-factor model in which all the attitude roots were represented as different latent variables, and a 7-factor model in which 4 pairs of thematically related attitude roots were collapsed into combined factors: (1) conspiracist ideation and distrust, (2) religious and moral concerns, (3) fear and phobias and distorted risk perception, and (4) perceived self-interest and reactance. Parameters were estimated by maximum likelihood method, which allows the calculation of the commonly used criteria for acceptable goodness-of-fit: Comparative Fit Index (CFI) and Tucker-Lewis Index (TLI) close to 0.90 or above, Root Mean Square Error of Approximation (RMSEA) close to 0.08 or below, and Standardised Root Mean Square Residual (SRMR) close to 0.05 or below 29 . The 7-factor and 11-factor models were not acceptable due to poor fit indices in both samples and because they implied mathematically impossible variance-covariance matrices. We theorise that this is attributable to extremely high correlations among items that were designed to measure distinct roots. We also explored statistical approaches that are more tolerant under conditions of substantial intercorrelation between latent variables, such as confirmatory bi-factor models or exploratory structural equation modeling, and those were also found to be unsatisfactory. The 1-factor model was unproblematic in both samples. The results are displayed in Table  2 . Sample 1 uses all 66 items, whereas Sample 2 uses the substantially narrowed item pool described above. Our results confirm the notion that people who are opposing vaccinations will tend to endorse any and all anti-vaccination arguments within the taxonomy.

Associations of anti-vaccination argument endorsement

Following our pre-registered hypotheses, we next examined the relationship between argument endorsements and the assays of the attitude roots. As shown in Table  3 , 11 out of 13 of the measured psychological constructs in Sample 2 were significantly correlated in the expected direction with argument endorsements drawn from the target attitude root. The constructs were also associated with total endorsements of all the arguments, is in line with the unidimensional structured revealed by the factor analyses. These correlations remained significant, with similar effect sizes, when controlling for age, gender, education, and political orientation (see Supplementary Information, Table  S4 ). We interpret these results as partial support for our hypotheses. Although we found 11 of the 13 hypothesised correlations, these associations are not exclusive to the target attitude, but rather extend to the rest of attitude roots, which, again, suggests a monological belief system among those who endorse anti-vaccinations arguments.

Two exceptions, Trait Fear and Prosocial Behavioural Intentions, did not correlate significantly with argument endorsements from the target attitude root—and Prosocial Behavioural Intentions did not correlate at all with overall argument endorsements. However, these constructs were also not significantly associated with their related dimensions of the 5C scale—confidence ( r = − 0.02) and collective responsibility ( r = − 0.03), respectively. By contrast, all other psychological constructs were significantly correlated to the 5C measures, indicating that these were predictive of the vaccine hesitancy determinants. We are inclined to attribute this lack of association for the two exceptions to the scales used to measure Trait Fear and Prosocial Behavioural Intentions, which may be too general and, consequently, do not reflect the specific psychological processes related to healthcare or vaccination.

In addition, average argument endorsement correlated positively with the 5C subscales Constraints, Complacency, Calculation, Collective, as well as negatively with the Confidence subscale 30 , as shown at the bottom of Table  3 . Greater endorsement of the arguments therefore indicated greater vaccine hesitancy. We also found in exploratory hierarchical linear regressions (available in Supplementary Information, Table  S5 ) that argument endorsements had incremental validity in predicting the psychological constructs, over and above the 5C items.

We also observed that the psychological constructs were significantly correlated with each other, albeit to a lesser extent than the argument endorsements (correlation coefficients among the psychological constructs can be found in Supplementary Information, Table  S6 ). This prompted us to further examine how the psychological constructs might overlap among individuals through an exploratory analysis of psychological profiles at the participant level.

We next used Latent Profile Analysis (LPA) to identify different profiles of participants in Sample 2 ( n = 590) based on their responses to the psychological constructs. LPA is a variant of latent class analysis that allows the use of continuous variables. LPA is a person-centered analytic tool that offers a classification of each participant in the most probable profile based on a set of observable variables, rather than classifying the variables 31 . A range of indices determine the most appropriate number of latent profiles: Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), sample-size adjusted BIC (SABIC), and a measure of entropy. Lower values for AIC, BIC, and SABIC indicate greater fit. For entropy, values above 0.80 denote reliable separation of profiles.

We included in the LPA the 11 psychological constructs that were associated with argument endorsements at p < 0.001 (see Table  3 ). To distinguish between pro-vaccination and anti-vaccination profiles, we included the average of participants’ endorsements for all arguments to classify their overall vaccination attitude. We additionally included Political Orientation as it was positively associated with argument endorsement ( r = 0.16, \(\textit{p} < 0.001\) ). Table  4 shows the fit indices of models with 1–10 profiles. We selected the 8-profile model, which exhibited the lowest BIC and a high entropy. We used the scores of each profile in endorsement of anti-vaccination arguments to define their respective attitude toward vaccinations (i.e., if they were below or above the mean). Four profiles were characterised as pro-vaccination and four as anti-vaccination (see Fig.  1 ).

Two of the identified profiles (“unspecified” pro- and anti-vaccination) did not show any distinctive association and exhibited moderate levels of pro- and anti-vaccination attitudes. The remaining six profiles had distinctive and consistent patterns. Among the anti-vaccination profiles, we found an “alternative epistemology” profile characterised by a combination of anti-scientific beliefs and epistemology, with this group being particularly prone to endorsing anti-vaccination arguments. A second “social conservatism” profile was characterised by high religiosity, moral rigidity, and traditionalism. The last, “free-market ideology”, anti-vaccination profile was predominantly characterised by its strong endorsement of this ideology. In contrast, among the pro-vaccination profiles we found a “critical thinking and leftism” profile characterised by its opposition to anti-scientific beliefs, alternative epistemology, and conservatism, and this profile appeared especially resistant to anti-vaccine arguments. The second “conservatism” profile was characterised by moderate conservative ideology and lower General Reactance and Alternative Epistemology than their anti-vaccination counterparts—which suggests an ideological profile less susceptible to politically motivated reasoning. The final pro-vaccination profile was characterised by its religiosity—which is in line with the context-dependent relationship between religiosity and vaccine hesitancy 32 .

Anti- and pro-vaccination profiles identified in a latent profile analysis using 13 psychological constructs associated with endorsement of anti-vaccination arguments.

We investigated the psychological factors, or “attitude roots”, motivating contrarian views regarding vaccines and the endorsement of these arguments. We selected attitude roots based on a taxonomy of anti-vaccination arguments 21 , and operationalised them in two ways. First, we selected a group of prototypical anti-vaccination arguments to represent themes from each attitude root in the original taxonomy. Second, we selected psychological construct measures that were conceptually aligned with the attitude roots. The analyses of these two different attitude root representations give rise to a complex overall picture of how people may sustain anti-vaccination attitudes. Individuals who scored higher on the psychological antecedents of vaccine hesitancy and the psychological construct representations of the attitude roots endorsed all arguments against vaccines more strongly. These individuals further clustered into four identifiable “profiles” based on the psychological constructs.

In two UK samples totalling 1250 responses, we found that endorsements of arguments selected to represented distinct attitude roots were so correlated that it constrained our ability to fit the proposed 11-factor structure model. We were thus unable to confirm any preferential endorsement patterns among arguments representing different attitude roots. This finding may seem at odds with previous work that was able to classify documented arguments that people had put forth against vaccination, where a computational model trained on scholarly analysis of the arguments could successfully predict the attitude roots of new arguments from a different domain 21 . However, it is important to distinguish endorsement of arguments that one may encounter from the expression of arguments that one may produce. When presented with an arguments against vaccines, an individual who is strongly negative about vaccination may strongly endorse any argument simply because it is consistent with their attitude. This tendency to endorse arguments that support one’s existing perspective has been documented in a family of cognitive biases, such as “belief bias” and “myside bias”, where people evaluate evidence and accept conclusions in a manner that is biased towards their prior opinions and attitudes 33 . Reasoning research in particular has shown that attitude-consistent conclusions are believed more than attitude-inconsistent ones, especially when these conclusions relate to ideological and political issues (e.g., 34 , 35 , 36 ). For example, participants’ prior attitudes towards abortion impeded their ability to discern flawed reasoning when the conclusions supported their abortion position 36 . People also tend to endorse otherwise identical information more if it supports one’s political beliefs rather than challenges them 37 . In extreme circumstances, endorsing one argument can even act as support for the endorsement of others towards the same conclusion, forming a monological belief system that is commonly seen within conspiracist ideation 26 . Indeed, beliefs in distinct conspiracy theories correlate highly with one another, even when those theories are contradictory or fictitious 25 , 38 , 39 , 40 . The motivations for one’s anti-vaccination attitude may thus be captured by one (or several) arguments that one might personally express, but endorsing other attitude-consistent arguments can serve to support, and perhaps strengthen, one’s overall position.

The motivations for endorsing anti-vaccination arguments may instead need to be captured by other measures. We included psychological construct measures in Sample 2 to assess the associations of these assays of the attitude root to argument endorsements. With the exception of trait fear and prosociality (which also did not predict the relevant 5C vaccine hesitancy determinant), each psychological construct was not only associated with argument endorsements from the target attitude root, but also argument endorsements from other attitude roots. In other words, there was an overall tendency for those with high levels of those psychological factors to give stronger endorsements of anti-vaccination arguments in general. The effect sizes of the significant correlations varied from r = 0.14–0.68, so some of these correlations were only weak ones. However, these correlational effect sizes, and their directions, generally match with those found in previous research regarding the relationship of the psychological constructs to other vaccine hesitancy measures 19 , 20 , 23 , 41 , 42 , 43 , 44 , 45 . It is important to clarify that our study related the psychological assays for the attitude root to both argument endorsement strength and vaccine hesitancy determinants (measured by the 5C scale 30 ), as vaccine hesitancy has historically been ambiguously defined, with researchers conceptualising the term in varying ways, from cognition and affect to decisions and behaviour 46 . Our findings thus link this comprehensive set of psychological constructs to their role in motivating cognition about vaccines, which themselves predict previously-validated behavioural determinants of vaccine hesitancy. Where a psychological construct predicted vaccine hesitancy in the literature, it also predicted argument endorsement to a similar extent. In both cases, some of these correlations were weak, which may reflect a difficulty in selecting the right measures to capture the latent psychological variables. More likely, it indicates that people can possess various overlapping motivations, each of which contribute in part to their attitudes and endorsements.

It was difficult to determine unique contributions of attitude roots to anti-vaccination argument endorsement strength. We had expected some level of clustering, where certain attitude roots should be more strongly associated than others, which was captured by the 7-root model that collapsed these attitude roots. For example, conspiracist ideation, which is characterised by a high level of distrust in the “official” narrative 47 ), should be strongly associated with distrust, even if it is distinct in that not all distrust in vaccination involves a belief in a conspiracy theory. We observed not just these expected clusters, but also a more complex pattern of inter-correlations among all the psychological constructs. To some extent, this is supported by past research—for example, conspiracist mentality is correlated with right-wing social conservatism 27 , free-market ideology 15 , distrust of official information sources 24 , and paranormal and pseudoscientific beliefs 28 . However, our study is the first to systematically investigate this many potential attitude roots and assess their overlap.

Making the case for potential overlap among attitude roots 18 , proposed that multiple roots could sustain an individuals’ attitudes and “in combination they could be more powerful than if one were to operate individually.” Our latent profile analysis provided some evidence for this proposal, as we were able to identify four distinct clusters of participants in Sample 2 who tended to endorse anti-vaccination arguments. These profiles were primarily characterised by various elements of anti-science beliefs and ideological partisanship. We consider below how the psychological clusters we found could be targeted for vaccine communication interventions, which future research may wish to build on.

One profile that displayed average scores across all constructs and less strong argument endorsements suggested that this might be an “on-the-fence” group who could be more amenable to informational interventions such as prebunking and debunking 48 . Because no one psychological construct distinguishes this group, it may be worth considering broader spectrum interventions that do not target specific misinformation content but warn against strategies marking out misinformation 49 . Techniques such as Motivational Interviewing may also be useful, as it encourages healthcare professionals engaging with patients who are uncertain about a certain behaviour (including vaccination) to explore their motivations for it and guide patients towards acceptance 50 .

Conversely, the psychological profile with the strongest total endorsement of anti-vaccination arguments and perception of vaccination risks encompassed individuals who may seek to justify their hesitancy through a combination of anti-scientific doctrines (i.e., conspiracy and pseudoscientific theories) and an alternative epistemology that undermines normative epistemological principles such as the primacy of scientific evidence. These attitude roots may also reinforce one another inasmuch as a relativistic epistemology facilitates the adoption and promotion of anti-scientific conceptions 51 . This group would be highly likely to resist correction that are based on a shared acceptance of facts and evidence. Communication with this group would gain most from first establishing a common ground for further discussion before attempting to correct any misconceptions. Consider, for instance, an individual who holds strong beliefs about the effectiveness of alternative medicinal products. Rather than arguing that there is insufficient evidence for alternative medicine and overwhelming evidence for vaccination, it may be more productive to acknowledge that one can reap benefits from different types of therapies—but these are in addition to rather than instead of vaccination.

The final profiles were characterised by high levels of social conservatism, with the smaller of these profiles distinguished by an additional stronger belief in free-market ideology—reflecting a divergence in conservative ideology on social and economic issues 52 , 53 . A vaccine communication strategy for these groups could focus on how vaccination is not at odds with their belief systems. For example, information and corrections will likely be trusted more and seen as compatible with beliefs if they come from authoritative sources within one’s religion, tradition, or community group 54 . Identifying benefits that align with existing worldviews may also be important, for example, positioning vaccination as an individual choice to gain its protective benefits for oneself (as opposed to benefiting society) would be in line with a neoliberal ideology that prizes individualism and deregulation 55 .

Our research also has a few limitations that future research may also wish to address. As a correlational study, although it is reasonable to posit that psychological factors drive anti-vaccination belief, our study design does not allow us to draw such a causal conclusions from the observed significant associations. We also focused on soliciting endorsements of arguments from different roots rather than having participants express reasons for rejecting vaccinations. While this method was necessary to allow us to determine the factor structure of the endorsements and their correlations with the psychological constructs, it could be good for future research to investigate if the psychological constructs are related to the types of arguments people might choose to express against vaccination.

We are also cautious about the generalisability of the psychological profiles in our UK sample, and recommend that future research address whether these profiles are present in other countries and cultures. The associations between some of the psychological constructs and vaccine hesitancy may differ, for example, reactance was previously found to predict anti-vaccination attitudes in the UK ( r = 0.33) but not in Japan ( r = 0.09) 20 . Specifically, associations around worldview and politics will likely be sensitive to different cultural contexts, as the relationship between social and economic conservatism is characteristic of developed countries 56 , 57 .

In sum, our work contributes data covering a comprehensive set of psychological factors associated with vaccine hesitancy, and, specifically, its cognitive manifestation as endorsements of anti-vaccination arguments. We found that these endorsements exhibit a monological response pattern, with high inter-correlations, but the psychological factors that predicted argument endorsement strength clustered into distinct psychological profiles. These indicate that two key motivators of anti-vaccination belief relate to anti-scientific conceptions and political polarisation, which may require different communication strategies to tackle.

Before data collection, the study was approved by the University of Bristol School of Psychological Science Research Ethics Committee (references: 10309 and 10708) and the study methods and planned analyses were pre-registered. The pre-registration, study materials, data, and analysis scripts to derive our reported results are shared on the Open Science Framework: https://osf.io/27f5u/ . All study methods were performed in accordance with the relevant guidelines and regulations approved by the Research Ethics Committee. Informed consent was obtained from all participants prior to their participation in the study.

Participants

We recruited 1250 participants (Sample 1: n = 660; Sample 2: n = 590) from the UK via Prolific, who were paid at a rate of \(\pounds\) 9/h. We determined sample sizes based on a recommended ratio for performing factor analyses of at least 10 participants per measured anti-vaccination argument 58 . For Sample 1, we pre-selected participants who had stated they either felt negatively or neutral towards the COVID-19 vaccine in a Prolific screening question. This was to ensure we would have enough participants who would endorse the anti-vaccination arguments to enable a factor analysis. For Sample 2, we did not apply this pre-selection filter because we aimed to assess a wider range of attitudes and psychological characteristics that would enable the correlational analyses and allow us to build profiles of individuals with pro- and anti-vaccination views. This also meant that Sample 2 should be less prone to monological thinking than Sample 1. In both cases, we obtained a balanced distribution of gender and political leanings.

At the end of each data gathering process, participants provided demographic information. Participants in Sample 1 were 50% male, 49% female (1% did not identify with either gender), with ages ranging between 18-84 years ( M = 38.36, SD = 12.13). Participants in Sample 2 were 49% male, 51% female, with ages ranging between 18–85 years ( M = 43.10, SD = 14.12). In both samples, 48% had at least a Bachelor’s degree, and there was a normal distribution across political leanings on an 11-point scale representing the left-right political spectrum 27 , 59 (Sample 1: M = 5.74, SD = 2.33, skewness = 0.06, kurtosis = − 0.37; Sample 2: M = 5.83, SD = 2.40, skewness < 0.01, kurtosis = − 0.62).

Anti-vaccination arguments

We assessed participants’ endorsements of anti-vaccination arguments using a methodology similar to that used in research investigating conspiracist beliefs (e.g., 60 . Participants endorsed arguments by indicating how much they agreed with each argument on a 7-point Likert scale (1: strongly disagree, 7: strongly agree). All arguments and their mean endorsement ratings in our two samples are available in Supplementary Information (Table  S2 ).

In the first sample, participants rated their endorsement of 66 prototype anti-vaccination arguments that were spread evenly across the 11 attitude roots. All but four of the arguments were prototypical arguments identified in Fasce et al.’s 21 taxonomy. The remaining four were created for the purposes of this study to ensure no root had disproportionately fewer arguments for analysis than the others. The levels of skewness and kurtosis of most of the arguments assessed in Sample 1 were within the usual thresholds for a normal distribution (+ 2/− 2). Only three arguments (the second and fourth of religious concerns, and the second of reactance) exhibited a kurtosis slightly above the threshold (2.71, 2.12, and 2.47, respectively). These 66 arguments showed high internal consistency ( \(\alpha\) of the six arguments within each attitude root ranged from 0.67 to 0.91; total \(\alpha\) = 0.98).

We used a 11 exploratory bi-factor latent variable models (i.e., with the Schmid-Leiman transformation 61 ) of each set of argument endorsements in Sample 1 to identify arguments most diagnostic for their attitude root to use in Sample 2. Specifically, we selected the three arguments for each attitude root that were most saturated with the general factor. Explained Common Variance of the general factors ranged from .43 (moral concerns) to .86 (epistemic relativism), with a median of .74, suggesting that most target roots were relatively unidimensional. The three items with general factor loadings > .60 for each target root were retained for Sample 2, resulting in 33 anti-vaccination arguments (the list of selected arguments and their respective mean endorsements can be found in the Supplementary Information, Table S2 ). This shortened the overall questionnaire while maintaining a minimum of three items per attitude root required for a confirmatory factor analysis on these data. Participants in Sample 2 rated their endorsement of these 33 arguments. The parameters of skewness and kurtosis of almost all the 33 anti-vaccination arguments included in the second sample were within the thresholds of normality, except for the second and fourth arguments of religious concerns, which showed higher levels of kurtosis (3.55 and 2.17, respectively). The total \(\alpha\) of the 33 anti-vaccination arguments was 0.98, with the internal consistency of the attitude roots ranging from 0.75 to 0.91. We found very similar patterns of argument endorsement between the two samples, indicating that the three items per root chosen for the second sample remained representative of that root.

Psychological constructs

In Sample 2, we also collected data on participants’ responses to 13 previously validated measures of psychological constructs that were selected as independent assays of the 11 attitude roots. Participants also responded to the short version 5C scale 30 , which composes five items for each of its dimensions, to be used independently: Confidence, Constraints, Complacency, Calculation, and Collective (responsibility). This gave us a general measure of the psychological antecedents of vaccination behaviour and, consequently, vaccine hesitancy, which provided further validation that the argument endorsements were associated with vaccine hesitancy (see Table  3 ). We summarise the psychological construct measures here, with relevant statistics in the Supplementary Information (Table  S3 ).

Conspiracy Mentality . Conspiracy Mentality Questionnaire 62 , five items measuring generic conspiracy beliefs.

General distrust . (Dis)trust Scale 63 ’s, eight items measuring general trust towards other people (reverse coded for distrust).

Pseudoscientific beliefs . Short-form Pseudoscientific Belief Scale 28 , eight items measuring general unwarranted beliefs falsely presented as scientific.

Free market ideology . Free-market Endorsement Scale 15 , five items measuring economic conservatism through the promotion of laissez-faire capitalism and private enterprise.

Traditionalism . Four items from the conventionalism factor of the Aggression-Submission-Conventionalism Scale 64 that express traditionalism (as opposed to respect for social norms).

Populism . Three items with the highest factor loading on the Populist Attitudes Scale 65 , defined as a political attitude with three core features: sovereignty of “the people”, opposition to the elite, and the Manichean division between “good” people and “evil” elites.

Centrality of religion . Centrality of Religion Scale 66 , five items measuring salience of religious meanings in personality.

Moral absolutism . Moral Absolutism Scale 67 , six items measuring desire for certainty in the moral domain. An additional measure of moral exporting was discarded due to poor internal consistency.

Trait fear . Six items with factor loadings> 0.70 from the Trait Fear Scale 68 , measuring self-reported variations in fear and fearlessness.

Perceived vaccination risk . Following 30 , we asked participants to rate the risk of four diseases (Covid-19, influenza, measles, and HPV) and the risk of their respective vaccines. To calculate the likelihood and magnitude of perceived risk of vaccination in comparison to that of vaccine-preventable diseases, we subtracted the risk of vaccines scores from the risk of disease scores.

Prosocial behavioral intentions . Prosocial Behavioral Intentions Scale 69 , four items measuring participants’ general prosociality in common situations.

Alternative epistemology . Epistemic Beliefs Scale 51 , 12 items with 3 sub-factors measuring epistemic beliefs. The first factor measures reliance on intuition for factual beliefs, the second reflects conviction that facts are politically constructed, and the third measures importance of consistency between empirical evidence and beliefs. The third factor was reversed to denote rejection of evidence and, subsequently, calculate a total score in alternative epistemology.

General reactance . A condensed version of the Hong Psychological Reactance Scale 70 used in 20 , with five items measuring motivation to reject consensus views as part of a nonconformist identity.

To assess the convergent and discriminant validity of the argument endorsements in relation to their associated psychological constructs, we pre-registered the following predictions based on previous findings on anti-vaccination arguments and vaccine hesitancy:

Endorsement of conspiracist ideation arguments would be positively correlated with Conspiracy Mentality (correlation coefficients ranging from 0.14 to 0.52 15 , 20 , 23 , 24 , 71 ).

Endorsement of distrust arguments would be positively correlated with General Distrust (correlation coefficients ranging from 0.20 to 0.58 19 , 24 , 72 ).

Endorsement of unwarranted belief arguments would be positively correlated with Pseudoscientific Beliefs (correlation coefficients ranging from 0.24 to 0.50 24 , 41 ).

Endorsement of worldview and politics arguments would be positively correlated with Free Market Ideology (correlation coefficients ranging from 0.22 to 0.24 41 , 42 ), Traditionalism (correlation coefficients ranging from 0.14 to 0.38 20 ), and Populism (correlation coefficients ranging from 0.72 to 0.79 43 ).

Endorsement of religious concern arguments would be positively correlated with Centrality of Religion ( r = 0.18 42 ).

Endorsement of moral concern arguments would be positively correlated with Moral Absolutism (no correlation coefficient previously reported 44 , 73 ).

Endorsement of fear and phobia arguments would be positively correlated with Trait Fear (correlation coefficients ranging from 0.09 to 0.50 20 , 74 , 75 ).

Endorsement of distorted risk perception arguments would be positively correlated with Perceived Vaccination Risk (correlation coefficients ranging from 0.11 to 0.86 30 ).

Endorsement of perceived self-interest arguments would be negatively correlated with Prosocial Behavioral Intentions (no correlation coefficient previously reported 76 , 77 , 78 , 79 , 80 , 81 , 82 , 83 ).

Endorsement of epistemic relativism arguments would be positively correlated with Alternative Epistemology (correlation coefficients ranging from 0.17 to 0.20 45 , 84 , 85 ).

Endorsement of reactance arguments would be positively correlated with General Reactance (correlation coefficients ranging from 0.14 to 0.47 20 , 24 ).

Data availibility

All datasets used in this article are publicly available at https://osf.io/27f5u/ .

Code availibility

All source code used in this article is publicly available at https://osf.io/27f5u/ .

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This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 964728 (JITSUVAX).

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February 17, 2021

COVID Vaccines Are Safe and Effective—What the Research Says

As more coronavirus vaccines are rolled out, researchers are learning about the extent and nature of side effects

By Ariana Remmel & Nature magazine

A healthcare worker administers a dose of the Pfizer-BioNTech Covid-19 vaccine at the Sun City Anthem Community Center vaccination site in Henderson, Nevada, U.S., on Thursday, Feb. 11, 2021.

Roger Kisby Getty Images

As people around the world receive COVID-19 vaccines, reports of temporary side effects such as headaches and fevers are rolling in. Much of this was expected—clinical-trial data for the vaccines authorized so far suggested as much. But now that millions of people are vaccinated, compared with the thousands enrolled in early studies, reports of some rare, allergic reactions are surfacing, and questions are arising about whether any deaths are linked to the shots.

There is no question that the current vaccines are effective and safe. The risk of severe reaction to a COVID-19 jab, say researchers, is outweighed by the protection it offers against the deadly coronavirus.  Nature  looks at what scientists are learning about the frequency and nature of side effects as huge numbers of people report their reactions to physicians and through safety-monitoring systems, such as smartphone apps.

How many people experience common side effects from COVID-19 vaccines?

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For the two available messenger RNA (mRNA) vaccines—one made by Moderna at Cambridge, Massachusetts, and the other developed through a collaboration between Pfizer in New York City and BioNTech in Mainz, Germany—a significant portion of people experience non-serious reactions, such as injection-site pain, headache and fatigue. These vaccines deliver bits of RNA that code for coronavirus proteins, which the body mounts a response against.

According to data  from the US Vaccine Adverse Event Reporting System (VAERS), about 372 out of every million administered doses of the mRNA vaccines lead to a non-serious reaction report. This number is lower than would be expected from clinical-trial data, which indicated that at least 80% of people would experience injection-site pain. Researchers running trials monitor patients closely and record every reaction. VAERS, meanwhile, relies on health-care workers and vaccinated individuals to self-report side effects.

So far, reactions to the mRNA vaccines are similar. These vaccines are administered in a two-dose regimen: the first shot triggers an immune reaction, and the second is a ‘booster’ that strengthens the body’s ability to fight the coronavirus. For the Pfizer–BioNTech vaccine, which has been in use longer than the Moderna vaccine and therefore has generated more data, side effects increase with the second dose.

In the United Kingdom, three million doses of another vaccine, developed by the University of Oxford and pharmaceutical firm AstraZeneca, have been doled out. This vaccine, which also requires a two-dose regimen, contains a inactivated cold-causing adenovirus with genetic instructions for making coronavirus proteins to trigger immunity.  According to UK safety-monitoring system  the Yellow Card Scheme, about 4,000 doses out of every million administered lead to adverse reactions. Again,  clinical-trial data suggest  that a higher frequency is more accurate: around 50% of participants had injection-site pain, headache or fatigue, according to data reported to the European Medicines Agency (EMA).

Few people have received a second dose of the Oxford–AstraZeneca vaccine because  the United Kingdom used its supplies  to administer a first dose to as many people as possible, but clinical-trial data presented to the EMA suggest that side effects of the second shot are milder than those caused by the first.

Safety data for shots rolling out in other parts of the world, such as the COVID-19 vaccines in China, are harder to come by. Preliminary data from clinical trials of the adenovirus-based Sputnik V vaccine in Russia suggest its most common side effects include flu-like symptoms and injection-site reactions.

How does that compare with side effects from an annual flu shot?

At least for the mRNA vaccines, physicians are seeing more side effects than for flu shots, says Helen Chu, an infectious-disease specialist at the University of Washington School of Medicine in Seattle, who directs the Seattle Flu Study. In clinical trials for the Pfizer–BioNTech vaccine, for instance, 75% of  participants reported  a ‘systemic reaction’, such as headache, fever or chills. In a clinical trial for the common influenza vaccine Flubok Quadravalent, around 34% of participants aged 18–49 had a systemic reaction. Side effects were even less frequent in study participants who were at least 50 years old.

Chu says the mRNA COVID-19 vaccines generate a particularly strong immune response that increases the risk of side effects, although this also means that the vaccines are working. She notes that her second dose of the Pfizer–BioNTech vaccine made her ill. “I got the vaccine, and 6 hours later, I had chills, a high fever, muscle aches and I went to bed for 24 hours,” she says. “Then by 36 hours later, it was totally over and I was back to normal.” But Chu would rather be temporarily ill from a vaccine than deal with COVID-19, “a potentially mortal disease that could kill me”, she says.

Have investigations linked any deaths to a COVID-19 vaccine?

Although some have questioned whether the vaccines have led to deaths, none have been directly attributed to a COVID-19 jab. After 33 elderly care-home residents in Norway died within 6 days of receiving the Pfizer–BioNTech vaccine, investigations by both the Norwegian Medicines Agency and  the World Health Organization  concluded that these deaths were in line with normal death rates in this age group and that the vaccine is still safe for older people. India's Ministry of Health and Family Welfare  reported 27 deaths  in the country, but none of these have been linked directly to a COVID-19 vaccine either.

It is “extremely difficult” to definitively link a death to the vaccine itself, says Hilda Bastian, a writer and scientist who specializes in validating evidence-based health claims. That is partially because the deaths reported so far have occurred days or weeks after an injection, making it hard to rule out other circumstances. Another reason is that, right now, clinicians are prioritizing vaccines largely for a population of older people with underlying health conditions. Most of those who have died after vaccination have been in this group, according to reports from the  United Kingdom  and the  United States .

What do researchers know about the rare, but severe, allergic reactions to the vaccines?

The Moderna vaccine elicits about three anaphylactic reactions per million doses administered, and the Pfizer–BioNTech vaccine triggers five reactions per million doses,  according to VAERS data . This is a higher rate than most other vaccines—including annual flu shots, which trigger anaphylaxis for only one out of every million doses administered. For the Oxford–AstraZeneca vaccine, 30 cases of anaphylaxis have been confirmed overall so far, out of a little more than 3 million administered doses. Vaccine specialists expect that these rates might change as more shots are administered.

Although some people have required hospitalization, all have fully recovered. Public-health officials advise people with a history of allergies to any of the vaccines’ ingredients not to get a COVID-19 jab.

Unlike COVID-19, anaphylaxis is treatable with drugs such as epinephrine if caught quickly, says Paul Offit, a vaccine and infectious-disease specialist at the Children’s Hospital of Philadelphia in Pennsylvania, who participated in the US Food and Drug Administration advisory-committee meetings that led the agency to authorize both mRNA vaccines. “I wish that SARS-CoV-2 could be immediately treated with a shot of epinephrine!” he says.

Most of the people who experienced anaphylaxis had reacted to other substances before: about 80% of people who reacted to the Pfizer–BioNTech vaccine, and 86% to the Moderna vaccine, had a history of allergies, according to the US Centers for Disease Control and Prevention.

The specific cause of the anaphylactic reactions remains unknown, but the US National Institute of Allergy and Infectious Diseases told  Nature  in an e-mail that the agency has designed a clinical trial to determine the underlying mechanism, but did not specify when the trial would begin.

What could be causing the allergic reactions?

Some researchers have had their eye on polyethylene glycol (PEG) as the anaphylaxis-causing agent in the mRNA vaccines. The Moderna and Pfizer–BioNTech vaccines use hollow lipid nanoparticles to store and then deliver their mRNA payload to cells. PEG is linked to the lipids in these particles and, under normal circumstances, helps them to sneak by the immune system. Although PEG-linked molecules are found in a variety of products, such as laxatives and gout medicines, they have been known to cause allergic reactions.

Follow-up studies in people who experienced anaphylaxis could help to determine whether PEG is the culprit, says Samuel Lai, a pharmaco-engineer at the University of North Carolina at Chapel Hill. If blood samples from these people contain anti-PEG antibodies, it could be an indicator, says Lai, but it is as yet unclear how long these proteins remain in the bloodstream after anaphylaxis.

Vaccines that don’t use PEG—such as the not-yet-authorized shot from Johnson & Johnson, which also uses an adenovirus to trigger immunity to the coronavirus—might be a way to vaccinate people with a sensitivity to the polymer, he adds.

Because mRNA vaccines have shown such promise, Ulrich Schubert, a polymer scientist at the University of Jena in Germany, thinks now is the time to invest in developing vaccine-compatible polymers that don’t cause allergic reactions. At the German Research Foundation-funded collaborative research center PolyTarget, where Schubert works, these studies are already in progress. “If we want to be ready for the next pandemic—which will come—we have to start now,” he says.

This article is reproduced with permission and was first published on February 16 2021.

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Should Schools Require Students to Get the Coronavirus Vaccine?

Los Angeles became the first major school district to mandate vaccines for students 12 and older who are attending class in person. Should all school districts follow suit?

Los Angeles Requires Vaccines for Students 12 and Older

The board of education voted, 6-0, to pass the measure, making los angeles the first major school district in the united states to mandate coronavirus vaccines for students 12 and older who are attending class in person..

“We are here today to discuss requiring all students who are eligible for the Covid-19 vaccination to be vaccinated, unless they have a qualified exemption or conditional admission.” “The bottom line for me, as an advocate of children and families and learning, is that the vaccine will help us avoid a winter like last year. The vaccine, for me and my family, has provided protection and to be able to just go on with our lives.” “I do not see this as your choice or my choice about my great-nieces and nephews and grandchildren or your children. I see this as a community necessity to protect the children under 12 who cannot be vaccinated.”

By Nicole Daniels

Were you required to receive certain vaccinations, such as those for protection against chickenpox or measles , before attending school or summer camp? Do you believe it is important for schools to require vaccinations like these to keep all students safe? Or do you think it should be up to individual families to decide?

In “ Los Angeles Mandates Vaccines for Students 12 and Older, ” Dana Goldstein writes about the school district’s decision to require coronavirus vaccines and how families have reacted:

Los Angeles is the first major school district in the United States to mandate coronavirus vaccines for students 12 and older who are attending class in person. With the Delta variant ripping across the country, the district’s Board of Education voted, 6-0, to pass the measure on Thursday afternoon. The Los Angeles Unified School District is the second largest in the nation, and the mandate would eventually apply to more than 460,000 students, including some enrolled at independent charter schools located in district buildings. The interim superintendent, Megan Reilly, said at Thursday’s board meeting that student vaccination was one way to ensure that the district’s classrooms would be able to remain open. Los Angeles had some of the country’s most extended school closures last year. Speaking about a 12th-grade athlete whom she met during a vaccination drive, Ms. Reilly said, “We owe this child his senior year.” Los Angeles already has a strict vaccine mandate for teachers and staff members, and the new student mandate will further increase the safety of the classroom. But it is also likely to be more divisive, with far-reaching educational repercussions. According to the Los Angeles County Department of Public Health, 58 percent of 12- to 18-year-olds living within the district’s boundaries have already received at least one dose of a vaccine. But polls show that many parents are hesitant to vaccinate their children against the coronavirus, raising the question of how many families will keep their children home to learn online or transfer them to schools that do not require the shots. Leaving the classroom again could be debilitating for some students. When virtual learning was widespread last academic year, millions of children fell behind academically; the impact was largest on low-income students and students of color.

Ms. Goldstein goes on to write that not everyone is in support of the vaccine mandates:

Vaccine hesitancy in Los Angeles exists across a broad range of demographic and ideological groups, from affluent, largely white, liberal parents who oppose a range of mainstream childhood vaccination practices; to conservative activists who have specifically targeted the coronavirus vaccines; to low-income Black and Hispanic families who are wary of the medical establishment.

The article continues:

Some parents, however, are likely to oppose any mandate because no coronavirus vaccine for children ages 12 to 15 has received full government approval. The Food and Drug Administration has authorized the Pfizer-BioNTech vaccine on an emergency basis for that age group and could potentially grant full approval this year. (No vaccine has been authorized in the United States for children younger than 12.) Some public health experts and parents have raised concerns about a rare side effect of that vaccine, a heart condition called myocarditis that is known to disproportionately affect young men. Angelica Ramos, 29, a mother of three public school students in the Baldwin Hills neighborhood of South Los Angeles, said she would either enroll her children in a charter school or home-school before vaccinating them. While she takes the pandemic seriously and supports masking, she said, she is concerned about side effects and said most of the parents she knew felt similarly. “It shouldn’t be mandatory,” she said. “It should be our decision.”

Students, read the entire article , then tell us:

What is your reaction to the decision made by the Los Angeles Unified School District? Do you believe it is an important step in keeping students and teachers safe? Or do you think parents and caregivers should be the ones to make decisions about whether students receive vaccinations?

Do you think more schools should have vaccine mandates? Would you want your school district to enact a mandate for students to attend in person? Why or why not?

According to the article, “All 50 states mandate vaccines for school attendance, such as those that protect against polio, measles, mumps, rubella and chickenpox.” If that is the case, why do you think there is such resistance to requiring the coronavirus vaccine?

Los Angeles has chosen to require vaccinations, while providing a remote option for families that refuse them. Other districts, like New York City, have reopened schools for in-person learning without requiring vaccinations, but only offer limited online schooling for students with medical issues. Do you think one of these approaches is better than the other? If so, which one and why? What other options do you think schools should consider to keep students safe this school year?

Schools aren’t the only institutions that have started to require vaccines. President Biden recently moved to mandate vaccines for health care workers, federal contractors and a vast majority of federal workers, and to mandate that all companies with more than 100 workers require vaccinations or weekly testing.

Supporters of this plan say vaccine mandates encourage more people to get vaccinated, in turn protecting the most vulnerable among us, including people with disabilities and children too young to be vaccinated. Opponents argue that it is government overreach and that individuals should be able to make decisions for themselves without risk of losing their jobs.

What is your reaction to vaccine mandates across the public and private sectors? What are the benefits and limitations of requiring vaccinations? Are all arguments for and against such mandates equal? If not, which should we weigh more heavily?

Learn more about Student Opinion here and find all of our questions in this column . Teachers, see how you can incorporate this feature into your classroom routine here .

Students 13 and older in the United States and the United Kingdom, and 16 and older elsewhere, are invited to comment. All comments are moderated by the Learning Network staff, but please keep in mind that once your comment is accepted, it will be made public.

Nicole Daniels joined The Learning Network as a staff editor in 2019 after working in museum education, curriculum writing and bilingual education. More about Nicole Daniels

The Trumpification of the Supreme Court

The conservative justices have shown they are ready to sacrifice any law or principle to save the former president.

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The notion that Donald Trump’s supporters believe that he should be able to overthrow the government and get away with it sounds like hyperbole, an absurd and uncharitable caricature of conservative thought. Except that is exactly what Trump’s attorney D. John Sauer argued before the Supreme Court yesterday, taking the position that former presidents have “absolute immunity” for so-called official acts they take in office.

“How about if a president orders the military to stage a coup?” Justice Elena Kagan asked Sauer. “I think it would depend on the circumstances whether it was an official act,” Sauer said after a brief exchange. “If it were an official act … he would have to be impeached and convicted.”

“That sure sounds bad, doesn’t it?” Kagan replied later.

The Democratic appointees on the bench sought to illustrate the inherent absurdity of this argument with other scenarios as well—Kagan got Sauer to admit that the president could share nuclear secrets, while Justice Sonia Sotomayor presented a scenario in which a president orders the military to assassinate a political rival. Sauer said that might qualify as an official act too. It was the only way to maintain the logic of his argument, which is that Trump is above the law.

David A. Graham: The cases against Trump: A guide

“Trying to overthrow the Constitution and subvert the peaceful transfer of power is not an official act, even if you conspire with other government employees to do it and you make phone calls from the Oval Office,” Michael Waldman, a legal expert at the Brennan Center for Justice, a liberal public-policy organization, told me.

Trump’s legal argument is a path to dictatorship. That is not an exaggeration: His legal theory is that presidents are entitled to absolute immunity for official acts. Under this theory, a sitting president could violate the law with impunity, whether that is serving unlimited terms or assassinating any potential political opponents, unless the Senate impeaches and convicts the president. Yet a legislature would be strongly disinclined to impeach, much less convict, a president who could murder all of them with total immunity because he did so as an official act. The same scenario applies to the Supreme Court, which would probably not rule against a chief executive who could assassinate them and get away with it.

The conservative justices have, over the years, seen harbingers of tyranny in union organizing , environmental regulations , civil-rights laws , and universal-health-care plans . When confronted with a legal theory that establishes actual tyranny, they were simply intrigued. As long as Donald Trump is the standard-bearer for the Republicans, every institution they control will contort itself in his image in an effort to protect him.

The Supreme Court, however, does not need to accept Trump’s absurdly broad claim of immunity for him to prevail in his broader legal battle. Such a ruling might damage the image of the Court, which has already been battered by a parade of hard-right ideological rulings. But if Trump can prevail in November, delay is as good as immunity. The former president’s best chance at defeating the federal criminal charges against him is to win the election and then order the Justice Department to dump the cases. The Court could superficially rule against Trump’s immunity claim, but stall things enough to give him that more fundamental victory.

If they wanted, the justices could rule expeditiously as well as narrowly , focusing on the central claim in the case and rejecting the argument that former presidents have absolute immunity for acts committed as president, without getting into which acts might qualify as official or not. Sauer also acknowledged under questioning by Justice Amy Coney Barrett that some of the allegations against Trump do not involve official acts but private ones, and so theoretically the prosecution could move ahead with those charges and not others. But that wouldn’t necessarily delay the trial sufficiently for Trump’s purposes.

“On big cases, it’s entirely appropriate for the Supreme Court to really limit what they are doing to the facts of the case in front of it, rather than needing to take the time to write an epic poem on the limits of presidential immunity,” Waldman said. “If they write a grant opinion, saying no president is above the law, but it comes out too late in the year, they will have effectively immunized Trump from prosecution before the election while pretending not to.”

Trump’s own attorneys argued in 2021, during his second impeachment trial, that the fact that he could be criminally prosecuted later was a reason not to impeach him. As The New York Times reported , Trump’s attorney Bruce Castor told Congress that “after he is out of office,” then “you go and arrest him.” Trump was acquitted in the Senate for his attempted coup after only a few Republicans voted for conviction; some of those who voted to acquit did so reasoning that Trump was subject to criminal prosecution as a private citizen. The catch-22 here reveals that the actual position being taken is that the president is a king, or that he is entitled to make himself one. At least if his name is Donald Trump.

David A. Graham: The Supreme Courts goes through the looking glass of presidential immunity

Democracy relies on the rule of law and the consent of the governed—neither of which is possible in a system where the president can commit crimes or order them committed if he feels like it. “We can’t possibly have an executive branch that is cloaked in immunity and still expect them to act in the best interests of the people in a functioning democracy,” Praveen Fernandes, the vice president of the Constitutional Accountability Center, a liberal legal organization, told me.

The only part of Trump’s case that contains anything resembling a reasonable argument is the idea that without some kind of immunity for official acts, presidents could be prosecuted on a flimsy basis by political rivals. But this argument is stretched beyond credibility when it comes to what Trump did, which was to try repeatedly and in multiple ways to unlawfully seize power after losing an election. Even if the prospect of presidents being prosecuted for official acts could undermine the peaceful transfer of power, actually trying to prevent the peaceful transfer of power is a much more direct threat—especially because it has already happened. But the Republican-appointed justices seemed much more concerned about the hypothetical than the reality.

“If an incumbent who loses a very close, hotly contested election knows that a real possibility after leaving office is not that the president is going to be able to go off into a peaceful retirement but that the president may be criminally prosecuted by a bitter political opponent,” Justice Samuel Alito asked, “will that not lead us into a cycle that destabilizes the functioning of our country as a democracy?”

Trump has the conservative justices arguing that you cannot prosecute a former president for trying to overthrow the country, because then they might try to overthrow the country, something Trump already attempted and is demanding immunity for doing. The incentive for an incumbent to execute a coup is simply much greater if the Supreme Court decides that the incumbent cannot be held accountable if he fails. And not just a coup, but any kind of brazen criminal behavior. “The Framers did not put an immunity clause into the Constitution. They knew how to,” Kagan pointed out during oral arguments. “And, you know, not so surprising, they were reacting against a monarch who claimed to be above the law. Wasn’t the whole point that the president was not a monarch and the president was not supposed to be above the law?”

At least a few of the right-wing justices seemed inclined to if not accept Trump’s immunity claim, then delay the trial, which would likely improve his reelection prospects. As with the Colorado ballot-access case earlier this year, in which the justices prevented Trump from being thrown off the ballot in accordance with the Constitution’s ban on insurrectionists holding office , the justices’ positions rest on a denial of the singularity of Trump’s actions.

No previous president has sought to overthrow the Constitution by staying in power after losing an election. Trump is the only one, which is why these questions are being raised now. Pretending that these matters concern the powers of the presidency more broadly is merely the path the justices sympathetic to Trump have chosen to take in order to rationalize protecting the man they would prefer to be the next president. What the justices—and other Republican loyalists—are loath to acknowledge is that Trump is not being uniquely persecuted; he is uniquely criminal.

This case—even more than the Colorado ballot-eligibility case—unites the right-wing justices’ political and ideological interests with Trump’s own. One way or another, they will have to choose between Trumpism and democracy. They’ve given the public little reason to believe that they will choose any differently than the majority of their colleagues in the Republican Party.