dissertation on economic burden

• Open access
• Published: 05 October 2022

The economic burden of malaria: a systematic review

• Mônica V. Andrade 1 ,
• Kenya Noronha 1 ,
• Bernardo P. C. Diniz 1 ,
• Gilvan Guedes 1 ,
• Lucas R. Carvalho 1 ,
• Valéria A. Silva 1 ,
• Júlia A. Calazans 2 ,
• André S. Santos 1 ,
• Daniel N. Silva 1 &
• Marcia C. Castro 3  

Malaria Journal volume  21 , Article number:  283 ( 2022 ) Cite this article

15k Accesses

19 Citations

23 Altmetric

Metrics details

Quantifying disease costs is critical for policymakers to set priorities, allocate resources, select control and prevention strategies, and evaluate the cost-effectiveness of interventions. Although malaria carries a very large disease burden, the availability of comprehensive and comparable estimates of malaria costs across endemic countries is scarce.

A literature review to summarize methodologies utilized to estimate malaria treatment costs was conducted to identify gaps in knowledge.

Only 45 publications met the inclusion criteria. They utilize different methods, include distinct cost components, have varied geographical coverage (a country vs a city), include different periods in the analysis, and focus on specific parasite types or population groups (e.g., pregnant women).

Conclusions

Cost estimates currently available are not comparable, hindering broad statements on the costs of malaria, and constraining advocacy efforts towards investment in malaria control and elimination, particularly with the finance and development sectors of the government.

In 2020, 241 million cases and 627 thousand deaths of malaria were estimated worldwide. Between 2000 and 2015, malaria case incidence reduced by 27%, while the mortality rate reduced by 60%. Since 2015 the decline has slowed (and even reversed in some countries) [ 1 ]. Ten countries eliminated malaria between 2000 and 2019, and 21 remained 3 years without an indigenous case. Reducing the malaria burden minimizes out-of-pocket expenses, avoids days lost at school or work due to an infection, and is likely to contribute to economic development. Among countries with intense malaria transmission, the Gross Domestic Product (GDP) grew 1.3% less per person per year, accounting for relevant social and economic factors [ 2 ].

Haakenstad et al. [ 3 ] estimated that global malaria spending—accounting both for government and out-of-pocket spending—amounted to $4.3 billion (95% UI 4.2–4.4) in 2016, which is an 8.6% (95% UI 8.1–8.9) per year increase over malaria spending in 2000. Estimates were mainly based on national accounts systems from 106 countries and included expenses to prevent and treat malaria. However, macro-analyses such as these, while useful for understanding the landscape of malaria financing, have limited use for strategic planning since they are not able to break down the costs. Quantifying the economic cost of malaria is critical for policymakers to set priorities, allocate resources, select control and prevention strategies, and evaluate the cost-effectiveness of interventions.

Among the principles for a world free of malaria is the stratification by malaria burden, which facilitates optimizing the selection of malaria interventions that are likely to be most effective given the local context. The process of stratification supports decision-making and considers financial resources available for malaria control [ 4 ] helping governments to achieve the best outcomes given limited resources. In 2019, the World Health Organization (WHO) Regional Office for Africa proposed a costing tool for countries to plan the budget of their national malaria control programmes [ 5 ]. The tool supports budget planning, but it does not assess executed services and does not include indirect costs. Although frameworks for analysis of the economic costs of malaria have been proposed [ 6 , 7 , 8 ] comprehensive estimates that break down costs by different stakeholders (health providers, individuals, community), that consider inequities across geographies, and that account for productivity losses and other non-tangible costs are scarce. Only two reviews on the economic burden of malaria are available [ 7 , 8 , 9 ]. The first, published in 2003, compiled evidence on direct and indirect costs of malaria for both families and the healthcare system [ 7 ]. They estimated monthly per capita expenditures incurred by households for malaria prevention and treatment ranging from, respectively, US$0.05 and US$0.41 in Malawi to US$2.10 and US$3.88 in the urban area of Cameroon. Overall, the average duration of absenteeism due to illness ranged from one to 5 days, reaching 18 days in Ethiopia. Despite detailed estimates of costs, the study was based on critical instead of a systematic review and focused only on African countries. The second, published in 2016, only focused on the economic and financial costs of malaria control, elimination, and eradication, without considering the treatment costs, either direct or indirect [ 9 ].

This study aims to conduct a systematic review of the economic burden of malaria. The analysis was conducted to assess whether estimates are available, for different regions where malaria is endemic, considering the perspectives of both individuals and health systems. Also, it aims at appraising the comprehensiveness and comparability of the estimates. Addressing this knowledge gap is important to target public policies that reduce the welfare losses due to malaria. Identifying and mitigating the costs incurred by families is particularly relevant to reducing inequalities.

Study design

A systematic review was conducted to examine the empirical evidence on the economic burden of malaria and its cost components following the principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement [ 10 , 11 ].

Search strategy and selection criteria

Studies published between 2000 and 2020 (up to May 8) were selected from three scientific articles databases: Medline (via PubMed), Lilacs (via BVS), and Embase. Since the epidemiology of the disease has changed worldwide, the search included only articles published from 2000 onwards to capture the recent trends in the economic burden of malaria. The research question in PECO format (Population, Exposure, Comparator, and Outcomes) and the full search strategy are available in Additional file 1 . The terms used were “economics, medical”, “economics, hospital”, “cost and cost analysis”, “cost of illness”, “cost control”, “health care costs”, “health expenditures”, and “malaria” or “paludism”.

References were imported into EndNote X9 [ 12 ] and transported into Rayyan for duplicates removal and screening [ 13 ]. All references were screened by title and abstract, and those selected had the full texts retrieved and assessed. The exclusion criteria were: (i) cost-effectiveness analyses of treatments, (ii) vaccine efficacy/cost studies, (iii) evaluations of long-term consequences of malaria during childhood, (iv) analyses of specific interventions to control or to eliminate malaria, (v) cost analyses of malaria combined with other infectious diseases that did not allow for the disaggregation of costs by disease, (vi) treatment guidelines, (vii) systematic reviews/literature reviews, (viii) studies without cost components disaggregation or with at most one cost component, and (ix) cost studies about imported malaria. Economic analyses of specific programmes were excluded since they usually report expenditures that are context-related to the intervention. Only full texts were included. No restrictions on language or geographical focus were made.

Seven researchers performed the screening and each paper was independently assessed for inclusion by at least two of them. Any differences were resolved by consensus, following recommendations from the Cochrane Collaboration [ 14 ].

Data extraction and analysis

A qualitative synthesis of the results was performed by systematically organizing the information extracted from the included studies. Data extracted included country and year of study, year of publication, currency, cost components, cost disaggregated by selected attributes (age and severity of the disease), source of research funding, and perspective of the study (healthcare system, household, and societal). A societal perspective is a comprehensive approach that considers healthcare system costs and direct and indirect household costs. The economic costs often fall into two categories. First, direct costs that include medical (treatment and control) and non-medical (transport, lodging, and food) expenses. Second, indirect costs that include absenteeism (short-term absence from work or school due to health problems), presenteeism (reduced performance while working or at school due to health problems), and value of lost time due to morbidity or premature mortality. Economic burden estimates are a broad framework to evaluate the wellbeing impacts as it considers all the economic costs associated with the disease. A broader perspective includes all stakeholders, and the costs are presented as the share of the gross domestic product. Other estimates consider all expenses financed by a specific agent, such as families. In this case, the economic burden is defined as a proportion of the household budget.

One researcher performed data extraction, which was then checked by other two. Information on cost components sought in each study is detailed in Additional file 2 . Average values in local currency were extracted and, to facilitate comparison, all cost values were converted into Purchase Power Parity 2020 American dollars (PPP-USD) using the Campbell and Cochrane Economics Methods Group (CCEMG)—Evidence for Policy and Practice Information and Coordinating Centre (EPPI-Centre) cost converter [ 15 ]. Descriptive analyses summarized the main characteristics of the selected studies, and all with valid information were included in the qualitative synthesis.

Quality assessment

There is no standard method to evaluate the quality of cost studies. Drawing from the available literature [ 16 , 17 , 18 ] nine items were selected to assess the reporting quality of the selected studies (Additional file 3 ). For each item, there were four possible response categories: (i) fully meet the item; (ii) partially meet the item; (iii) did not meet the item; (iv) not applicable. One researcher checked the quality assessment for each paper and any uncertainties were decided by consensus.

Study selection

A total of 6408 articles were initially identified through the database search (Fig.  1 ). After the removal of 722 duplicates and 5472 references not eligible based on titles and abstracts, 214 studies were suitable for a full review. Following exclusion criteria detailed in Additional file 4 , 140 articles were excluded. Despite multiple attempts, it was not possible to obtain the full text of 29 studies (only abstracts were available). The final sample included 45 publications (Additional file 5 ).

Flow diagram of the systematic review article selection

Characteristics of the studies

The selected studies analysed 27 countries, almost half from Africa. The most studied countries were Nigeria (n = 7) and Kenya (n = 5). Only three studies involved a cross-country comparison [ 19 , 20 , 21 ]. Studies were mostly published between the years 2015 and 2020 (44.4%). From 2005 to 2015 only countries from Africa and the Pacific were investigated, while studies analysing the Americas only appeared after 2015 (Fig.  2 ).

Distribution of studies according to the World Health Organization (WHO) regions from 2000 to 2020. The systematic review covers the period of January 1, 2000, to May 8, 2020. Some studies refer to more than one country

Most selected studies (76%) received financial support (Additional file 6 ). The most frequent donors were the World Bank/United Nations Development Programme—UNDP/WHO Special Programme for Training and Research in Tropical Diseases, and the Bill and Melinda Gates Foundation, which funded 20% and 15.5% of the studies, respectively. International health organizations (e.g., WHO) and foreign agencies (e.g., European Union) were important funders for studies in Africa. Only one study was funded by the private sector, specifically the pharmaceutical industry [ 21 ].

Two-thirds of the selected papers (67%) carried out the cost analysis using some form of stratification (Additional file 7 ), such as individual attributes (age and socioeconomic status), access conditions (type of service and distance to the hospital), illness attributes (type of parasite, type of care, and disease severity), endemicity level, seasonality/raining period, and place of residence.

Qualitative synthesis

There was variation in the cost analysis in terms of the components investigated, source of costs (household or healthcare system), unit of measurement (cost per episode, per household, or per capita), and summary statistics (mean or median). Cost estimates based on household data were the most prevalent (95.5% of the studies), but the number of cost items included varied significantly; 88.9% investigated at least one household direct cost, and 75.6% at least one indirect cost. Medication and treatment/diagnosis were the most reported direct medical cost (Table 1 ). The majority (n = 41) of the studies reported average cost estimates, and cost per episode (n = 35) was the most common unit of measurement. These differences in estimating and presenting the results limit the comparability of malaria costs across countries.

The magnitude of costs depends on several factors such as the healthcare system organization, the level of healthcare coverage, treatment protocols, and private market organization (Table 2 ). Therefore, estimated costs vary widely, with total and indirect household costs showing the largest variation (e.g., total per capita household costs varied from US$0.48 in Sri Lanka to US$214.68 in India, and total per capita indirect costs was US$0.25 in Kenya and US$182 in India). Patient absenteeism ranged from 1.3 days in Brazil to 11 days in India, while days of caregiver absenteeism varied from 0.2 in Brazil to 9.2 in Malawi.

In addition to cost components, ten studies estimated the economic burden of malaria. Seven considered a household perspective, two utilized a societal perspective, and one included household and healthcare system costs components but did not consider indirect costs (Table 3 ). All studies focused on African countries except one that used data from India. Estimates were based on the nominal value of total costs [ 21 , 22 ], or its share in the gross domestic product (GDP) [ 23 ] or the household budget [ 24 , 25 , 26 ]. Considering the economic burden of malaria as a percentage of the family budget, results range from 3.12% in India to 8.23% in Nigeria. Catastrophic health expenses due to malaria, measured as the household healthcare expenses exceeding a specified threshold of household income or household capacity to pay, ranged from 17.8% to 22.5% of families in Sudan, Mozambique, and Zimbabwe [ 20 , 27 , 28 ].

Overall, the selected studies met the items that should be presented in economic cost studies (Additional file 8 ). The description and analysis of the cost components as well as the inclusion of detailed information about the currency and adjustment for inflation were the main limitations encountered.

A systematic review is presented to extract and synthesize evidence on the economic costs of malaria published since 2000. Only 45 publications met the inclusion criteria, out of the 6,408 search results. Most analysed African countries (about 75%), where the highest burden of malaria is concentrated [ 1 ]. Indeed, seven of the 11 high-burden countries (which concentrate about 70% of malaria burden) were analyzed: Burkina Faso, the Democratic Republic of the Congo, Ghana, Mozambique, Nigeria, United Republic of Tanzania, and India. While the focus on African countries is not surprising, the scarcity of cost estimates for countries in the Americas and Asia is concerning for at least two reasons. First, as some of those countries approach elimination, cost estimates are critical to inform and sensitize ministers of finance and health to prevent defunding elimination efforts. Second, estimates on costs of malaria as countries approach and achieve elimination will be essential knowledge to high-burden countries in the future. Therefore, cost estimates for countries with diverse transmission intensity remains a gap in the literature.

Global funding has been crucial for the development of studies on the economic costs of malaria with 76% of the selected articles having had received a grant. Three main funders jointly financed 45% of the studies on economic costs of malaria: UNDP/WB/WHO special programme for research and training in tropical diseases, the Bill and Melinda Gates Foundation, and the Wellcome Trust. These results align with previous analyses that show a concentration of the resources in a few funders. Viergever and Hendriks [ 29 ] identified the 55 most important public and philanthropic funders. Among the public funders, the US National Institutes of Health ($26.1 billion), the European Commission ($3.7 billion), and the UK Medical Research Council ($1.3 billion) stood out with the highest annual research budgets. The largest philanthropic funders were the Wellcome Trust ($909.1 million), Howard Hughes Medical Institute ($752 million), and Bill and Melinda Gates Foundation ($462.6 million). Official Development Assistance Agencies and Multilateral organizations contributed smaller amounts; the most substantial funding was from the USAID ($186.4 million) and the World Health Organization ($135.0 million). Head et al. showed that between 1993 and 2017, 333 different grants funded malaria-related research investment in sub-Saharan Africa, totaling US$814.4 million [ 30 ]. The US National Institutes of Health and the Bill & Melinda Gates Foundation were the main grantors, contributing 60% of the funds [ 30 ].

Results shows that there is no systematization of cost components of malaria and no comprehensive and comparable quantification of the economic burden of the disease to society and governments. Comparability of results summarized in this review is difficult because studies vary by the type of cost components included, the estimation method, and the regional level of analysis. Even studies that estimated costs for more than one country have limited comparability [ 19 , 20 , 21 ]. Devine et al. [ 19 ] is the most comprehensive study, based on a multicentric approach, including nine countries—Afghanistan, Brazil, Colombia, Ethiopia, Indonesia, Philippines, Peru, Thailand, and Vietnam. It investigated direct and indirect household costs for all countries, while costs of treatment and diagnosis from the healthcare system perspective were available only for four countries. The range of estimated values was relatively high, especially for families, with the average total cost varying from US$8.7 in Afghanistan to US$254.7 in Colombia. The main component of the household cost was productivity loss due to illness.

The methodological disparities across selected studies stem from the challenges in investigating healthcare costs. Surveying costs from the provider’s perspective depends on the availability of a systematic and organized information system that stores detailed categories of health spending. Also, some categories of public expenditure may be aggregated for different health conditions or programmes (e.g., surveillance, vector control), making it necessary to implement apportionment strategies to obtain numbers specific for malaria. Similarly, information about the costs associated with the maintenance of the health unit’s physical structure and human resources often must be partitioned among the different diseases based on some criteria [ 16 , 31 , 32 , 33 , 34 ].

Most of the studies included in the review utilized household surveys or interviews with patients/caregivers as the primary sources of information. Therefore, most of the costs were estimated from a household perspective. Still, the comparability of costs across studies is hampered by differences in the cost components included, which varied depending on the specificity of the country/region, the organization of the healthcare system, and the families' vulnerability conditions.

Transportation fees were the most investigated cost component, [ 19 , 22 , 24 , 35 , 36 , 37 , 38 , 39 , 40 , 41 , 42 ] ranging from no cost in the urban area of Benin [ 43 ], to US$47.49 for pregnant women who received inpatient care in Manaus, Brazil [ 42 ]. High transportation costs in the Brazilian Amazon reflect the long distances that some isolated communities need to travel to receive hospital care [ 44 ]. Absenteeism was the second most investigated cost component. In low-income malaria-endemic areas, with precarious labour market conditions, and where family farming is one of the main economic activities, families usually have poor access to social security schemes and incur significant losses in the event of illnesses episodes [ 45 , 46 , 47 , 48 ]. The review showed that the number of workdays lost per episode of malaria ranged from 1.4 in Brazil [ 19 ] to 11 days in high transmission areas of India [ 24 ]. Absenteeism days may translate into a high economic burden on families. In Vietnam, workdays lost in the treatment of malaria reached 2% of the total annual household production [ 45 ]. Of note is the fact that just one study considered the costs of mortality in the estimates. Potential life-long productivity losses due to premature death were monetized considering the present value of the institutional minimum wage. Considering children aged 0–1 and 1–4 years, the costs of mortality (in thousands) due to malaria was equal to US$ 11.8 and US$ 13.8 in Ghana, US$ 7.6 and US$ 8.9 in Kenya, and US$ 6.9 and US$ 8.1 in Tanzania, respectively [ 21 , 49 ].

Only eight studies estimated the costs associated with prevention of malaria: six focused on costs incurred by families [ 24 , 26 , 37 , 42 , 48 , 50 ] and two focused on the healthcare system [ 24 , 37 ]. Since governments are usually in charge of implementing prevention and surveillance actions, costs associated with these strategies should be one of the main components estimated from the healthcare system perspective [ 3 ].

Ten studies estimated the economic burden of malaria, but they differ in terms of the perspective and the measurement used to express the economic burden. Three studies considered a broader estimation that included both the household and healthcare system perspectives [ 21 , 22 , 23 ]. To assess welfare losses, economic burden should be expressed as the share of the GDP. However, that measure was only calculated by one of those studies that was conducted for Tanzania and considered a comprehensive set of spending from private, government, and international donors [ 23 ]. It showed that the burden reached 1.1% of the GDP and 39% of the public spending on health; families bear most of the malaria expenditure (71%), followed by the government (20%). The remaining seven papers conducted a more targeted estimate that computed expenses incurred by households. In this case, the economic burden was expressed as the weight of malaria costs on the household budget or the percentage of families incurring in catastrophic expenditures with results showing that malaria can substantially affect the family’s wellbeing [ 20 , 24 , 26 , 27 , 28 , 51 , 52 ].

In addition to the limited number of studies that provided estimates on the costs of malaria, the systematic review showed that one of the main limitations was the lack of a standard conceptual framework of the costs to be included and a methodological approach for the calculation. Estimates often vary in several aspects: (i) types of costs considered, (ii) number of years of data used, (iii) choice of cost analysis perspective (healthcare system, household or societal), (iv) geographical coverage, and (v) types of parasites considered. Ideally, the conceptual framework should distinguish different types of costs and stakeholders. Estimates should detail direct and indirect costs and consider differences due to parasite type and spatial geographical heterogeneities in transmission. The cost estimation should also allow its decomposition by different stakeholders (health providers, individual/household, and the community) to target public policies that reduce the welfare losses due to malaria. Identifying the cost components incurred by families is particularly relevant as their economic burden depends on their vulnerability and the organization of the healthcare system. These differences are critical for implementing a proper decision-making process of control strategies and thus must be reflected in cost estimates.

The limited available estimates are hardly comparable, and there are no comprehensive figures on the cost of malaria from both societal and healthcare system perspectives. This knowledge gap affects proper resource allocation, selection of prevention and control strategies, and evaluation of the cost-effectiveness of interventions. Also, it constrains advocacy efforts towards investment in malaria control and elimination, particularly with the finance and development sectors of the government.

Availability of data and materials

Not applicable.

Abbreviations

Virtual Health Library

Campbell and Cochrane Economics Methods Group

Brazilian National Council for Scientific and Technological Development

Department of Science and Technology

Evidence for Policy and Practice Information and Coordinating Centre

Gross Domestic Product

Medical Literature Analysis and Retrieval System Online

Population, Exposure, Comparator, and Outcomes

Purchase Power Parity American dollars

Preferred Reporting Items for Systematic Reviews and Meta-Analysis

Innovation and Health Strategic Products

World Bank/United Nations Development Programme

World Health Organization

WHO. World malaria report 2021. Geneva: World Health Organization; 2021.

Google Scholar  

Gallup JL, Sachs JD. The economic burden of malaria. Am J Trop Med Hyg. 2001;64:85–96.

Article   CAS   PubMed   Google Scholar  

Haakenstad A, Harle AC, Tsakalos G, Micah AE, Tao T, Anjomshoa M, et al. Tracking spending on malaria by source in 106 countries, 2000–16: an economic modelling study. Lancet Infect Dis. 2019;19:703–16.

Article   PubMed   PubMed Central   Google Scholar  

WHO. A framework for malaria elimination. Geneva: World Health Organization; 2017.

WHO. User guide for the malaria strategic and operational plan costing tool. Brazzaville: World Health Organization Regional Office for Africa; 2019.

Arrow KJ, Panosian C, Gelband H. Saving lives, buying time: economics of malaria drugs in an age of resistance. Institute of Medicine Committee on the Economics of Antimalarial Drugs. . Washington: National Academies Press; 2004.

Chima RI, Goodman CA, Mills A. The economic impact of malaria in Africa: a critical review of the evidence. Health Policy. 2003;63:17–36.

Article   PubMed   Google Scholar  

Shepard DS, Ettling MB, Brinkmann U, Sauerborn R. The economic cost of malaria in Africa. Trop Med Parasitol. 1991;42:199–203.

CAS   PubMed   Google Scholar  

Shretta R, Avancena AL, Hatefi A. The economics of malaria control and elimination: a systematic review. Malar J. 2016;15:593.

Moher D, Liberati A, Tetzlaff J, Altman DG. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. PLoS Med. 2009;6: e1000097.

Liberati A, Altman DG, Tetzlaff J, Mulrow C, Gøtzsche PC, Ioannidis JP, et al. The PRISMA statement for reporting systematic reviews and meta-analyses of studies that evaluate healthcare interventions: explanation and elaboration. BMJ. 2009;339: b2700.

The EndNote Team. EndNote. EndNote X9 edition. Philadelphia: Clarivate; 2013.

Ouzzani M, Hammady H, Fedorowicz Z, Elmagarmid A. Rayyan-a web and mobile app for systematic reviews. Syst Rev. 2016;5:210.

Higgins JP, Thomas J, Chandler J, Cumpston M, Li T, Page MJ, et al. Cochrane handbook for systematic reviews of interventions version 6.0. 2nd Edn. 2019.

CCEMG-EPPI-Centre cost converter; Version 1.4: The Campbell and Cochrane Economics Methods Group (CCEMG) and the Evidence for Policy and Practice Information and Coordinating Centre (EPPI-Centre) https://eppi.ioe.ac.uk/costconversion/

Drummond MF SM, Claxton K, Stoddart GL, Torrance GW. Methods for the Economic Evaluation of Health Care Programmes. 4th Edn. 2015.

Fukuda H, Imanaka Y. Assessment of transparency of cost estimates in economic evaluations of patient safety programmes. J Eval Clin Pract. 2009;15:451–9.

Silva EN, Galvão TF, Pereira MG, Silva MT. Economic evaluation of health technologies: checklist for critical analysis of published articles. Pan Am J Public Health. 2014;35:219–27.

Devine A, Pasaribu AP, Teferi T, Pham HT, Awab GR, Contantia F, et al. Provider and household costs of Plasmodium vivax malaria episodes: a multicountry comparative analysis of primary trial data. Bull World Health Organ. 2019;97:828–36.

Castillo-Riquelme M, McIntyre D, Barnes K. Household burden of malaria in South Africa and Mozambique: is there a catastrophic impact? Trop Med Int Health. 2008;13:108–22.

Sicuri E, Vieta A, Lindner L, Constenla D, Sauboin C. The economic costs of malaria in children in three sub-Saharan countries: Ghana, Tanzania and Kenya. Malar J. 2013;12:307.

Alonso S, Chaccour CJ, Elobolobo E, Nacima A, Candrinho B, Saifodine A, et al. The economic burden of malaria on households and the health system in a high transmission district of Mozambique. Malar J. 2019;18:360.

Jowett M, Miller NJ. The financial burden of malaria in Tanzania: implications for future government policy. Int J Health Plann Manage. 2005;20:67–84.

Singh MP, Saha KB, Chand SK, Sabin LL. The economic cost of malaria at the household level in high and low transmission areas of central India. Acta Trop. 2019;190:344–9.

Chuma J, Okungu V, Molyneux C. The economic costs of malaria in four Kenyan districts: do household costs differ by disease endemicity? Malar J. 2010;9:149.

Somi MF, Butler JR, Vahid F, Njau JD, Kachur SP, Abdulla S. Economic burden of malaria in rural Tanzania: variations by socioeconomic status and season. Trop Med Int Health. 2007;12:1139–47.

Abdel-Hameed AA, Abdalla HM, Alnaury AH. Household expenditure on malaria case management in Wad-Medani. Sudan Afr J Med Med Sci. 2001;30(Suppl):35–8.

PubMed   Google Scholar  

Gunda R, Shamu S, Chimbari MJ, Mukaratirwa S. Economic burden of malaria on rural households in Gwanda district, Zimbabwe. Afr J Prim Health Care Fam Med. 2017;9:e1–6.

Viergever RF, Hendriks TC. The 10 largest public and philanthropic funders of health research in the world: what they fund and how they distribute their funds. Health Res Policy Syst. 2016;14:12.

Head MG, Goss S, Gelister Y, Alegana V, Brown RJ, Clarke SC, et al. Global funding trends for malaria research in sub-Saharan Africa: a systematic analysis. Lancet Glob Health. 2017;5:e772–81.

Etges APS, Schlatter RP, Neyeloff JL, Araújo DV, Bahia LC, Cruz L, et al. Estudos de Microcusteio aplicados a avaliações econômicas em saúde: uma proposta metodológica para o Brasil. J Bras Econ Saúde. 2019;11:87–95.

Newbrander WL, Lewis E. Hospital costing model manual. Management Sciences for Health. USAID: Health Reform and Financing and Sustainability Project. 1999.

Etges APB, Cruz LN, Notti RK, Neyeloff JL, Schlatter RP, Astigarraga CC, et al. An 8-step framework for implementing time-driven activity-based costing in healthcare studies. Eur J Health Econ. 2019;20:1133–45.

Article   Google Scholar  

Cavassini ACM, Lima SAM, Calderon IMP, Rudge MVC. Avaliações econômicas em Saúde: apuração de custos no atendimento de gestações complicadas pelo diabete. Rev Adm Saude. 2010;12:23–30.

Beogo I, Huang N, Drabo MK, Ye Y. Malaria related care-seeking-behaviour and expenditures in urban settings: a household survey in Ouagadougou. Burkina Faso Acta Trop. 2016;160:78–85.

Hennessee I, Chinkhumba J, Briggs-Hagen M, Bauleni A, Shah MP, Chalira A, et al. Household costs among patients hospitalized with malaria: evidence from a national survey in Malawi, 2012. Malar J. 2017;16:395.

Sicuri E, Bardaji A, Sanz S, Alonso S, Fernandes S, Hanson K, et al. Patients’ costs, socio-economic and health system aspects associated with malaria in pregnancy in an endemic area of Colombia. PLoS Negl Trop Dis. 2018;12: e0006431.

Karyana M, Devine A, Kenangalem E, Burdarm L, Poespoprodjo JR, Vemuri R, et al. Treatment-seeking behaviour and associated costs for malaria in Papua, Indonesia. Malar J. 2016;15:536.

Onyia VU, Ughasoro MD, Onwujekwe OE. The economic burden of malaria in pregnancy: a cross-sectional study. J Matern Fetal Neonatal Med. 2020;33:92–5.

Hailu A, Lindtjorn B, Deressa W, Gari T, Loha E, Robberstad B. Economic burden of malaria and predictors of cost variability to rural households in south-central Ethiopia. PLoS ONE. 2017;12: e0185315.

Xia S, Ma JX, Wang DQ, Li SZ, Rollinson D, Zhou SS, et al. Economic cost analysis of malaria case management at the household level during the malaria elimination phase in The People’s Republic of China. Infect Dis Poverty. 2016;5:50.

Botto-Menezes C, Bardaji A, Dos Santos CG, Fernandes S, Hanson K, Martinez-Espinosa FE, et al. Costs associated with malaria in pregnancy in the Brazilian Amazon, a low endemic area where Plasmodium vivax predominates. PLoS Negl Trop Dis. 2016;10: e0004494.

Rashed S, Johnson H, Dongier P, Moreau R, Lee C, Lambert J, et al. Economic impact of febrile morbidity and use of permethrin-impregnated bed nets in a malarious area I: study of demographics, morbidity, and household expenditures associated with febrile morbidity in the Republic of Benin. Am J Trop Med Hyg. 2000;62:173–80.

Botega LA, Andrade MV, Guedes GR. Brazilian hospitals’ performance: an assessment of the unified health system (SUS). Health Care Manag Sci. 2020;23:443–52.

Morel CM, Thang ND, Xa NX, le Hung X, le Thuan K, Van Ky P, et al. The economic burden of malaria on the household in south-central Vietnam. Malar J. 2008;7:166.

Tawiah T, Asante KP, Dwommoh RA, Kwarteng A, Gyaase S, Mahama E, et al. Economic costs of fever to households in the middle belt of Ghana. Malar J. 2016;15:68.

Tefera DR, Sinkie SO, Daka DW. Economic burden of malaria and associated factors among rural households in Chewaka District, Western Ethiopia. Clinicoecon Outcomes Res. 2020;12:141–52.

Deressa W, Hailemariam D, Ali A. Economic costs of epidemic malaria to households in rural Ethiopia. Trop Med Int Health. 2007;12:1148–56.

Ilunga-Ilunga F, Leveque A, Okenge Ngongo L, Tshimungu Kandolo F, Dramaix M. Costs of treatment of children affected by severe malaria in reference hospitals of Kinshasa, Democratic Republic of Congo. J Infect Dev Ctries. 2014;8:1574–83.

Uguru NP, Onwujekwe OE, Uzochukwu BS, Igiliegbe GC, Eze SB. Inequities in incidence, morbidity and expenditures on prevention and treatment of malaria in southeast Nigeria. BMC Int Health Hum Rights. 2009;9:21.

Chuma JM, Thiede M, Molyneux CS. Rethinking the economic costs of malaria at the household level: evidence from applying a new analytical framework in rural Kenya. Malar J. 2006;5:76.

Onwujekwe O, Hanson K, Uzochukwu B, Ichoku H, Ike E, Onwughalu B. Are malaria treatment expenditures catastrophic to different socio-economic and geographic groups and how do they cope with payment? A study in southeast Nigeria. Trop Med Int Health. 2010;15:18–25.

Ayieko P, Akumu AO, Griffiths UK, English M. The economic burden of inpatient paediatric care in Kenya: household and provider costs for treatment of pneumonia, malaria and meningitis. Cost Eff Resour Alloc. 2009;7:3.

Onwujekwe O, Uguru N, Etiaba E, Chikezie I, Uzochukwu B, Adjagba A. The economic burden of malaria on households and the health system in Enugu State southeast Nigeria. PLoS ONE. 2013;8: e78362.

Article   CAS   PubMed   PubMed Central   Google Scholar  

Attanayake N, Fox-Rushby J, Mills A. Household costs of “malaria” morbidity: a study in Matale district, Sri Lanka. Trop Med Int Health. 2000;5:595–606.

Dalaba MA, Welaga P, Oduro A, Danchaka LL, Matsubara C. Cost of malaria treatment and health seeking behaviour of children under-five years in the Upper West Region of Ghana. PLoS ONE. 2018;13: e0195533.

Gatton ML, Cho MN. Costs to the patient for seeking malaria care in Myanmar. Acta Trop. 2004;92:173–7.

Jackson S, Sleigh AC, Liu XL. Cost of malaria control in China: Henan’s consolidation programme from community and government perspectives. Bull World Health Organ. 2002;80:653–9.

PubMed   PubMed Central   Google Scholar  

Moreno-Gutierrez D, Rosas-Aguirre A, Llanos-Cuentas A, Bilcke J, Barboza JL, Hayette MP, et al. Economic costs analysis of uncomplicated malaria case management in the Peruvian Amazon. Malar J. 2020;19:161.

Sicuri E, Davy C, Marinelli M, Oa O, Ome M, Siba P, et al. The economic cost to households of childhood malaria in Papua New Guinea: a focus on intra-country variation. Health Policy Plan. 2012;27:339–47.

Yusuf WA, Yusuf SA, Oladunni OS. Financial burden of malaria treatment by households in Northern Nigeria. Afr J Biomed Res. 2019;22:11–8.

Mustafa MH, Babiker MA. Economic cost of malaria on households during a transmission season in Khartoum State, Sudan. East Mediterr Health J. 2007;13:1298–307.

Fernández García A, Collazo Herrera M, Mendes NP, Hossi JP. Costos directos sanitarios del paludismo en el Hospital Militar Regional de Uíge. Medisur. 2018;16:6–9.

Download references

Acknowledgements

The authors MVA, KN and GRG thanks to the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) for the Research Productivity Scholarships.

This work was supported, in whole or in part, by the Bill & Melinda Gates Foundation [INV003970] and the DECIT/Brazilian Ministry of Health/CNPq [#442842/2019-8]. Under the grant conditions of the Foundation, a Creative Commons Attribution 4.0 Generic License has already been assigned to the Author Accepted Manuscript version that might arise from this submission.

Author information

Authors and affiliations.

Centre of Regional Planning and Development (Cedeplar-UFMG), Universidade Federal de Minas Gerais, Belo Horizonte, Minas Gerais, Brazil

Mônica V. Andrade, Kenya Noronha, Bernardo P. C. Diniz, Gilvan Guedes, Lucas R. Carvalho, Valéria A. Silva, André S. Santos & Daniel N. Silva

Centre d’Estudis Demogràfics, CED, Universitat Autònoma B, 08193, Barcelona, Spain

Júlia A. Calazans

Department of Global Health and Population, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA

Marcia C. Castro

You can also search for this author in PubMed   Google Scholar

Contributions

MVA, KN, MCC, and ASS conceived the study. MVA and MCC acquired funding and provided coordination and supervision of the study. MVA, KN, BC, GG, LRC, VS, JC, DNS, and ADS conducted the bibliographic review. MVA, KN, JC, LRC, VS, BC, and DNS performed the screening of the papers. MVA, KN, JC, LRC, VS, BC, and DNS extracted the data of the selected studies. MVA, KN, BPCD, GG, MCC, and ASS wrote the first draft of the manuscript. All authors contributed to data analysis and manuscript editing. All authors read and approved the final manuscript.

Corresponding author

Correspondence to Marcia C. Castro .

Ethics declarations

Ethics approval and consent to participate, consent for publication, competing interests.

The authors declare that they have no competing interest.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1..

PECO search framework.

Additional file 2.

Descriptive system of cost components.

Additional file 3.

Items included in the quality assessment of the included articles.

Additional file 4.

Studies excluded after full-text review and reasons for exclusion.

Additional file 5.

List of included references.

Additional file 6.

Funding sources of studies included in the analysis.

Additional file 7.

Distribution of selected papers according to the type of stratification.

Additional file 8.

Quality assessment of the selected papers.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ . The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/ ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Cite this article.

Andrade, M.V., Noronha, K., Diniz, B.P.C. et al. The economic burden of malaria: a systematic review. Malar J 21 , 283 (2022). https://doi.org/10.1186/s12936-022-04303-6

Download citation

Received : 20 March 2022

Accepted : 25 September 2022

Published : 05 October 2022

DOI : https://doi.org/10.1186/s12936-022-04303-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

• Economic burden
• Cost analysis

Malaria Journal

ISSN: 1475-2875

• Submission enquiries: [email protected]

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• My Account Login
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Open access
• Published: 08 January 2024

Global evidence on the economic effects of disease suppression during COVID-19

• Jonathan T. Rothwell   ORCID: orcid.org/0000-0002-9251-0029 1 , 2 ,
• Alexandru Cojocaru 3 ,
• Rajesh Srinivasan 1 &
• Yeon Soo Kim   ORCID: orcid.org/0000-0002-7757-7858 3  

Humanities and Social Sciences Communications volume  11 , Article number:  78 ( 2024 ) Cite this article

1231 Accesses

25 Altmetric

Metrics details

• Development studies

Governments around the world attempted to suppress the spread of COVID-19 using restrictions on social and economic activity. This study presents the first global analysis of job and income losses associated with those restrictions, using Gallup World Poll data from 321,000 randomly selected adults in 117 countries from July 2020 to March 2021. Nearly half of the world’s adult population lost income because of COVID-19, according to our estimates, and this outcome and related measures of economic harm—such as income loss—are strongly associated with lower subjective well-being, financial hardship, and self-reported loss of subjective well-being. Our primary analysis uses a multilevel model with country and month-year levels, so we can simultaneously test for significant associations between both individual demographic predictors of harm and time-varying country-level predictors. We find that an increase of one-standard deviation in policy stringency, averaged up to the time of the survey date, predicts a 0.37 std increase in an index of economic harm (95% CI 0.24–0.51) and a 14.2 percentage point (95% CI 8.3–20.1 ppt) increase in the share of workers experiencing job loss. Similar effect sizes are found comparing stringency levels between top and bottom-quintile countries. Workers with lower-socioeconomic status—measured by within-country income rank or education—were much more likely to report harm linked to the pandemic than those with tertiary education or relatively high incomes. The gradient between harm and stringency is much steeper for workers at the bottom quintiles of the household income distribution than it is for those at the top, which we show with interaction models. Socioeconomic status is unrelated to harm where stringency is low, but highly and negatively associated with harm where it is high. Our detailed policy analysis reveals that school closings, stay-at-home orders, and other economic restrictions were strongly associated with economic harm, but other non-pharmaceutical interventions—such as contact tracing, mass testing, and protections for the elderly were not.

Similar content being viewed by others

Effects of government policies on the spread of COVID-19 worldwide

Hye Won Chung, Catherine Apio, … Taesung Park

COVID-19 restrictions and age-specific mental health—U.S. probability-based panel evidence

Elvira Sojli, Wing Wah Tham, … Michael McAleer

A global analysis of the effectiveness of policy responses to COVID-19

Kwadwo Agyapon-Ntra & Patrick E. McSharry

Introduction

In 2020, governments around the world started putting in place extraordinary policies to mitigate the spread of the coronavirus, including stay-at-home orders, restrictions on travel and gatherings, and closures of schools and workplaces. These policies have been found to be associated with reduced economic activity, in the form of visits to workplaces, parks, restaurants, and non-grocery retail establishments, both in global analyses (Hale et al. 2021 ), and based on detailed evidence from single countries or a subset of countries (Deb et al. 2020 ; Boone and Ladreit 2021 ; Lozano Rojas et al. 2020 ; Aminjonov et al. 2021 ; Carvalho et al. 2021 ; Coibion et al. 2020 ; Gathergood et al. 2021 , including illegal economic activity (Nivette et al. 2021 )). Using U.S. data from early in the pandemic, other scholars have argued that widespread economic disruptions would have happened in the absence of restrictions (Goolsbee and Syverson 2020 ; Forsythe et al. 2020 ; Gupta et al. 2020 ).

Epidemiological theory and empirical evidence suggest that these policies likely reduced the number of deaths (Liu et al. 2021 ; Chernozhukov et al. 2021 ; Violato et al. 2021 ; Qi et al. 2022 ), although given the methodological challenges, the evidence on the causal links between mobility restrictions and COVID-19 mortality is not entirely consistent (Berry et al. 2021 ; Herby et al. 2022 ; Spiegel and Tookes 2022 ). Similarly, public health policies that do not restrict economic activity—such as contact tracing (Fetzer and Graeber 2021 ) and surgical mask use (Abaluck et al. 2022 )—have been found to reduce infections.

Regardless of the causes, pandemic-era economic distress has been widely documented. Global output contracted by 3.4% in 2020, with output contractions observed in 95% of countries, a scale that rivals that of the Great Depression (World Bank 2022 ), and global poverty increased (Mahler et al. 2021 ; Kim et al. 2021 ). Furthermore, low-income countries faced widescale income losses (Egger et al. 2021 ; Josephson et al. 2021 ). Within countries, the economic effects of the pandemic have been worse for households with relatively low socioeconomic status, as measured by income rank or educational attainment (Rothwell and Smith 2021 ; Narayan et al. 2022 ; World Bank 2022 ; Bundervoet et al. 2021 ; Kugler et al. 2021 ), which is consistent with past pandemics (Furceri et al. 2022 ).

This paper contributes to the literature by providing the most comprehensive analysis to-date on several research questions related to the pandemic: How prevalent was the economic harm related to the pandemic, and how did that harm relate to subjective well-being and financial security? What is the association between economic harm and the stringency of regulations on economic and social activity? How did harm vary by socioeconomic status within and across countries? How do estimated effects of stringency compare to alternative non-pharmaceutical interventions in terms of job loss and similar outcomes?

The analysis relies heavily on the Gallup World Poll, which used random samples of individuals in 117 countries representing nearly three-quarters of the global population. From July 2020 to March 2021, the survey collected detailed demographic data on income and education, subjective well-being measures, and information on several economic outcomes in which respondents were explicitly asked if they were caused by the pandemic. The resulting database provides the only harmonized quasi-global database available to study individual and country-level employment and income outcomes. By directly measuring forms of economic harm—rather than proxy measures such as mobility—these data provide insights that would otherwise be lost to history. Data on policy interventions, COVID deaths, and other contextual data were matched to individual responses using cumulative-to-date means, such that a respondent’s self-reported degree of harm from COVID-19 could be compared to the policy regime used up to match the month of the interview. The primary analysis uses multilevel mixed modeling to simultaneously estimate associations with individual demographic characteristics—including socioeconomic status—and time-varying country-level variables, aggregated to month-year units. The database needed to replicate our analysis will be released upon publication, allowing other scholars to use the data for their own novel analyses.

The hypotheses tested in this paper require data on three main components of our empirical models: (i) measures of economic harm or welfare impact; (ii) measures of the stringency of economic restrictions imposed by governments in the wake of the COVID-19 pandemic, and (iii) measures of the disease burden of COVID-19. These are described in turn in this section. Summary statistics from the country-level and individual data are available in Supplementary Table 1 . The analysis was conducted using Stata 17.0.

Economic harm measures

The main source of data supporting the analysis in this paper comes from surveys fielded by the Gallup World Poll between July 9, 2020, and March 3, 2021, with 321,386 observations of people aged 15 and older in 117 countries/territories. Footnote 1 The survey included demographic information as well as items related to health and well-being that were designed to be nationally representative for each country in the sample. Footnote 2 The relevant ethics statement is provided below.

The main focus of this analysis is on five survey items that broadly measure social or economic harm from COVID-19. The first item, fielded to all survey respondents, solicits an answer to the question, “In general, to what extent has your own life been affected by the coronavirus situation?” We recode responses as a binary variable, which takes a value of one if the response is “a lot,” and zero if respondents reply “some” or “not at all.”

The second item, applicable only to people working at the start of the pandemic, solicits whether respondents have experienced each of the following as a result of the coronavirus situation?

Temporarily stopped working at your job or business

Lost your job or business

Worked less hours at your job or business

Received LESS money than usual from your employer or business

Respondents are instructed to answer “Yes” or “No”, or “Does not apply” if they did not have a job leading up to the pandemic. The World Poll includes a large number of other respondent-level variables, which we only briefly describe below in context. On average, 42% of adults responded that they were affected a lot; 24% reported permanently losing their job; 48% reported a temporary job loss, and 47% reported lost income (see Supplementary Table 9 for full text).

The advantage of the above survey items for the purpose of assessing the welfare impacts of the COVID-19 pandemic, vis-à-vis more traditional measures of economic changes, such as employment status or income, stems from the fact that the respondent is asked to attribute the severity of the overall impact, or the different aspects of job and income losses to the pandemic in a causal sense. This is important because many factors other than COVID-19 could cause people to lose their job, leave the labor force or experience emotional stress. Thus, while the analysis in this paper relies on cross-sectional variation, the framing of the key questions related to impacts help at least partially guard against common omitted variable bias concerns in such settings.

A second advantage of these items is that respondents are well-placed to know if an economic change in their life was caused by the pandemic. The event itself was highly salient and often highly disruptive to daily life, with clear time boundaries, tied to events like international and national emergency declarations and stay-at-home orders. In many cases, employers may have specifically told employees that the cause of their layoff was the pandemic, but even in the absence of that messaging, respondents would be well aware of the timing of their job loss and the circumstances leading up to it, which may include the business being shut down or customers canceling contracts or no longer showing up.

Stringency of economic restrictions measures

The analysis relates the above measures of economic harm to the stringency of restrictions on economic activity imposed by governments. We measure stringency of lockdowns by using data from the Oxford COVID-19 Government Response Tracker (Hale et al. 2021 ). The database evaluates national and sub-national government policies along various dimensions.

Data are coded on an ordinal scale, such that values are increasing with stringency. For business closures, 0 means no measures, 1 means recommended closing or recommended work from home, 2 requires the closing of some sectors, and 3 requires the closing of all but essential workplaces, such as healthcare offices and grocery stores. The data are collected for every day since the start of 2020, which facilitates our analysis. Since we are studying the cumulative economic effects up until the time of the survey, we want a measure of the cumulative lockdown up to that point, which we measure as the average stringency up until the month of the survey. Hale et al. ( 2021 ) constructed a “stringency index” that is the mean value of the stringency of the 8 containment policies and one health-related policy. The latter measures the degree to which public officials urged caution through coordinated efforts to promote social distancing and related behavioral changes across traditional and social media (see Supplementary Table 4 for full description). For the purposes of our analysis, we restrict the sample to data collected through March of 2021, to coincide with our sample collection period. We standardize the stringency index and its components to have mean 0 and a standard deviation of one across all 184 countries in the database.

In our decomposition analysis, we focus on these containment measures, as well as “health systems policies” which include regulations of facial coverings, contact tracing, testing, vaccination policy, and protections of the elderly. We omitted investment related policies because they are highly dependent on country budgets and GDP.

In most cases, each country has a single daily measure for each indicator. Sub-national data is available for only Brazil, Canada, the United Kingdom, and the United States. For these countries, we obtain population data from national statistical offices for the sub-regions and use these as weights, so that the national value is a population-weighted average of the subregional policies. Footnote 3

It should be noted that stringency measures, such as those related to social distancing and restrictions to physical mobility, need not result in economic harm if the degree of compliance is low, either because people are unable or do not want to comply with the measures and the authorities lack the capacity to enforce them. Thus, it is important to ascertain that stringency measures are actually binding and do, in fact, lead to reduced mobility and economic activity. To verify this, we rely on several sources of data that speak to physical mobility and social distancing dynamics (see Supplementary Materials).

One direct way of looking at restrictions to mobility is with the aid of data from Google Community Mobility Reports. Using mobile phone location software, these data show the percentage change in visits to various places from a pre-COVID baseline (January 3 to February 6, 2020). We focus only on visits to retail and restaurants, described by Google LLC ( 2021 ) as: “places like restaurants, cafes, shopping centers, theme parks, museums, libraries, and movie theaters.” Roughly half of the adult population in the sample reported direct contact with non-household members, and visits to restaurants and similar places were down 25% on the average day through the end of 2020.

One additional proxy measure for the degree of social distancing that is directly relevant to COVID-19 transmission is related to changes in the transmission of a parallel respiratory virus that was common before the pandemic. A large drop in the transmission of this parallel virus would suggest major behavioral changes relevant to disease transmission, whereas the absence of change in its transmission would suggest limited behavioral changes. Influenza is close to ideal in providing this analytic opportunity. The most significant problem is that flu cases are measured only based on testing, and flu testing conditional on symptoms—like COVID testing—is likely to vary by country. At the same time, by comparing pre-COVID flu rates to COVID-era flu rates, we control for unchanging country-level testing infrastructure and practices. We, therefore, believe these data provide a valid measure of changes in social distancing that include both policy-induced and non-policy-induced behaviors. These data are from the World Health Organization’s FluNet and include total positive influenza cases per week by country for each year from 2016 to the 45th week of 2021. The use of weekly data allows us to adjust for seasonal effects, which vary by hemisphere and countries within hemispheres. We are interested in the percentage change in weekly cases during flu season before and after the pandemic, ending the analysis on the 12th week of 2021 to coincide with the World Poll data collection period. To identify the flu season for each country, we calculate the weekly share of cases from 2016 to 2019 and classify any week with at least 1% of annual cases as being part of flu season. For the United States, this would include weeks 1–16 and weeks 47 through 52 of every year. For Australia, in the Southern Hemisphere, it would include weeks 20–41. Unfortunately, FluNet data are far from being comprehensive and many countries are either entirely missing or only report a few weeks out of the year. We require 90% reporting coverage during flu-season weeks before and after the pandemic. We find that flu cases in the 2020–2021 flu season were just 18% of the mean number of flu cases measured from 2016 to 2019 flu season in 74 countries.

As part of our robustness checks, we analyze the relationship between stringency and changes in flu rates at the country-month level. For this analysis, we calculate positive flu cases in the current year (2020) relative to the previous year (2019) and the year before that (2018) and take the average of these two rates before aggregating this average to months. This gives us a measure of flu rates relative to previous years that varies by month and country.

We include an additional measure of subjective social distancing. In partnership with Facebook, the University of Maryland fielded a large-scale global daily survey of Facebook users (the COVID-19 World Symptom Survey Data), reweighted to be representative of the national population (Barkay et al. 2020 ). Using the University of Maryland API (Fan et al. 2020 ), we were able to get weighted data for the percentage of respondents who have reported having had direct contact (longer than 1 min) with people not staying with them within the past 24 h. Using data aggregated across 103 countries in 2020, 46% of respondents report direct contact with a standard deviation of 10%.

Disease burden measures

The disease burden is measured in terms of deaths per capita, which is preferable to the number of COVID-19 cases. We do not claim that every national health system is equally likely to capture and correctly identify every COVID-19 death, but nearly every country has formal systems to record the causes of death. By contrast, the probability of seeking testing conditional on the experience of symptoms is highly contingent on factors that vary widely by country, such as cost, guidelines on testing priorities, and the availability of tests. Asymptomatic testing, moreover, also varies widely by country. In short, data on COVID-19 cases per capita are very noisy measures of the disease burden relative to deaths per capita.

To further guard against measurement error—and potential bias stemming from lack of reporting—we include model-based estimates of deaths from COVID-19 in our analysis from the University of Washington’s Institute for Health Metrics and Evaluation (IHME 2021 ). That analysis uses actual all-cause mortality data for 56 countries, subtracts out known increases in deaths, and determines estimates of actual COVID deaths. The research team then models the ratio between reported deaths and actual deaths for every country to arrive at a measure of total COVID deaths. We regard these as credible alternative measures of disease burden, as argued by Wang et al. ( 2022 ). IHME is the source for both the official and estimate deaths used in our models.

Details of analysis

Our analysis tests models at the individual and country levels. For individual analysis, we study (1) how experiences of economic harm relate to subjective-well-being outcomes; (2) which demographic variables predict a greater risk of harm; (3) whether the relationship between low-socioeconomic status and harm is higher or lower in countries with high-stringency versus low-stringency.

Predicting well-being

The initial findings test whether our measures of economic harm predict subjective well-being at the individual level. We run linear OLS regression models of the following form, where W is the outcome of interest, θ is a vector of individual i demographic variables, C is an indicator for the country of residence (a country fixed effect) c , and the errors are clustered at the country level to account for within-country-level measurement error. Since respondents answer the survey at different times t , time periods are measured in months, and months fixed effects are included. In this setup, there are no country-level regressors, other than the fixed effect.

Predicting harm in a multilevel framework

The primary analysis combines country-level and individual-level data and therefore uses a multilevel model. We estimate the model using the mixed program in Stata v17, allowing for one unique variance parameter per random effect and maximum likelihood estimation. The variance-covariance matrix is calculated to allow intragroup correlation at the country level, where the data are structured by countries and by month-years, allowing random intercepts that vary by time and country ( \(\beta _{0,c,t}\) in Eq. 2 ). The dependent variable is economic harm H measured at the individual level i in country c during time t (Eq. 2 ). We include country-level time-varying variables, captured in X in (Eq. 4 ). These are cumulative-to-date measures of COVID-19 restrictions, economic support policies, and COVID-19 deaths per capita.

When written out formally, Eq. 2 captures the first-level individual specification. Harm varies by individual, country, and time period and so do the errors, intercepts, and predictors. Equation 3 represents level 2 (the time period). The mean outcome for individuals is modeled as a function of the time period and a random component. The time period mean varies by country, since countries faced different disease and economic trajectories during the pandemic. Level 3 is modeled in Eq. 4 . The mean outcome by country and time period is a function of the mean across all groups, a country and time-varying component, and a random country-varying component. Equation 5 combines the multiple levels into our preferred model. The fixed components are the first three terms, whereas the random components are the final three. The estimation procedure in Stata uses maximum likelihood. This exposition follows the discussion from Tascam Giorgio et al. ( 2009 ) and Oshchepkov and Shirokanova ( 2022 ).

Country-level variables are cumulative-to-date time-varying for several reasons. A single cumulative measure would include information that occurred after measurement for survey respondents who interviewed in early waves, and this would introduce unnecessary error into the model. A time-varying metric that is not cumulative-to-date would be a problem, because the outcome variable measures cumulative harm-to-date, as in “have you ever lost your job as a result of the coronavirus situation?” Since a measure that ignores the past can hardly be expected to predict the past, this approach would also introduce error.

The individual-level measures are demographic indicators for age, gender, foreign-born status, education, income, and urbanicity. We also include an indicator for whether the respondent is out of the labor force at the time of the survey. Since most of our measures of harm involve job loss, they are not usually applicable to those who were out of the labor force, whose lives were less likely to have been affected. We omit current unemployment status because many people recently harmed through job loss or one of the other measures may still be unemployed at the time of the survey.

The results from our baseline model can be used to assess the appropriateness of our multilevel modeling strategy. Both of the random intercepts are significant at 95% confidence levels (see Table 1 ). The country level explains approximately 8.8% of the total variation, whereas the time-period effect is just 0.8%. The intraclass correlations are 8% at the country level and 8.8% combined and both significant, confirming our assumption that individual-level errors are correlated with higher-level errors. The model’s results are reported in Table 1 using the harm index and job loss as the predicted outcomes; results predicting income loss, whether the respondent was affected a lot by the pandemic, temporary job loss, and loss of hours are reported in the Supplemental Materials ( ST5 , ST6 , ST7 , and ST8) .

We also report the results of models that interact household income quintile with stringency (Fig. 2 ). These models are identical to our primary specification except they include additional interaction terms along the lines of

where \(\beta _2\) identifies the slope of harm for an income group as stringency increases. Figure 2 plots the mean predicted values from these models for each quintile after collapsing the data to centiles of stringency. Since we are interested in how effects vary by socioeconomic status, we drop educational attainment levels from the model (which is included in our benchmark model), so that the income effects are not conditional on education level. Standard errors are estimated in the plots by regressing the group-specific effect sizes on the stringency centile rank. These approximate the standard errors from the larger database.

To test the differences between policies, we replicate the analysis from Eq. 5 and Table 1 using our preferred multilevel model and report the coefficients and standard errors (Fig. 3 ).

Summary data

Across the 117 countries included in the Gallup World Poll from July 2020 to March 2021, 42% of adults said they were affected a lot by the pandemic, weighting responses by population. Among those who were in the labor force leading up to the pandemic, 51% were laid off temporarily, 50% lost hours, 49% lost income, and 27% lost their job (see ST3).

These outcomes varied widely by country and continental sub-region. In Eastern Asia, Western Europe, and Northern Europe, only 4.3%, 6.4%, and 6.8% permanently lost their job, respectively, but in Southern and South-eastern Asia it was 49.0% and 44.1%, respectively. In Northern America and Western Asia, 50.1% and 57.4% said their lives were affected a lot. In Western Europe, this was just 29.5%. Meanwhile, cumulative deaths per capita were much higher in Europe and North America relative to Africa and South Asia (ST2), suggesting that the disease burden is unlikely to explain these findings.

A general pattern, found in the data, is that low-income countries experienced a relatively low disease burden from COVID-19 but a high economic burden. This mismatch between the health burden of the pandemic and its social burden suggests an important role for policy. GDP per capita measured in 2019 PPP-adjusted dollars is negatively correlated with the share of population reporting a COVID-related job loss (–0.74), but positively correlated with deaths per capita (0.35) and estimated deaths per capita (0.18), using data from (Wang et al. 2022 ). GDP per capita is also highly correlated with an economic support index (0.55). Yet, GDP per capita has no correlation with the stringency index for disease suppression policies (0.02), even though stringency predicts greater job loss (0.19) and economic support predicts less job loss (–0.40).

Importantly, these relationships would be missed using Google mobility as economic indicators. Visits to restaurants were negatively correlated with GDP per capita (–0.20) and positively correlated with job loss (0.15). In other words, Google data provides the opposite signal as survey-based data. Other Google mobility measures showed the same pattern, including use of transportation and visits to work. It seems that in rich countries, people were able to withdraw from discretionary in-person economic activity—including work—while preserving their jobs and income to a much greater extent than in low-income countries, likely because of the development of digital service markets.

Validating a novel measure of economic harm

Before describing the primary results, we establish grounds for accepting the validity of our key measures. Further information is provided in the Methods section and Supplementary Text. First, we create a “harm index” as the standardized individual-level mean of responses to five survey items about how respondents’ lives have been affected by the coronavirus situation. They are as follows: whether their lives have been affected a lot, whether they lost their job or business temporarily or permanently (two distinct items), whether they worked fewer hours, or whether they received less money. Using the global sample, each item is standardized to have a mean of zero and a standard deviation of one.

The results show that the economic harm index—and its component parts—strongly predict four measures of subjective well-being, covering (1) changes in subjective living standards, (2) current life evaluation, (3) experiences of worry, and (4) lack of money for food (wording is provided in Supplementary Table 3 ). Essentially, we regress these outcomes on the harm index, controlling for respondent demographics and country fixed effects. Each component of harm is strongly and significantly associated with lower well-being using all four measures. Moreover, when each component of harm is included in the same model, all of them are significant, except for the loss of hours, which is highly correlated with the others. Since each variable adds information, we consider the harm index to be the most comprehensive measure of several dimensions: job loss, income loss, and subjective disruption to life (Fig. 1 ).

Data are from the Gallup World Poll. Analysis includes approximately 222,000 respondents when restricted to the working population, which is used for the economic outcome measures. All models include demographic controls and country effects. The red diamonds show results when all variables, except the harm index, are used in the same model.

We considered several alternative measures of our harm index, including a factor analysis-based index, one that only uses the four labor market items (excluding whether the respondent was affected more generally), and one that combines temporary and permanent layoffs. Based on empirical investigations discussed in the Supplemental Text and summarized in Supplementary Table 10 , our preferred measure is the one used here, though the results reported in Table 1a —testing the association with stringency—are almost exactly the same, when we replace the harm index with these alternatives. Footnote 4

Next, we check the reliability and validity of World Poll data on employment losses against alternative sources. World Poll data on the job loss rate are broadly aligned with administrative data on changes in the official unemployment rate (correlation is 0.52 in 52 countries). Yet, in addition to broader coverage, the World Poll measures are superior in two respects: harmonization in measurement and a causal link with COVID-19. Note, we are not suggesting that this fact implies that our estimators are causal. The point is that respondents are asked to report on an outcome that they believe is causally linked to the pandemic. This is a different question about whether they believe it is causally linked to stringent policies, which is a much harder question. Nonetheless, this is a large conceptual advance over asking whether someone is employed or not and assuming any change from pre- to post-pandemic is caused by the pandemic.

Consider that in normal times, except in rare cases, “unemployment” requires that adults are out of work but seeking and able to work. If the latter two conditions are unmet, the person is considered out of the labor force, but not unemployed. COVID-19, however, resulted in many people losing their job but temporarily halting efforts to find a new one—for various reasons. Statistical offices around the world took different non-harmonized approaches to classifying such persons, resulting in different methodological bases for documenting unemployment rate levels and changes. Moreover, COVID-19 was not the only causal factor affecting social and economic conditions around the world, so the World Poll data also improve conceptual validity by asking respondents to attribute their economic harm to the pandemic and allowing them to express it along several dimensions (see Supplementary Text for further discussion of these issues).

Finally, we show that our primary policy measure also meets basic validity criteria, as discussed in Hale et al. ( 2021 ). Stringency is weakly and positively related to COVID death rates but more closely related to measures of social distancing, particularly those involving declines in visits to restaurants and small businesses (Supplementary Text and Supplementary Fig. 1 ). We examine two additional and related outcomes in the supplement. In more stringent countries, self-reported social contact (available from a non-representative alternative survey covering a smaller number of countries) tends to be lower and reported cases of seasonal flu fell further from baseline season-adjusted trends—for the subset of countries with high-quality flu data. This provides further evidence that the behaviors associated with respiratory disease transmission (e.g., social contact) fell further where disease-suppression policies were strongest, but flu case data are likely more informative than COVID-19 case count data, since flu surveillance systems were well-established before 2020, and COVID surveillance relied on novel tests that were neither available uniformly globally nor across regions within countries. Taken together, this evidence suggests a plausible link between stringency and economic outcomes.

Stringency measures and economic harm: main results

We now proceed with the main research question—whether more stringent restrictions are associated with a greater degree of economic harm, and what demographic factors are most strongly associated with harm. The stringency of mitigation policies is measured by the COVID-19 Government Response Tracker (Hale et al. 2021 ). Harm is aggregated from the World Poll microdata, using sample weights to ensure national representation. The analysis regresses harm on stringency (see Methods) and a vector of demographic variables in a multilevel model, with country and month-year levels.

Column (1) of Table 1a reports the regression-adjusted correlation between policy stringency and an index of economic harm, with no individual-level controls. A one standard deviation increase in the stringency index predicts a 0.31 increase in harm (0.40 for a std deviation unit of harm). Colum (2) adds individual-level demographic controls. The coefficient on harm falls—in absolute value terms—only slightly to 0.29 increase in harm (0.37 std dev). This model includes cumulative-to-date measures of reported COVID-19 deaths per capita and an index of economic support, as well as a rich list of individual-level controls, and country and month effects.

The economic support index is measured by the Oxford database (Hale et al. 2021 ) and captures the record of the government providing direct cash payments to people who lose their jobs or cannot work, including payments to firms that are linked to payroll/salaries, as well as the record of the government freezing financial obligations for households (e.g., stopping loan repayments, preventing services like water from stopping or banning evictions). Models 1–3 suggest that the degree of economic support is not correlated with the extent of economic harm, but a significant and negative effect is found after adjusting for the observed economic behavior of the population (using Google mobility) and using a measure of COVID deaths per capita that considers measurement error in reporting (columns 5 and 6 of Table 1a ). These latter results more closely approximate the country-level bivariate correlation between harm—aggregated using all observations—and economic support averaged through 2020, which is negative ( r  = −0.32).

In our conceptual model, stringency may be confounded with behavioral changes—such as voluntary social distancing—that would have happened even in the absence of government regulations. To account for this, in columns/models 3, 5, and 6, we control for a cumulative-to-date measure of visits to restaurants, cafes, and discretionary (non-grocery) shopping, using cell-phone-based data from Google Mobility. Conditional on government policies, visits to restaurants predict greater harm in model 3, but there is no significant relationship when using the error-corrected measure of deaths.

As another robustness check, in columns 3–6, we replace reported deaths per capita with a model-based measure of actual deaths, based on seroprevalence rates and other observable factors. These estimates are generated in (IHME 2021 ) as discussed in (Wang et al. 2022 ). Using either measure, the correlation between COVID deaths per capita and economic harm does not reach significance at 95% confidence levels.

Finally, column six drops the continuous measure of stringency in favor of binary measures of stringency set to equal one for each quintile of severity. The most stringent quintile is the omitted reference group. This setup accounts for potential non-linear effects of stringency. The quintiles are all negative, significant, and decreasing in a roughly linear pattern, such that lower levels of stringency predict less harm at each point in the distribution, though not entirely to the same extent. The coefficient on the first quintile is −0.30, which is very close to the corresponding coefficient in column 5 (−0.31), which uses the continuous stringency measure in an otherwise identical model. Thus, comparing the top-to-bottom-quintile of stringency yields a result that is well-approximated by a unit of the stringency index. The marginal effect sizes seen from comparing one quintile to the next range from −0.11 (comparing the fifth quintile to the fourth or the third to the second) to −0.05 (comparing the fourth to the third or second to the first).

To test whether our results are sensitive to the use of our index—and the assumptions underlying it, we run the same six models using permanent job loss (whether the respondent lost his or her job as a result of the pandemic) as the dependent variable (Table 1b ). Coefficients on stringency range from 14.2 to 15.9 ppts (with a margin of error of approximately 5.9 at 95% CI). The job loss rate has a standard deviation of 0.45 (see ST1). Converting the effect size to standardized units yields values ranging from 0.32 to 0.35 ppt (MOE of 0.13 at 95% CI), which are slightly smaller than those found for the harm index: 0.37–0.41 (MOE of 0.14 at 95% CI).

Relative to the most stringent quintile, adults in the least stringent countries were 14 ppt less likely to have experienced job loss, which is slightly less in absolute magnitude than the comparable linear estimate (16 ppt in column 5 of Table 1b ). The marginal effects on job loss rates of a one-unit change in the quintile range from 1.2 to 6.5 ppt. Economic support is negatively and significantly related to job loss, but we cannot reject the null hypothesis that the number of deaths per capita has no effect on job loss, and visits to restaurants predict slightly more job loss, surprisingly.

In the supplemental materials, we show similar results using income loss (ST5), whether the respondent was affected a lot (ST6), temporary job loss (ST7), and loss of hours (ST8) as the dependent variables. Stringency is strongly and positively related to each outcome. Economic support predicts less adverse outcomes with respect to loss of hours, temporary layoff, but not whether the respondent was affected a lot. The results of economic support were mixed for income loss, showing some evidence that these policies may have mitigated income loss.

These models also allow us to see which demographic variables are most closely related to harm, and to test the relationship between socioeconomic status and harm. The ratio of coefficients to standard errors (the t-statistic in OLS models and a z-statistic in random effects models) provides a valid measure of variable importance, as pointed out by Bring ( 1996 ). Columns 2 of Table 1a, b are our preferred models, as they allow government restrictions on economic activity to affect visits to restaurants and use reported COVID deaths.

By variable importance, income status was more closely linked to harm than any other demographic variable considered in our model, and lower-income predicted more harm, consistent with the literature. Moreover, even with income in the model, higher educational attainment is strongly associated with less harm. Socioeconomic status—measured through income or education—is more predictive than urbanicity, gender, foreign-born status, age, child-rearing status, or marital status. These results are consistent with the findings of several earlier studies that similarly find greater job losses among the more vulnerable population groups (Bundervoet et al. 2021 ; Kugler et al. 2021 ; Narayan et al. 2022 ; World Bank 2022 ; Rothwell and Smith 2021 ), but confirm them across a much wider and more comprehensive number of countries during the same time period.

The z-stat for those in the second-lowest quintile is 14.1, and it is 14.0 for those at the bottom, with coefficients of 16 and 20 ppt, respectively. These are the two largest z-statistics in absolute value terms. Workers in the bottom-quintile experienced 0.26 standard deviations of additional harm relative to those in the top quintile. Workers with an elementary education also saw a large increase in harm (9.6 ppt) compared to those with a tertiary (or college) education. Women did not experience more or less harm than men, but women with children under 15 experienced less harm, as did married couples or those living as domestic partners, relative to those living alone or in other arrangements. Young adults aged 30 to 39 experienced more harm than any other age group. By urbanicity, residents of cities saw the most harm, whereas workers in rural areas experienced the least harm. Foreign-born residents experienced significantly more harm than those born domestically. People out of the labor force at the time of the survey—and possibly throughout the pandemic—reported less harm, likely because they had less to lose.

Looking at job loss (Table 1b ) and other outcomes (ST5-ST8), the patterns are broadly similar. The largest estimated effect (16.9 ppt) and largest z-statistic (16.9) is for those at the bottom quintile of the household earnings distribution. The next largest effect is for those in the second-lowest quintile (12 ppt; 13.9 z-stat), followed by those with elementary education (10 ppt; 12.7 z-stat). There are no gender differences in job loss risk, and workers who are married or living with a domestic partner experienced less risk. Again, young adults aged 30 to 39 (5.2 ppt; 4.1 z-stat).

From the perspective of variable importance, the stringency index is less important than household income but more important than age, gender, and some measures of urbanicity in predicting harm (5.3 z-stat). It is comparable to secondary education (6.6 z-stat) and foreign-born status (5.7) In models predicting job loss, stringency is more important than foreign-born status and urbanicity, but less important than education or income (4.8 z-stat).

In the supplemental text, we discuss an out-of-sample test of the relationships between stringency and loss of income, using alternative U.S.-based data sources organized at the state level. Using a linear OLS model, we find that cumulative stringency predicts 0.6 standard deviations of additional COVID-related job loss (3 ppt) across U.S. states, controlling for median household income, COVID deaths per capita, and the percent of households who telework. The results are even stronger using pre-COVID party control as an instrumental variable in a two-stage least squares model. While party control is strongly related to policy, it is unclear if it is truly exogenous to loss of income from COVID-19 through channels other than COVID-related policies (ST11). We regard these results as supportive but still quite limited in establishing a causal relationship.

Socioeconomic status and heterogenous effects of stringency

The previous discussion considered the average country-level effects of policy stringency on economic harm. Here, we consider that public health policies, even when they are implemented uniformly at the national level, may not affect all households and individuals in the same way. To do so, we add interaction effects to our baseline multilevel models, multiplying stringency with binary variables for each income quintile. Using the results of this model, we forecast the harm index and job loss separately for each income group (see methods).

If lower-income households were more likely to be affected by restrictions on economic and social activity, then we should find a steeper slope between harm and stringency for lower-income groups relative to higher-income groups. This is exactly what we find (Fig. 2 ). The slope on the stringency-bottom-income quintile coefficient is 0.12 ppt higher than the slope on stringency-top income for the harm index and job loss rate; it is 0.08 for whether the respondent was affected a lot and 0.04 for temporary layoffs. Except for temporary layoffs, the results are significant at 99% confidence levels.

Plots model-predicted outcome by income group, where outcome is measured as the Harm index ( A ); whether the respondent experienced permanent job loss ( B ); whether respondent is affected a lot by COVID ( C ); whether respondent was temporarily laid off ( D ). Each model is a weighted mixed multilevel linear regression with country and month-year levels and interactions between cumulative-to-date stringency and within-country household income quintiles. Other control variables include whether the respondent was out of the labor force at time of survey, age group, gender, foreign-born status, marital status, the presence of children, and a category for level of urbanicity. Sample size is 269,725 observations in 117 countries. 95% confidence intervals are shaded around the prediction line. Point-estimates are shown as hollow diamonds or circles for top and bottom-income quintiles, respectively.

In the least restrictive policy regimes by centile rank, there is little or no difference in outcomes between the highest and lowest-income groups. For example, using the job loss rate, the gap is negative (6.5% for highest versus 5.2% for lowest) for the bottom centile of stringency, but it expands rapidly as stringency increases. In the top centile of stringency, the gap is very large (18.8% for highest-income group versus 46.9% for the lowest), with small error bars. Thus, this is strong evidence that policies meant to suppress the spread of the coronavirus were associated with a widening of economic inequality between income groups.

Alternative policy responses and economic harm

We consider that restricting social and economic activity was not the only tool available to public health officials. Widespread testing, meticulous contact tracing, social distancing focused on the elderly, travel restrictions, and use of facial coverings outside of one’s home are alternatives to universal social distancing and some do not necessarily limit economic behavior. The Oxford database tracks these and several other policies, and we tested these in our preferred multilevel model that controls for COVID-19 deaths and economic support.

In predicting the harm index (Fig. 3 , top panel), we find that some, but not all policy measures are positively associated with economic harm, and many policies have no significant relationship with harm. While no policies were negatively and significantly related to harm, vaccination policy, restrictions on gathering, public information, testing policy, contact tracing, and protection of the elderly were all insignificant, with the latter two having negative coefficients. In order of effect size, the overall index, school closings, internal travel restrictions, the closing of public transportation, stay-at-home-orders, canceling public events, mask orders, workplace closings, and international travel restrictions were each significantly associated with harm. The results and policy rankings are very similar using job loss as the dependent variable (Fig. 3 , bottom panel). The only substantive difference is that restrictions on gatherings are significantly associated with job loss but not the harm index.

Plots of standardized coefficients of mixed multilevel regression models. Dependent variables are the harm index ( A , at top) or the job loss rate ( B , at bottom). The figures plot the coefficients and 95% confidence intervals of 15 policy measures, each separately estimated, standardized, and measured as cumulative-to-date averages at the time the respondent was surveyed. The model includes controls for reported COVID-19 deaths per capita and an index of economic support, as well as individual demographic data with country and month-year fixed effects.

The restrictions to mobility and economic activity deployed by governments to contain the spread of coronavirus presumably saved many lives, by delaying transmission until effective treatments and vaccines countrhardship for many households around the world, and restrictions may have exacerbated the scale and severity of hardship. Our research uses the best available data to describe these outcomes, how they varied within and across countries, and to what extent they were linked to pandemic restrictions and other public health policies.

Soon after the start of the pandemic and throughout the first year, we document that many people around the world believed they were affected a lot and/or experienced job loss, income loss, or loss of hours, because of the pandemic. These outcomes were associated with negative levels and self-reported changes in subjective well-being and hardship. Moreover, this hardship was greater—around the world—for people with lower socioeconomic status, as measured by educational attainment or within-country income rank.

People were not asked whether or not their government’s response to the pandemic was harmful or helpful or how it affected them across various dimensions, and it would be difficult for any individual to know. We, therefore, use variation in the timing and severity of government responses across 117 countries to estimate the association between government policies and self-described economic harm at the individual level.

We find robust evidence that countries adopting more stringent disease suppression policies experience a higher rate of economic harm. This is found in models that simultaneously account for individual-level demographic variables, month-specific disease dynamics, and time-varying country measures of the disease burden and policy environment. These partially confirm the work of previous scholars conducting country-specific or regional analyses and add richer, more comprehensive evidence to support that work. Moreover, the associations between stringency and harm are stronger for individuals with lower levels of baseline socioeconomic status.

In addition, we find that stringent economic and social restrictions predict more severe harm globally, but other public health efforts—such as contact tracing, widespread vaccination, and special protections of the elderly did not predict economic harm.

A limitation of this analysis is that disease-suppression policies—like all government laws—are not randomly assigned, even though many of the policies studied were novel in their application as of 2020. We cannot rule out the possibility that our results are biased by omitted time-varying variables operating at the country level. Few variables successfully predict the disease burden of COVID, making instrumentation difficult, though we attempted such an analysis using U.S. states, as discussed in the supplemental materials. Another limitation—one shared by all data collection agencies worldwide—is that the pandemic forced Gallup’s partners to switch the mode of collection from face-to-face to phone-based collection in most countries during the early periods of the pandemic. The data were mode-adjusted, but there may be residual error from these adjustments affecting the results.

To be clear, these data do not allow for any clear cost-benefit calculation with respect to the pandemic-related policies. It is well beyond the scope of this research to attempt to estimate benefits and how they might vary by country or groups of people within countries. These data, however, could help provide benchmark estimates for costs, though we stress that our estimates should not be interpreted as causal effects, but rather associations between economic outcomes and policies.

A key question for future research is whether alternative policies could have been enacted—or could be enacted during future pandemics—that are able to save lives and mitigate disease without generating widespread economic harm, or disproportionate harm to the poorest households. These are difficult issues involving substantial uncertainty as well as value judgments that are sure to vary across individuals and countries.

Data availability

All replication code (Stata v17), microdata, and aggregate data needed to replicate the analysis are available here https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/8SET4W . Questions should be directed to the corresponding author.

While China was part of the World Poll, it is not included in the analysis, since these items were not fielded on its survey.

A weighting variable was calculated by Gallup statisticians in multiple stages for each respondent to allow researchers to generate nationally representative estimates for each country. Base weights were calculated based on the probability of selection and post-stratification weights were calculated to adjust for non-response bias by gender, age, and, in some countries, education or socioeconomic status.

Stringency measures are missing for several countries in our sample, including Guinea, North Macedonia, Montenegro, and Kosovo. We found no relationship between our harm index and whether stringency, deaths per capita, inequality, or flu growth variables were missing. The correlation between the harm index and whether these variables are missing is approximately zero.

Formally, we standardize the three outcome variables: our original harm index, the PCA-based harm index, and the labor market harm index (with 4 instead of 5 items) and run the models shown in Table 1 column 4. The coefficient on stringency is 0.38, 0.39, and 0.38, across the respective models. These results are shown in Supplementary Table 10, panel A.

Abaluck J, Kwong LH, Styczynski A, Haque A, Kabir MA, Bates-Jefferys E, Mobarak AM (2022) Impact of community masking on COVID-19: a cluster-randomized trial in Bangladesh. Science 375(6577):eabi9069

Article   CAS   PubMed   PubMed Central   Google Scholar  

Aminjonov U, Bargain O, Bernard T (2021) Gimme shelter. Social distancing and income support in times of pandemic. IZA DP No. 14967

Barkay N, Cobb C, Eilat R, Galili T, Haimovich D, LaRocca S, Morris K, Sarig T (2020) Weights and methodology brief for the COVID-19 symptom survey by University of Maryland and Carnegie Mellon University, in Partnership with Facebook Version 3–19. https://covidmap.umd.edu/document/css_methods_brief.pdf

Berry CR, Fowler A, Glazer T, Handel-Meyer S, MacMillen A (2021) Evaluating the effects of shelter-in-place policies during the COVID-19 pandemic. Proc Natl Acad Sci USA 118(15):e2019706118

Boone L, Ladreit C (2021) Fear of COVID and non-pharmaceutical interventions: an analysis of their economic impact among 29 advanced OECD countries COVID. Economics (73)

Bring J (1996) A geometric approach to compare variables in a regression model. Am Stat 50(1):57–62

Google Scholar  

Bundervoet T, Dávalos ME, Garcia N (2021) The short-term impacts of COVID-19 on households in developing countries: an overview based on a harmonized data set of high-frequency surveys. Policy Research Working Paper No. 9582, The World Bank, Washington, DC

Carvalho VM, Garcia JR, Hansen S, Ortiz Á, Rodrigo T, Rodríguez Mora JV, Ruiz P (2021) Tracking the COVID-19 crisis with high-resolution transaction data. R Soc Open Sci 8(8):210218

Article   ADS   PubMed   PubMed Central   Google Scholar  

Chernozhukov V, Kasahara H, Schrimpf P (2021) Causal impact of masks, policies, behavior on early COVID-19 pandemic in the US. J Econ Pandemic Econ 220(1):23–62. https://doi.org/10.1016/j.jeconom.2020.09.003

Article   MathSciNet   Google Scholar  

Coibion O, Gorodnichenko Y, Weber M (2020) The cost of the COVID-19 crisis: lockdowns, macroeconomic expectations, and consumer spending. NBER Working Paper. p. 27141

Deb P, Furceri D, Ostry JD, Tawk N (2020) The economic effects of COVID-19 containment measures. IMF Working Paper WP/20/158

Egger D, Miguel E, Warren SS, Shenoy A et al (2021) Falling living standards during the COVID-19 crisis: quantitative evidence from nine developing countries Sci Adv 7(6):eabe0997

Article   ADS   CAS   PubMed Central   Google Scholar  

Fan J, Li Y, Stewart K, Kommareddy AR, Garcia A, Ma J, Liu Z, O’Brien J, Bradford A, Deng X, Chiu S, Kreuter F, Barkay N, Bilinski A, Kim B, Galili T, Haimovich D, LaRocca S, Presser S, Morris K, Salomon JA, Stuart EA, Tibshirani R, Barash TA, Cobb C, Gros A, Isa A, Kaess A, Karim F, Eliat R, Kedosha OE, Matskel S, Melamed R, Patankar A, Rutenberg I, Salmona T, Vannette D (2020). COVID-19 World Symptom Survey Data API. https://covidmap.umd.edu/api.html

Fetzer T, Graeber T (2021) Measuring the scientific effectiveness of contact tracing: evidence from a natural experiment. Proc Natl Acad Sci USA 118(33):e2100814118

Forsythe E, Kahn LB, Lange F, Wiczer D (2020) Labor demand in the time of COVID-19: evidence from vacancy postings and UI claims. J Public Econ 189:104238

Article   PubMed   PubMed Central   Google Scholar  

Furceri D, Loungani P, Ostry JD, Pizzuto P (2022) Will COVID-19 have long-lasting effects on inequality? Evidence from past pandemics. J Econ Inequal 20:811–839

Gathergood J, Guttman-Kenney B (2021) The English patient: evaluating local lockdowns using real-time COVID-19 & consumption data. Covid Economics 64, Centre for Economic Policy Research

Google LLC (2021) Google COVID-19 Community Mobility Reports. https://www.google.com/covid19/mobility/ Accessed 31 Mar 2021

Goolsbee A, Syverson C (2020) Fear, lockdown, and diversion: comparing drivers of pandemic economic decline 2020. J Public Econ 193:104311

Gupta S, Simon K, Wing C (2020) Mandated and voluntary social distancing during the COVID-19 epidemic. Brookings Papers on Economic Activity. pp 269–316

Hale T, Angrist N, Goldszmidt R, Kira B, Petherick A, Phillips T, Webster S, Cameron-Blake E, Hallas L, Majumdar S, Tatlow H (2021) A global panel database of pandemic policies (Oxford COVID-19 Government Response Tracker). Nat Hum Behav 5:529–538

Article   Google Scholar  

Herby J, Jonung L, Hanke S (2022) A literature review and meta-analysis of the effects of lockdowns on COVID-19 mortality. Studies in Applied Economics (200)

Institute for Health Metrics and Evaluation (2021) Estimation of total mortality due to COVID-19. http://www.healthdata.org/special-analysis/estimation-excess-mortality-due-covid-19-and-scalars-reported-covid-19-deaths

Josephson A, Kilic T, Michler JD (2021) Socioeconomic impacts of COVID-19 in low-income countries. Nat Hum Behav 5:557–565

Article   PubMed   Google Scholar  

Kim LY, Lugo MA, Mason AD, Uochi I (2021) Inequality under COVID-19: taking stock of high-frequency data for East Asia and the Pacific. Policy Research Working Paper; No. 9859. World Bank, Washington, DC

Kugler M, Viollaz M, Duque D, Gaddis I, Newhouse DL, Palacios-Lopez A, Weber M (2021) How did the COVID-19 crisis affect different types of workers in the developing world? IZA Discussion Paper No. 14519

Liu Y, Morgenstern C, Kelly J, Lowe R; CMMID COVID-19 Working Group and Mark Jit (2021) The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories. BMC Med. 19:40

Lozano Rojas F, Jiang X, Montenovo L, Simon KI, Weinberg B, Wing C (2020). Is the cure worse than the disease? Immediate labor market effects of COVID-19 case rates and school closures in the US. Technical report, National Bureau of Economic Research

Mahler DG, Yonzan N, Lakner C, Castaneda Aguilar RA, Wu H (2021) Updated estimates of the impact of COVID-19 on global poverty: turning the corner on the pandemic in 2021? Data Blog (blog). June 24, 2021. https://blogs.worldbank.org/opendata/updated-estimates-impact-covid-19-global-poverty-turning-corner-pandemic-2021

Narayan A, Cojocaru A, Agrawal S, Bundervoet T, Davalos M, Garcia N, Lakner C, Mahler DG, Montalva Talledo V, Ten A, Yonzan N (2022) COVID-19 and economic inequality: short-term impacts with long-term consequences. Policy Research Working Paper, No. 9902. World Bank, Washington, DC

Nivette AE, Zahnow R, Aguilar R et al. (2021) A global analysis of the impact of COVID-19 stay-at-home restrictions on crime. Nat Hum Behav 5:868–877

Oshchepkov A, Shirokanova A (2022) Bridging the gap between multilevel modeling and economic methods. Soc Sci Res 104:102689

Qi J, Zhang D, Zhang X et al. (2022) Short- and medium-term impacts of strict anti-contagion policies on non-COVID-19 mortality in China. Nat Hum Behav 6:55–63

Rothwell J, Smith E (2021) Socioeconomic status as a risk factor in economic and physical harm from COVID-19: evidence from the United States. Ann Am Acad Pol Soc Sci 698(1):12–38

Spiegel M, Tookes H (2022) All or nothing? Partial business shutdowns and COVID-19 fatality growth. PLOS ONE 17:e0262925

Tascam Giorgio A, Illing V, Joyce AS, Ogrodniczuk JS (2009) Three-level multilevel growth models for nested change data: a guide for group treatment researchers. Psychother Res 19(4–5):453–461

Violato C, Violato EM, Violato EM (2021) Impact of the stringency of lockdown measures on COVID-19: a theoretical model of a pandemic. PLOS ONE 16(10):e0258205

Wang H, Paulson KR, Pease SA, Watson S et al (2022) Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21 Lancet 399:1513–1536

Article   CAS   Google Scholar  

World Bank (2022) Global Economic Prospects, January 2022. Washington, DC, World Bank. https://doi.org/10.1596/978-1-4648-1758-8

Download references

Author information

Authors and affiliations.

Gallup Inc, Washington, DC, USA

Jonathan T. Rothwell & Rajesh Srinivasan

The Brookings Institution, Washington, DC, USA

Jonathan T. Rothwell

The World Bank, Washington, DC, USA

Alexandru Cojocaru & Yeon Soo Kim

You can also search for this author in PubMed   Google Scholar

Contributions

JTR: conceptualization, formal analysis, methodology, writing of original draft and revised drafts. AC: formal analysis, methodology, and writing and revisions. YSK: writing, review, and editing. RS: data collection, methodology, writing, and reviewing. All authors substantially contributed to the article and approved the submitted version.

Corresponding author

Correspondence to Jonathan T. Rothwell .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Ethical approval

Prior to fielding, the World Poll project was reviewed by Gallup’s Institutional Review Board (IRB) and approval was granted in January of 2020. Gallup’s IRB is publicly registered with the U.S. Department of Health and Human Services (IRB00004888). Documentation of this registration is publicly available on the agency’s website, by typing “Gallup” into the search box: https://ohrp.cit.nih.gov/search/search.aspx?styp=bsc . The names of the IRB committee members and their highest level of education is provided here: Lloyd, Camille (MS); Chattopadhyay, Manas (PhD); Rheault, Magali (MS); Houts, Jonah M (MBA); Marken, Stephanie (MA); Phares Sharon (PhD); Royal, Dawn (MS); Fernandez, Cheryl F (PhD); McMurray, Coleen (BA); Odle, Adam (Esq); Ford, Kenya (AA). The database used in this analysis has no personally identifying information. Responses are linked to individuals using a quasi-random number with no external meaning.

As the scale of the coronavirus pandemic became clear in March 2020, Gallup paused global data collection to thoroughly assess risk and prepare contingency plans for data collection. By May, the continued prevalence of COVID-19 made it clear that there was too much risk of community transmission to conduct face-to-face data collection in 2020 for the World Poll. Gallup prepared a contingency methodology based entirely on telephone interviewing. In designing the new approach, Gallup prioritized the safety of interviewers and respondents, retaining high levels of representativity, and ensuring high-quality data collection. Countries were selected for inclusion based on client interest, their population size, phone penetration rates, and Gallup’s local partner’s ability to execute Computer Assisted Telephone Interviewing (CATI) aligned with Gallup’s quality assurance standards. With more than 100 countries included, the 2020 World Poll represents more than 90% of the global adult population. As a standard practice, Gallup and its partners complied with all government-issued guidance from local authorities and took this guidance into account throughout the interviewing process, including following social distancing measures for telephone interviews. Collection began in July 2020 with these issues in mind and Gallup’s weighting strategy adjusts for the mode of data collection. In July and August 2020, collection was exclusively phone-based, but gradually included face-to-face collection as the year went on.

Informed consent

Formal consent was obtained verbally from all research participants in accordance with Gallup’s IRB standards. The database used in this analysis has no personally identifying information. Responses are linked to individuals using a quasi-random number with no external meaning. Gallup and its research partners obtain consent from every respondent surveyed. Both consent requests and the survey itself are conducted in the prominent local languages of each specific region, and the survey is conducted in multiple languages in many countries. The survey is only given to people who are at least 15 years old. The English version of the consent language request used in the World Poll data analyzed in the manuscript, read as follows: “Hello, this is _______ calling on behalf of Gallup. Your household has been selected as one of only 1,000 in the [country of respondent] to participate in a special poll about this country… Your participation in this survey is voluntary. Your information will be kept private and combined with responses of other people so that individuals cannot be identified. Do you agree to participate in the survey?” For countries where 15–17-year-olds are not considered adults, the interviewer also collects parental consent. Are you age 18 or older? If not, respondent is asked, “May I speak to your parent or guardian to obtain permission to interview you? Hello, this is _______ with ________. Your child has been selected as one of only 1,000 people in [country of respondent] to participate in a special poll about this country. May I have your permission to interview your child to get their thoughts and opinions about issues in this country?”

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Supplementary text and data, replication data, rights and permissions.

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ .

Reprints and permissions

About this article

Cite this article.

Rothwell, J.T., Cojocaru, A., Srinivasan, R. et al. Global evidence on the economic effects of disease suppression during COVID-19. Humanit Soc Sci Commun 11 , 78 (2024). https://doi.org/10.1057/s41599-023-02571-4

Download citation

Received : 13 June 2023

Accepted : 21 December 2023

Published : 08 January 2024

DOI : https://doi.org/10.1057/s41599-023-02571-4

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

• | Accessibility
• University of Copenhagen
• Department of Economics, University of Copenhagen
• PhD Series, Department of Economics, University of Copenhagen

Essays on health care: New insights into the economic burden of population ageing and the implementation of health policies aimed at promoting evidence-based clinical practice and consistency in the delivery of hospital care 

Items in EconStor are protected by copyright, with all rights reserved, unless otherwise indicated.

• Bibliography
• More Referencing guides Blog Automated transliteration Relevant bibliographies by topics
• Automated transliteration
• Relevant bibliographies by topics
• Referencing guides

Dissertations / Theses on the topic 'Economic burden'

Create a spot-on reference in apa, mla, chicago, harvard, and other styles.

Consult the top 50 dissertations / theses for your research on the topic 'Economic burden.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse dissertations / theses on a wide variety of disciplines and organise your bibliography correctly.

Pennock, Jennifer M. "The economic burden of bottle-feeding." Thesis, University of Ottawa (Canada), 2002. http://hdl.handle.net/10393/6254.

Cesur, Resul. "Essays on the Aggregate Burden of Alcohol Abuse." Digital Archive @ GSU, 2009. http://digitalarchive.gsu.edu/econ_diss/4.

Silva, Guilherme. "Economic disparities and intensifying burden of neglected tropical diseases." Thesis, McGill University, 2013. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=119615.

Patel, Anisha M. "CHARACTERIZATION AND ECONOMIC BURDEN ASSOCIATED WITH PEDIATRIC OPIOID EXPOSURES AND POISONINGS." VCU Scholars Compass, 2016. http://scholarscompass.vcu.edu/etd/4518.

Poudel, Ak Narayan. "The economic burden of HIV/AIDS upon households in Nepal." Thesis, University of Aberdeen, 2015. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?pid=225678.

Patel, Dipen. "Assessing Economic and HRQL Burden of Food Allergy and Anaphylaxis in the U.S." VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2220.

Elrayah-Eliadarous, Hind. "Economic burden of diabetes on patients and their families in Sudan /." Stockholm, 2007. http://diss.kib.ki.se/2007/978-91-7357-450-1/.

O’Malley, Geoffrey. "The Unequal Health and Economic Burden of Pandemics on the Poor:." Thesis, Boston College, 2021. http://hdl.handle.net/2345/bc-ir:109154.

McCormick, Natalie. "The health resource utilization and economic burden of systemic autoimmune rheumatic diseases." Thesis, University of British Columbia, 2012. http://hdl.handle.net/2429/42149.

Wang, Xiaoting [Verfasser], and Eva [Akademischer Betreuer] Grill. "The economic burden of vertigo and dizziness / Xiaoting Wang ; Betreuer: Eva Grill." München : Universitätsbibliothek der Ludwig-Maximilians-Universität, 2020. http://d-nb.info/1221761498/34.

Fichtner, Amber, Ellen Sandvig, and Katherine Tauson. "Economic Burden of Illness and Outcomes Associated with Inpatient-Related Cases of Asthma." The University of Arizona, 2007. http://hdl.handle.net/10150/624328.

Tsang, Man-ching, and 曾文正. "Financial burden of hospitalisation for child abuse in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2013. http://hdl.handle.net/10722/196546.

Zelmer, Jennifer. "The economic burden of end-stage renal disease in Canada: present and future /." *McMaster only, 2005.

Locker, Alison R. "Burden of agricultural machinery injuries in Ontario, 1985-1996, descriptive and economic analyses." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp05/MQ63330.pdf.

Ferry, Finola Róise. "The economic and social burden of mood and anxiety disorders in Northern Ireland." Thesis, Ulster University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.673826.

Plowman, Rosalind Mary. "The incidence and economic burden of hospital acquired infections occurring in surgical patients." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2004. http://researchonline.lshtm.ac.uk/1472143/.

Mboji, Lulama. "Impact of the tax burden on long run economic growth: A BRICS perspective." Master's thesis, University of Cape Town, 2017. http://hdl.handle.net/11427/27331.

Powell, Scott R. "Shifting the Employment Burden: The Social and Economic Foundations of Welfare State Reform." The Ohio State University, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=osu1325176807.

Chandiwana, Shingirai David. "The economic burden of 'malaria' morbidity on households in Mtoko district of North-Eastern Zimbabwe." Master's thesis, University of Cape Town, 2006. http://hdl.handle.net/11427/9342.

Campbell, Robert Jr. "THE BURDEN OF DISEASE AMONG PATIENTS OF THE CAROLINA LUPUS STUDY: HUMANISTIC, CLINICAL AND ECONOMIC FACTORS." Connect to text online, 2006. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=case1145243298.

Habimana, Andre. "The effects of external debt burden on capital accumulation: a case study of Rwanda." Thesis, University of the Western Cape, 2005. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=init_2877_1177928061.

Naanda, Sara Ndapewa Mutaleni. "The magnitude and determinants of capital flight burden : a case study of Namibia, 1990 - 2005." Thesis, Stellenbosch : Stellenbosch University, 2006. http://hdl.handle.net/10019.1/21981.

Masiiwa, Rufaro. "Inpatient household economic burden of child malnutrition in Zimbabwe : a case study conducted at Harare Central hospital." Master's thesis, University of Cape Town, 2013. http://hdl.handle.net/11427/9449.

Fuchkan, Buljan Nika. "Burden of Posttraumatic Stress Disorder (PTSD) : health, social, and economic impacts of exposure to the London bombings." Thesis, London School of Economics and Political Science (University of London), 2015. http://etheses.lse.ac.uk/3274/.

Gilligan, Adrienne M. "Health Shocks in Patients with Cancer: A Longitudinal Analysis of Financial and Retirement Trends Using the Health and Retirement Study." Diss., The University of Arizona, 2013. http://hdl.handle.net/10150/293483.

Kodama, Yuko. "Increased financial burden among patients with chronic myelogenous leukaemia receiving imatinib in Japan: a retrospective survey." Kyoto University, 2017. http://hdl.handle.net/2433/226007.

Wei, Jade Wei. "Disparities in the burden of stroke in China and its relevance to emerging economies." Thesis, The University of Sydney, 2011. https://hdl.handle.net/2123/28922.

Miller, Elizabeth Jill, and res cand@acu edu au. "Burden of Care: Ageing in urban China and Japan: Gender, the family and the state." Australian Catholic University. School of Social Work, 2002. http://dlibrary.acu.edu.au/digitaltheses/public/adt-acuvp22.29082005.

Söderlin, Maria. "A population-based study on early arthritis in southern Sweden : incidence, preceding infections, diagnostic markers and economic burden /." Linköping : Univ, 2003. http://www.ep.liu.se/diss/med/08/24/index.html.

Söderlin, Maria. "A population-based study on early arthritis in southern Sweden : Incidence, preceding infections, diagnostic markers and economic burden." Doctoral thesis, Linköpings universitet, Reumatologi, 2003. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-5225.

Tabassum, Ummey Hanney. "Abandoned by Home and Burden of Host: Evaluating States' Economic Ability and Refugee Acceptance through Panel Data Analysis." Wright State University / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=wright1547548163628041.

Inocencio, Timothy. "The Economic Burden of Opioid Poisoning in the United States and Determinants of Increased Costs in Opioid Poisoning." VCU Scholars Compass, 2012. http://scholarscompass.vcu.edu/etd/2930.

Hagemeier, Nicholas E. "Introduction to the Opioid Epidemic: The Economic Burden on the Healthcare System and Impact on Quality of Life." Digital Commons @ East Tennessee State University, 2018. https://dc.etsu.edu/etsu-works/5413.

Bruce, Colin (Colin Ashley). "Contractual unenforceability, external debt renegociation and the effective incidence of the burden of debt service." Thesis, McGill University, 1986. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=72816.

Valencia, Celina I., Kacey Ernst, and Cecilia Ballesteros Rosales. "Tuberculosis Treatment Completion in a United States/Mexico Binational Context." FRONTIERS MEDIA SA, 2017. http://hdl.handle.net/10150/625712.

Chen, Jing, and 陈静. "Economic evaluation of community pharmacy based smoking cessation on burden of chronic obstructive pulmonary disease (COPD) in Hong Kong." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2011. http://hub.hku.hk/bib/B47157252.

Wagner, Ryan G. "The Burden of Epilepsy : using population-based data to define the burden and model a cost-effective intervention for the treatment of epilepsy in rural South Africa." Doctoral thesis, Umeå universitet, Epidemiologi och global hälsa, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-120163.

Baaz, Maria Eriksson. "The white wo/man's burden in the age of partnership : a postcolonial reading of identity in development aid /." Göteborg, Sweden : Dept. of Peace and Development Research, Göteborg University, 2002. http://www.loc.gov/catdir/toc/fy041/2003488872.html.

Kale, Hrishikesh P. "Economic Burden of Renal Cell Carcinoma (RCC) and Treatment Patterns, Overall Survival and Healthcare Costs among Older Metastatic RCC Patients." VCU Scholars Compass, 2018. https://scholarscompass.vcu.edu/etd/5555.

Dupont, Fabian [Verfasser], Bernhard [Akademischer Betreuer] Hemmer, Bernhard [Gutachter] Hemmer, and da Costa Clarissa [Gutachter] Prazeres. "Risk factors and socio-economic burden of neurocysticercosis in Uganda / Fabian Dupont ; Gutachter: Bernhard Hemmer, Clarissa Prazeres da Costa ; Betreuer: Bernhard Hemmer." München : Universitätsbibliothek der TU München, 2018. http://d-nb.info/1174305371/34.

Lovie-Toon, Yolanda Grace. "Burden of respiratory illnesses with cough in children from an economic and quality of life perspective, and the cost-effectiveness of early intervention." Thesis, Queensland University of Technology, 2020. https://eprints.qut.edu.au/198008/1/Yolanda_Lovie-Toon_Thesis.pdf.

White, Sarah L. "The epidemiology of lifestyle-related and social risk factors for chronic kidney disease, and approaches to the burden of disease." Thesis, The University of Sydney, 2009. https://hdl.handle.net/2123/28217.

Gallrach, Franziska. "Quality of Life of People with Dementia and their Informal Caregivers - A Clinical and Economic Analysis in New Zealand." Thesis, University of Canterbury. Health Sciences Centre, 2010. http://hdl.handle.net/10092/4818.

Neave, Penny. "The burden of imported malaria among Nigerians and Ghanaians living in London : understanding the influences of the social, cultural, environmental, economic and structural context." Thesis, London School of Hygiene and Tropical Medicine (University of London), 2013. http://researchonline.lshtm.ac.uk/4646553/.

Campbell, Braden Joseph. "Alternative management practices to improve the growth and mitigate the health and economic losses associated with parasitic infection in pasture-raised lambs in the eastern United States of America." The Ohio State University, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=osu1619020179009712.

Nakabe, Takayo. "The personal cost of dementia care in Japan: A comparative analysis of residence types." Kyoto University, 2020. http://hdl.handle.net/2433/253218.

Katzenellenbogen, Judith Masha. "Use of data linkage to enhance burden of disease estimates in Western Australia : the example of stroke." University of Western Australia. School of Population Health, 2009. http://theses.library.uwa.edu.au/adt-WU2009.0117.

Drabo, Alassane. "Health, environment and economic development." Thesis, Clermont-Ferrand 1, 2011. http://www.theses.fr/2011CLF10376/document.

Vu, Huong. "Health and economic burden of human Streptococcus suis infection in Viet Nam and the contribution of undercooked pig product consumption practices : implications for prevention and control." Thesis, University of Oxford, 2016. https://ora.ox.ac.uk/objects/uuid:3c2d8313-130d-4399-9910-7b8cfb50855f.

Stankevičius, Evaldas. "Mokesčių naštos poveikio ekonomikos konkurencingumui vertinimas socialinės aplinkos kontekste." Doctoral thesis, Lithuanian Academic Libraries Network (LABT), 2014. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2014~D_20141105_162130-57417.

BRIEF RESEARCH REPORT article

Comparative assessment of economic burden of disease in relation to out of pocket expenditure.

• School of Humanities and Social Sciences, Indian Institute of Technology Mandi, Mandi, India

Background: The economic costs associated with morbidity pose a great financial risk on the population. Household's over-dependence on out-of-pocket (OOP) health expenditure and their inability to cope up with the economic costs associated with illness often push them into poverty. The current paper aims to measure the economic burden and resultant impoverishment associated with OOP health expenditure for a diverse set of ailments in India.

Methods: Cross-sectional data from National Sample Survey Organization (NSSO) 71st Round on “Key Indicators of Social Consumption: Health” has been employed in the study. Indices, namely the payment headcount, payment gap, concentration index, poverty headcount and poverty gap, are defined and computed. The measurement of catastrophic burden of OOP health expenditure is done at 10% threshold level.

Results: Results of the study reveal that collectively non-communicable diseases (NCDs) have higher economic and catastrophic burden, individually infections rather than NCDs such as Cardio Vascular Diseases and cancers have a higher catastrophic burden and resultant impoverishment in India. Ailments such as gastro-intestinal, respiratory, musco-skeletal, obstetrics, and injuries also have a substantial economic burden on population and push them below the poverty line. Results also show that despite the pro-poor concentration of infections, their economic burden is more concentrated among the wealthier consumption groups.

Conclusion: The study concludes that universal health coverage through adequate provision of pooled resources for health care and community-based health insurance is critical to reduce the economic burden and impoverishment related to OOP health expenditure. Measures should also be instituted to insulate people from economic burden on morbidity, especially the NCDs.

The economic costs associated with morbidity pose a great financial risk on population ( 1 ). Direct spending on health care discourages people from using health care services and encourages them to postpone their health care needs ( 2 , 3 ). In the majority of LMICs, limited resources for health care and lack of protection against catastrophic health spending have led to the over-reliance on OOP health expenditure ( 4 ).

Household's overly dependence on out-of-pocket (OOP) health expenditure and their inability to cope up with the economic costs of illness often push them into poverty ( 5 , 6 ). Households faced with this situation face enormous financial liability and are devoid of adequate means for other essential needs such as food and education ( 7 , 8 ). Further, rural dwelling, low socioeconomic status and outpatient care also contribute to the increasing economic burden of illness ( 9 , 10 ).

There are few studies which have talked about this issue by taking into consideration either NCDs or infectious diseases without analyzing its impact on impoverishment ( 6 , 11 , 12 ). There is no study which has analyzed the monetary burden and impoverishment impact of different sets of NCDs and infectious diseases separately. Therefore, this study aims at filling this gap in the literature by analyzing the economic burden and resultant impoverishment due to OOP health expenditure for a diverse set of ailments by employing the recent health expenditure survey in India.

Materials and Methods

The current study employed a nationally representative data from National Sample Survey Organization (NSSO), 71st Round (2004) on Key indicators of social consumption: Health ( 13 ). The survey comprises 65,932 sample households consisting a population of 0.33 million persons. The survey adopted a stratified multistage sample design, using census villages for the rural areas and urban blocks for the urban areas as the first-stage units (FSUs), and households as the second-stage units. The reference period for inpatient and outpatient care is 365 and 15 days, respectively. For the analysis, the OOP health expenditure for inpatient and outpatient care is converted into monthly figures and added together to get the total OOP health expenditure. In this study, OOP health expenditure is calculated by deducting the amount of reimbursement from total health expenditure. Respective sample weights have been applied in the calculation of the results. For the analysis, we have taken 16 groups of different ailments ( 13 ). The analysis is done on Stata 14 ( 14 ).

Measuring the Economic Burden of Morbidity

The economic burden of morbidity has been calculated in terms of headcount and payment gap ( 15 ). Headcount (HC) measures the percentage of population incurring OOP health expenditure. It is measured by H C =   1 N ∑ i = 1 N n i , where N is the sample size, HC is the headcount and n is number of persons incurring OOP health expenditure. The payment gap is explained as the share of OOP health expenditure in total consumption expenditure is given by G =   H T C E   * 100 , S is the payment gap, H is the OOP health expenditure, TCE is the total consumption expenditure. Measurement of catastrophic burden of OOP health expenditure (headcount and payment gap) is done at 10% threshold level of TCE which has been a standard benchmark in the literature ( 15 , 16 ). Catastrophic headcount is a fraction of the population whose OOP health expenditure as a proportion of TCE exceed the given threshold. Whereas, catastrophic payment gap measures the average degree by which OOP health expenditure as a proportion of TCE exceeds the threshold level. The concentration index has been used to determine whether the poor incur more OOP health expenditure or the rich ( 17 ). Concentration index C E and C O (for headcount and payment gap, respectively) as given by the following formula: CI = ( p 1 L 2 − p 2 L 1 ) + ( p 2 L 3 − p 3 L 2 )+…+( p t −1 L t − p t L t −1 ), Where CI is the concentration index, p t is the cumulative percentage of the population ranked by monthly consumption expenditure in group t, L t is the corresponding health variable.

Measuring the Impoverishment Impact of Morbidity

Poverty headcount impact measures the fraction of population falling below the poverty line due to OOP health expenditure. The poverty impact in terms of headcount is measured as PI HC = HC Post − HC Pre , where PI HC is the poverty headcount impact, Z Pre be the pre-payment poverty line. Then P Pre = 1 if x < Z Pre H C P r e   =   1 N ∑ i = 1 N P P r e , P Pre is the pre-payment poverty headcount, HC Post and HC Post are the post and pre-payment poverty headcount. Poverty impact in terms of gap measures the average shortfall due to OOP health expenditure from the existing poverty line. It is given as PI G = G Post − G Pre , where PI G is the poverty gap impact, g Pre is the pre-payment gap, that is equal to x—Z Pre if x < Z Pre , and zero otherwise, G P r e =   1 N   ∑ i = 1 N g P r e   , G Post and G Pre are the post and pre-payment poverty gap.

Economic Burden of Morbidity in India

Table 1 reports the economic and catastrophic burden of OOP health expenditure incurred on different ailments. Although, collectively NCDs have higher economic burden, in case of individual ailments a significant proportion of population reported OOP health expenditure in case of infections followed by respiratory, CVDs, musco-skeletal, gastro-intestinal, psychiatric, and injuries. Although in lesser proportions, OOP health expenditure is also reported in other categories of ailments. Similarly, the payment gap as share of OOP health expenditure in TCE is also higher among infections as compared to other ailments. Similar to the economic burden, the catastrophic burden reported at 10% threshold level is relatively higher in case of infections than other ailments. However, collectively NCDs have higher catastrophic impact on the population. In case of infections, the negative value of C.I E and the positive value of C.I O reveal that despite its pro-poor concentration, it is the wealthier consumption groups which spends more on the treatment. However, in case of NCDs, especially CVDs and cancer, the positive values of CI E and CI O reveal a pro-rich concentration of headcount as well as OOP health expenditure.

Table 1 . Economic burden of morbidity in India.

Poverty Impact of Morbidity in India

Table 2 presents the poverty impact of OOP health expenditure incurred on different ailments in terms of headcount and payment gap. Poverty impact in terms of headcount is highest in case of infections, followed by CVDs and gastro-intestinal, musco-skeletal, respiratory, and injuries. Similarly, the poverty impact in terms of payment gap is also significantly higher in infections. It shows that the average shortfall from the poverty line is higher in case of infections than other ailments. Ailments consisting of gastro, musco-skeletal, respiratory, CVDs, and injuries also have higher poverty gap impact. Some other ailments such as skin, blood disorders, eye and ear also marginally contribute toward impoverishment.

Table 2 . Poverty impact of morbidity in India.

Overall, the results of the study reveal that NCDs such as CVDs, cancers, etc. have the higher catastrophic burden and resultant impoverishment in India. Although individually CVDs have a significant economic burden and high poverty impact, it is less than infections. Ailments such as gastro-intestinal, respiratory, musco-skeletal, obstetrics and injuries also have a substantial economic burden on population and push them below the poverty line. Infections have higher poverty impact because the population affected with the same is more concentrated around the poverty line. A smaller increase in OOP health expenditure pushes the larger proportion of population below the poverty line.

Although it is true that the burden of NCDs is increasing in India and cumulatively they have higher catastrophic burden but it is the infectious diseases which push more people into the quagmire of poverty ( 18 ). Studies from other LMICs reveal that the economic burden and resultant impoverishment due to OOP health expenditure has been relatively high in case of NCDs such as CVDs, cancer, diabetes and stroke ( 19 , 20 ). Further, many countries in Africa have higher incidence of catastrophic health expenditure due to infectious disease like Malaria and Tuberculosis ( 21 , 22 ). In LMICs, lack of access to health services, poor quality of care and high user charges contribute to higher OOP health expenditure ( 12 ). Further, inadequate public spending on health care and poor implementation of publicly financed health insurance schemes (PFHIs) have further accentuated the problem of health care financing in India ( 23 , 24 ).

The high catastrophic burden and resultant impoverishment associated with morbidity highlight the need for a better financial protection mechanism in India, particularly for the poor and vulnerable. Universal health coverage (UHC) is regarded as a critical path for improving the health outcomes and providing financial protection against the catastrophic health expenditure ( 25 ). It is a comprehensive health system approach that helps to provide improved access to health care services which significantly improves the health outcomes ( 26 ). UHC can be achieved through a matured health system that can provide sufficient and continuous pooled resources for health ( 27 ). Apart from improving access to health care services, policy makers must focus on extending quality care, especially to poor families ( 28 ). LMICs can implement community-based health insurance (CBHI) which can go a long way in achieving UHC ( 29 ).

The future plan of the research will be to measure the economic burden of ailments at different threshold levels. Along with-it different sources of finance used to cope up with OOP health expenditure for different ailments will also be studied. A comparative analysis with previous data rounds may also be useful.

Data Availability Statement

This paper is based on anonymized survey data collected by the National Sample Survey organization (NSSO), a department of the Ministry of Statistics and Programme Implementation, Government of India. Data is available in the public domain. The data is already available in publicly available repositories to individuals both at national and international level through http://www.mospi.gov.in/

Author Contributions

RT and SS conceived the idea with inputs from VD. SS performed the statistical analysis and prepared the initial draft of the manuscript. RT and VD assisted in the revision of the manuscript. All authors read and approved the final manuscript.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

1. Tolla MT, Norheim OF, Verguet S, Bekele A, Amenu K, Abdisa SG, et al. Out-of-pocket expenditures for prevention and treatment of cardiovascular disease in general and specialised cardiac hospitals in Addis Ababa, Ethiopia: a cross-sectional cohort study. BMJ Global Health (2017) 2:e000280. doi: 10.1136/bmjgh-2016-000280

PubMed Abstract | CrossRef Full Text | Google Scholar

2. WHO. World Health Report 2010: Health Systems Financing the Path to Universal Coverage. Geneva: WHO (2010).

3. Xu K, Evans DB, Kawabata K, Zeramdini R, Klavus J, Murray CJ. Household catastrophic health expenditure: a multicountry analysis. Lancet (2003) 362:111–7. doi: 10.1016/S0140-6736(03)13861-5

4. Dieleman J, Campbell M, Chapin A, Eldrenkamp E, Fan VY, Haakenstad A, et al. Evolution and patterns of global health financing 1995–2014: development assistance for health, and government, prepaid private, and out-of-pocket health spending in 184 countries. Lancet (2017) 389:1981–2004. doi: 10.1016/S0140-6736(17)30874-7

CrossRef Full Text | Google Scholar

5. van Doorslaer E, O'Donnell O, Rannan-Eliya RP, Somanathan A, Adhikari SR, Garg CC, et al. Effect of payments for health care on poverty estimates in 11 countries in Asia: an analysis of household survey data. Lancet (2006) 368:1357–64. doi: 10.1016/S0140-6736(06)69560-3

6. Mahal AS, Karan A, Engelgau M. Economic Implications of Non-communicable Disease for India . Washington, DC: World Bank (2010).

Google Scholar

7. Van Minh H, Kim Phuong NT, Saksena P, James CD, Xu K. Financial burden of household out-of pocket health expenditure in Viet Nam: findings from the National Living Standard Survey 2002–2010. Soc Sci Med. (2013) 96:258–63. doi: 10.1016/j.socscimed.2012.11.028

8. WHO. World Health Statistics 2015 . Geneva: World Health Organisation (2015).

9. Karan A, Selvaraj S, Mahal A. Moving to universal coverage? Trends in the burden of out-of-pocket payments for health care across social groups in India, 1999–2000 to 2011–12. PLoS ONE (2014) 9:e105162. doi: 10.1371/journal.pone.0105162

10. Kumar K, Singh A, Kumar S, Ram F, Singh A, Ram U, et al. Socio-economic differentials in impoverishment effects of out-of-pocket health expenditure in China and India: evidence from WHO SAGE. PLoS ONE (2015) 10:e0135051. doi: 10.1371/journal.pone.0135051

11. Rajpal S, Kumar A, Joe W. Economic burden of cancer in India: evidence from cross-sectional nationally representative household survey, 2014. PLoS ONE (2018) 13:e0193320. doi: 10.1371/journal.pone.0193320

12. Russell S. The economic burden of illness for households in developing countries: a review of studies focusing on malaria, tuberculosis, and human immunodeficiency virus/acquired immunodeficiency syndrome. Am J Trop Med Hyg. (2004) 71 (2_suppl):147–55. doi: 10.4269/ajtmh.2004.71.147

13. NSSO. Key Indicators of Social Consumption in India: Health, 71st Round (January-June 2014) . New Delhi: Ministry of Statistics and Programme Implementation, Government of India (2014).

14. Corp 2015. Stata. Stata Statistical Software: Release 14. College Station, TX: StataCorp LP 2014 (2014).

15. Wagstaff A, van Doorslaer E. Catastrophe and impoverishment in paying for health care: with applications to Vietnam 1993–1998. Health Econ. (2003) 12:921–33. doi: 10.1002/hec.776

16. Pradhan M, Prescott N. Social risk management options for medical care in Indonesia. Health Econ. (2002) 11:431–46. doi: 10.1002/hec.689

17. Fuller MF, Lury DA. Statistics Workbook for Social Science Students . Oxford, UK: Allan (1977)

18. ICMR. PHFI and IHME. India: Health of the Nation's States - The India State Level Disease Burden Initiative . New Delhi: Indian Council of Medical Research, Public Health Foundation of India and Institute for Health Metrics and Evaluation (2017).

19. Zaidi AA, Ansari TZ, Khan A. The financial burden of cancer: estimates from patients undergoing cancer care in a tertiary care hospital. Int J. Equit Health (2012) 11:60. doi: 10.1186/1475-9276-11-60

20. Huffman MD, Rao KD, Pichon-Riviere A, Zhao D, Harikrishnan S, Ramaiya K, et al. A cross-sectional study of the microeconomic impact of cardiovascular disease hospitalization in four low-and middle-income countries. PLoS ONE (2011) 6:e20821. doi: 10.1371/journal.pone.0020821

21. Laokri S, Dramaix-Wilmet M, Kassa F, Anagonou S, Dujardin B. Assessing the economic burden of illness for tuberculosis patients in Benin: determinants and consequences of catastrophic health expenditures and inequities. Trop Med Int Health (2014) 19:1249–58. doi: 10.1111/tmi.12365

22. Onwujekwe O, Hanson K, Uzochukwu B, Ichoku H, Ike E, Onwughalu B. Are malaria treatment expenditures catastrophic to different socio-economic and geographic groups and how do they cope with payment? A study in southeast Nigeria. Trop Med Int Health (2010) 15:18–25. doi: 10.1111/j.1365-3156.2009.02418.x

23. Prinja S, Chauhan AS, Karan A, Kaur G, Kumar R. Impact of publicly financed health insurance schemes on healthcare utilization and financial risk protection in india: a systematic review. PLoS ONE (2017) 12:e0170996. doi: 10.1371/journal.pone.0170996

24. Karan A, Yip W, Mahal A. Extending health insurance to the poor in India: an impact evaluation of Rashtriya Swasthya Bima Yojana on out of pocket spending for healthcare. Soc Sci Med. (2017) 181:83–92. doi: 10.1016/j.socscimed.2017.03.053

25. Assembly, UN General. Transforming Our World: The 2030 Agenda for Sustainable Development. New York, NY: United Nations (2015).

26. Ranabhat CL, Atkinson J, Park MB, Kim CB, Jakovljevic M. The influence of universal health coverage on life expectancy at birth (LEAB) and healthy life expectancy (HALE): a multi-country cross-sectional study. Front Pharmacol. (2018) 9:960. doi: 10.3389/fphar.2018.00960

27. Dieleman JL, Sadat N, Chang AY, Fullman N, Abbafati C, Acharya P, et al. Trends in future health financing and coverage: future health spending and universal health coverage in 188 countries, 2016–40. Lancet (2018) 391:1783–98. doi: 10.1016/S0140-6736(18)30697-4

28. Khera R, Valero-Elizondo J, Okunrintemi V, Saxena A, Das SR, de Lemos JA, et al. Association of out-of-pocket annual health expenditures with financial hardship in low-income adults with atherosclerotic cardiovascular disease in the United States. JAMA Cardiol. (2018) 3:729–38. doi: 10.1001/jamacardio.2018.1813

29. Ranabhat CL, Kim CB, Singh DR, Park MB. A comparative study on Outcome of government and co-operative community-based health insurance in nepal. Front Public Health (2017) 5:250. doi: 10.3389/fpubh.2017.00250

Keywords: economic burden, impoverishment, ailments, infections, morbidity

Citation: Sangar S, Dutt V and Thakur R (2019) Comparative Assessment of Economic Burden of Disease in Relation to Out of Pocket Expenditure. Front. Public Health 7:9. doi: 10.3389/fpubh.2019.00009

Received: 05 July 2018; Accepted: 10 January 2019; Published: 29 January 2019.

Reviewed by:

Copyright © 2019 Sangar, Dutt and Thakur. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ramna Thakur, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

• < Previous

Home > Theses and Dissertations > 4409

Theses and Dissertations

Economic burden of tuberculosis among bangladeshi population and economic evaluation of the current approaches of tuberculosis control in bangladesh.

Mohammad Rifat Haider , University of South Carolina - Columbia

Date of Award

Spring 2017

Document Type

Open Access Dissertation

Health Services and Policy Management

Sub-Department

Public Health

First Advisor

M. Mahmud Khan

Introduction: Tuberculosis (TB) is major scourge for human history and causes profound economic burden. Bangladesh is a high burden TB country with 12% of its annual death is caused and 362 thousand people are infected by TB. DS-TB is the most prominent type of TB found in Bangladesh and a 6 month drug regimen (2 month intensive and 4 month continuation phase) is followed. But the directly observed treatment short-course (DOTS) differ in delivery through community health workers (CHW) and community members (CM). Bangladesh has also experienced surge in the number of MDR-TB cases with a 29% of MDR-TB cases were found among the re-treatment of pulmonary TB cases in 2015. In Bangladesh, two MDR-TB treatment regimens (9 month and 20-24 month) are practiced. This dissertation aims to estimates the economic burden of TB on the afflicted Bangladeshi population and conducts economic evaluation among different programs for DS-TB and MDR-TB in Bangladesh.

Methods: This study collects direct and indirect cost for TB care data from 1,000 drug sensitive TB (DS-TB) and 145 multi-drug resistant (MDR-TB) patients from all over Bangladesh. Provider cost for TB care was also collected from the health facilities. Costs for DS-TB and MDR-TB patients were estimated using Generalized Linear Model and summed up with per patient provider level costs to get the total costs per TB patients.

The incremental cost-effectiveness ratio (ICER) of treating DS-TB and MDR-TB patients, CM versus CHW model for DS-TB and 9-month vs. 20-24 month regimen for MDR-TB were compared using a Markov model with life-time horizon. The measure of effectiveness, Quality adjusted life year (QALY) and cost of treatment was collected from 1,000 DS-TB and 145 MDR-TB patients (598 for CM model and 402 from CHW model; 58 undergone 9 month treatment and 87 from 20-24 month regimen) in Bangladesh. Transition probabilities between Markov states were estimated from quarterly outcomes report collected from health facilities and cost and QALY both were discounted at a rate of 3%. Both deterministic and probabilistic sensitivity analyses were conducted in a Monte Carlo Simulation using R.

Results: Mean age of DS-TB patients under the study was 45.2 years while mean age of MDR-TB patients were 35.5 years. In aggregate, DS-TB patients incurred total average costs of BDT 21,235 (USD 265) for TB illness; while MDR-TB patients’ average costs were BDT 34,975 (USD 437). Including provider costs for each patient (USD 9 for DSTB and USD 2,006 for MDR-TB patients) total average costs for each DS-TB patient was BDT 22,003 (USD 275) and for each MDR-TB patient was BDT 1,95,449 (USD 2443).

Assuming 57% case notification rate, the actual costs for treating TB patients in 2015 was USD 55.6 million. If all DS-TB patients were treated the cost would have been 1 billion USD. For MDR-TB treatment, total cost was USD 12.5 million; treating all MDR-TB patients would have costed USD 23 million.

Results show that each DS-TB patient under CM treatment model gains 3.61 QALYs with a cost of BDT 131,555. For the DS-TB patients under the CHW model the cost is 81,650 and the QALY gain is 3.12. The Incremental Cost-Effectiveness Ratio (ICER) is 103,454, i.e., the CM model is cost-effective if per QALY gain if willingness-to-pay is set to the per capita GDP of Bangladesh (BDT 107,360 in 2015).

Based on the study data, each patient under 9 month regimen gained 6.21 QALY with a total cost of BDT 987,418. Whereas, each patient under CHW model gained 5.74 QALY by incurring costs of BDT 1,501,221. Therefore, 9 month regimen is clearly dominating over the 20-24 month regimen because it costs less while it gains more QALY.

Conclusions: Results show that DS-TB patients incurred about 50% of their household annual income for treatment while that goes up to 66% for the MDR-TB patients. Pre-diagnosis cost constitutes about 63% of total costs for DS-TB patients and 42% of MDR-TB patient costs. This figures show the significant economic burden posed by TB and early diagnosis of the disease can reduce the burden in great extent.

Our study results demonstrate that community based model of DS-TB treatment is cost-effective even with changed costs and utility values in probabilistic sensitivity analysis. Community members as DOTS provider are more capable of reducing stigma related to TB, enhancing patient adherence and thereby reduce costs and increase utility from the treatment. Community members should also be involved in contact tracing and prevention activities to increase the effect of the involvement in TB control.

Our study results also suggest that shorter regimen remains cost-effective in Bangladesh setting with changing costs and utility parameters changed in the probabilistic sensitivity analysis. MDR-TB treatment is itself cost-effective in developed countries and with cost-effective shorter regimen both treatment adherence and efficacy of the treatment will be improved.

© 2017, Mohammad Rifat Haider

Recommended Citation

Haider, M.(2017). Economic Burden of Tuberculosis among Bangladeshi Population and Economic Evaluation of the Current Approaches of Tuberculosis Control in Bangladesh. (Doctoral dissertation). Retrieved from https://scholarcommons.sc.edu/etd/4409

Since July 16, 2018

Included in

Health Policy Commons

Advanced Search

• Notify me via email or RSS
• Collections
• Disciplines

Submissions

• Give us Feedback
• University Libraries

Home | About | FAQ | My Account | Accessibility Statement

Privacy Copyright

• Harvard T.H. Chan School of Public Health
• SPH Theses and Dissertations
• Communities & Collections
• By Issue Date
• FAS Department
• Quick submit
• Waiver Generator
• DASH Stories
• Accessibility
• COVID-related Research

Terms of Use

• Privacy Policy
• By Collections
• By Departments

Epidemiological and Economic Evaluation of Disease Burden in the United States: Data, Models, and Applications

Citable link to this page

Collections.

• SPH Theses and Dissertations [256]

Contact administrator regarding this item (to report mistakes or request changes)

• < Previous

Home > Graduate School > Theses and Dissertations > 5555

Theses and Dissertations

Economic burden of renal cell carcinoma (rcc) and treatment patterns, overall survival and healthcare costs among older metastatic rcc patients.

Hrishikesh P. Kale , Virginia Commonwealth University Follow

https://doi.org/10.25772/FR9H-2D70

Defense Date

Document type.

Dissertation

Degree Name

Doctor of Philosophy

Pharmaceutical Sciences

First Advisor

Norman V. Carroll

Renal cell carcinoma (RCC) is the most common type of kidney cancer. Patients diagnosed with metastatic RCC (mRCC) have shorter overall survival compared to those diagnosed at earlier stages. Several targeted therapies, which cost from $7,000 - $16,000 per month have been approved since 2005 to treat mRCC. In addition, there is a growing interest in the use of cytoreductive nephrectomy (CN) with targeted therapies among mRCC patients. However, little is known regarding the economic burden of RCC and role of CN and prescribing patterns of targeted therapies among older mRCC patients.

1) To assess the economic burden of RCC among older adults in the targeted therapy era 2) To compare the overall survival (OS) and total healthcare cost (THC) among older mRCC patients receiving CN and targeted therapy versus patients receiving targeted therapy alone 3) To describe prescribing patterns of targeted therapies and associated OS and THC among older mRCC patients.

This dissertation was conducted using the Surveillance Epidemiology and End Results (SEER) - Medicare linked data. For the first objective, the study included a prevalent cohort of RCC patients from 2013, diagnosed during 2005 - 2013 and continuously enrolled in Medicare. RCC patients were matched to non-cancer beneficiaries using propensity score matching. Generalized linear models estimated the incremental healthcare costs. Incremental total healthcare cost (THC) was multiplied by the estimated number of RCC patients on Medicare to calculate the total economic burden of RCC. For the second objective, we included patients diagnosed with mRCC between 2007-2014 and compared overall survival (OS), and THC between patients who received CN + targeted therapy and targeted therapy alone. A propensity score based inverse probability of treatment weighting (IPTW) method was used to balance the two treatment groups. A Cox proportional hazard model assessed the risk for death and a GLM compared healthcare costs between the groups. For the third objective, patients with mRCC were defined as patients who were diagnosed at stage-IV or at earlier stages but were currently using targeted therapies. Further, we restricted our sample to patients who initiated targeted therapy. We described the frequencies of the most common first and second line targeted therapies. We also described OS and THC per month for clear-cell and non-clear cell mRCC for each therapy and line of therapy.

The first study included 10,392 each of RCC and control patients. The average THC associated with RCC was $7,419. The average THC was $4,584 for patients diagnosed at stage-I, $4,727 for stage-II, $9,331 for stage-III, and $31,637 for stage-IV. The annual economic burden of RCC on Medicare was estimated to be $1.5 billion. The second study included 471 mRCC patients that received CN + targeted therapy or targeted therapy alone. The median OS from the adjusted survival curves was significantly higher (p

Conclusions

The economic burden of RCC varied substantially between early stage and metastatic patients. Among mRCC patients, use of CN among targeted therapy users was associated with a higher median OS and similar monthly THC over a lifetime. Sunitinib and everolimus were the most common first and second line targeted therapies among mRCC patients. The descriptive analysis suggested that OS and THC were similar across types of targeted therapy sequences.

© Hrishikesh P. Kale

VCU University Archives

VCU Theses and Dissertations

Date of Submission

Since August 02, 2018

Included in

Epidemiology Commons , Health Services Research Commons , Oncology Commons , Other Pharmacy and Pharmaceutical Sciences Commons , Pharmacoeconomics and Pharmaceutical Economics Commons , Pharmacy Administration, Policy and Regulation Commons

• Collections
• Disciplines

Advanced Search

• Notify me via email or RSS

Author Corner

• Submission Guidelines
• Submit Research
• Graduate School Website
• Author Rights/Copyright

Home | About | FAQ | My Account | Accessibility Statement

Privacy Copyright

Virginia Commonwealth University | VCU Libraries | Contact Us

ScholarWorks@UMass Amherst

Home > SBS > ECONOMICS > Economics Department Dissertations Collection

Economics Department Dissertations Collection

Current students, please follow this link to submit your dissertation.

Dissertations from 2023 2023

Essays on International Trade and Economic Growth , Mateo Hoyos, Economics

THREE ESSAYS ON MACROECONOMICS AND DEVELOPMENT , Guilherme Klein Martins, Economics

THREE ESSAYS ON ALLOCATION OF COSTS AND BENEFITS, CREDIT, AND TIME , Anamika Sen, Economics

Dissertations from 2022 2022

THREE ESSAYS on GROWTH and DISTRIBUTION in DUAL ECONOMIES , Adam Aboobaker, Economics

WORK, WORKERS, AND REPRODUCING SOCIAL CONTROL: RACIAL POST-FORDISM AND ALTERNATIVE SYSTEMS , Hannah Rebecca Archambault, Economics

Employer Power: Consequences for Wages, Inequality and Spillovers , Ihsaan Bassier, Economics

THREE ESSAYS ON SOCIAL JUSTICE ISSUES: HEALTH, GENDER, AND POLICING , Travis B. Campbell, Economics

CREATION OF ECONOMIC GROWTH AND COMPETITION THROUGH GREEN-INDUSTRIAL POLICIES , Camilo A. Gallego, Economics

Essays on Unpaid Care and Gender Inequality in India , Leila Gautham, Economics

THREE ESSAYS ON TECHNOLOGICAL CHANGE, THE STATE, AND EMPLOYMENT , Baris Guven, Economics

CONSTRAINTS AND ACCOMMODATED PREFERENCE: ESSAYS ON GENDER AND SOCIOECONOMIC INEQUALITY IN PAKISTAN , Sana Khalil, Economics

Essays on Anti-Discrimination Legislation Enforcement and Sex-Based Discrimination in U.S. Labor Markets , Carly McCann, Economics

THREE ESSAYS ON THE POLITICAL ECONOMY OF THE CFA FRANC , Francis Perez, Economics

THREE ESSAYS ON THE POLITICAL ECONOMY OF CULTURAL PRODUCTION AND CREATIVE LABOR , Luke Pretz, Economics

FOUR ESSAYS ON PEACE CONSOLIDATION AND ETHNIC RECONCILIATION IN POSTWAR SRI LANKA , Narayani Sritharan, Economics

The Political Economy of Consumer Credit Expansion and Real Exchange Rate Policy in Dual Economies , Esra Nur Ugurlu, Economics

Dissertations from 2021 2021

Three Essays on Learning and Conflict Applied to Developing Countries , Amal Ahmad, Economics

The Political Economy of the Cost of Foreign Exchange Intervention , Devika Dutt, Economics

CARE WORK IN CHILE’S SEGREGATED CITIES , Manuel Garcia, Economics

ESSAYS ON EXCHANGE RATE SHOCKS AND THE POLITICAL ECONOMY OF LOCAL FISCAL POLICY IN BRAZIL , Raphael Rocha Gouvea, Economics

THREE ESSAYS ON THE POLITICAL ECONOMY OF GLOBAL INACTION ON CLIMATE CHANGE , Tyler A. Hansen, Economics

Three Essays on Socio-Institutional Ecosystems & Labor Structures , Jonathan Donald Jenner, Economics

CONSTRUCTING A MARXIAN INPUT-OUTPUT MODEL CONSIDERING THE TURNOVER OF CAPITAL AND REVISITING THE FALLING-RATE-OF-PROFIT HYPOTHESIS , Junshang Liang, Economics

Three Essays on Structural Change and Labor Market Adjustment in Developing Countries , Karmen Naidoo, Economics

THREE ESSAYS ON EMPLOYMENT IMPACTS OF LABOR MARKET POLICIES , Simon Dominik Sturn, Economics

THREE ESSAYS ON LABOR AND MARRIAGE MARKETS: FARM CRISIS AND RURAL-TO-URBAN MIGRATION IN THE UNITED STATES, 1920-1940 , Jennifer Withrow, Economics

Dissertations from 2020 2020

THREE ESSAYS ON GENDER-SPECIFIC EMPLOYMENT OUTCOMES OF MACROECONOMIC POLICIES , SELIN SECIL AKIN, Economics

A New Economic History of Deindustrialization: Class Conflict and Race in the Motor City , Jackson Allison, Economics

THREE ESSAYS ON MICROECONOMIC ANALYSIS OF POLITICAL ECONOMY: EXPLOITATION, TECHNICAL CHANGE, AND MULTISECTORAL ANALYSIS , Weikai Chen, Economics

Essays on Food Security, Gender and Agriculture , Berna Dogan, Economics

THREE ESSAYS ON THE ECONOMICS OF CORPORATE GOVERNANCE , Kuochih Huang, Economics

THREE ESSAYS ON POLITICAL ECONOMY OF UNEVEN DEVELOPMENT: SPACE, CLASS AND STATE IN PAKISTAN , Danish Khan, Economics

ESSAYS ON WOMEN AND WORK IN INDIA AND ON OTHER-REGARDING PREFERENCES , Sai Madhurika Mamunuru, Economics

THREE ESSAYS ON THE ROLE OF INSTITUTIONS IN INDIAN AGRICULTURE , Kartik Misra, Economics

Neoliberal Capitalism and the Evolution of the U.S. Healthcare System , Samantha Sterba, Economics

THREE ESSAYS ON THE PAST AND FUTURE OF SOCIALISM , Mihnea Tudoreanu, Economics

THREE ESSAYS ON THE ECONOMICS AND POLITICAL ECONOMY OF THE “SCHOOL-TO-PRISON PIPELINE” , Anastasia C. Wilson, Economics

Endogenous Money, Corporate Liquidity Preferences and the Transformation of the U.S. Financial System , Yeo Hyub Yoon, Economics

Dissertations from 2019 2019

The Historical and Legal Creation of a Fissured Workplace: The Case of Franchising , Brian Callaci, Economics

Essays on the Minimum Wage, Immigration, and Privatization , Doruk Cengiz, Economics

Bangladesh's Energy Policy: Economic, Environmental, and Climate Change Impacts , Rohini Kamal, Economics

THREE ESSAYS ON THE POLITICAL ECONOMY OF THE ENVIRONMENT , An Li, Economics

REVISITING THE EAST ASIAN MIRACLE: LABOR REGIMES, PROFITABILITY AND ACCUMULATION , Zhongjin Li, Economics

Dimensions of US Global Financial Power: Essays on Financial Sanctions, Global Imbalances, and Sovereign Default , Mariam Majd, Economics

THE POLITICAL ECONOMY OF ACCUMULATION IN SOUTH AFRICA: Resource Extraction, Financialization, and Capital Flight as Barriers to Investment and Employment Growth , Seeraj Mohamed, Economics

STATE-LOCAL GOVERNMENT SPENDING, MACROECONOMIC FISCAL POLICY, AND THE BUSINESS CYCLE , Amanda Page-Hoongrajok, Economics

Essays on Monetary Policy in Developing Countries: Income Distribution, Housing and Unemployment , Zhandos Ybrayev, Economics

Resource Rents, Public Investment and Economic Development: The Case of Bolivia , Raul Zelada Aprili, Economics

Dissertations from 2018 2018

Three Essays on Governments and Financial Crises in Developing Economies, 1870-1913 , Peter H. Bent, Economics

Constraining Labor's “Double Freedom”: Revisiting the Impact of Wrongful Discharge Laws on Labor Markets, 1979-2014 , Eric Hoyt, Economics

SOCIAL STRUCTURE OF ACCUMULATION IN TURKEY (1963 – 2015) , Osman C. Icoz, Economics

Stumbling Toward the Up Escalator: How Trends in International Trade, Investment, and Finance Have Complicated Latin America’s Quest for Sustainable, Diversified Economic Development , Mary Eliza Rebecca Ray, Economics

Forms of Naturalism in Seminal Neoclassical Texts: An Analysis and Comparison of Léon Walras, John Bates Clark, and William Stanley Jevons , Mark Silverman, Economics

THREE ESSAYS ON CHILD WELFARE IN CÔTE D’IVOIRE , Didier Wayoro, Economics

Dissertations from 2017 2017

Currency Mismatch and Balance Sheet Effects of Exchange Rate in Turkish Non-Financial Corporations , Serkan Demirkilic, Economics

The Impacts of Foreign Labor Migration of Men on Women's Empowerment in Nepal , Pratistha Joshi Rajkarnikar, Economics

Real and Nominal Effects of Exchange Rate Regimes , Emiliano Libman, Economics

Three Essays on International Economics and Finance , Juan Antonio Montecino, Economics

THREE ESSAYS ON “DOING CARE”, GENDER DIFFERENCES IN THE WORK DAY, AND WOMEN’S CARE WORK IN THE HOUSEHOLD , Avanti Mukherjee, Economics

Dissertations from 2016 2016

Colonial and Post-Colonial Origins of Agrarian Development: The Case of Two Punjabs , Shahram Azhar, Economics

Three Essays on the Social Determinants of Early Childhood Health and Development , Andrew Barenberg, Economics

ELITE CAPTURE, FREE RIDING, AND PROJECT DESIGN: A CASE STUDY OF A COMMUNITY-DRIVEN DEVELOPMENT PROJECT IN CEARÁ, BRAZIL , Jessica Carrick-Hagenbarth, Economics

Three Essays on Sustainable Development in China: Social, Economic and Environmental Aspects , Ying Chen, Economics

Three Essays on Women's Land Rights in Rural Peru , Rosa L. Duran, Economics

Three Essays on Economic Stages and Transition , Ricardo R. Fuentes-Ramírez, Economics

Three Essays on U.S. Household Debt and the Sources of Systemic Financial Fragility , Thomas Herndon, Economics

Essays on Household Health Expenditures, National Health Insurance and Universal Access to Health Care in Ghana , EVELYN KWAKYE, Economics

Microfinance, Household Indebtedness and Gender Inequality , Theresa Mannah-Blankson, Economics

Three Essays on Labor Market Friction and the Business Cycle , Jong-seok Oh, Economics

Three Essays on Sustainability , Mark V. Paul, Economics

The Political Economy of Smallholder Incorporation and Land Acquisition , Alfredo R. Rosete, Economics

Employment and Family Leave Mandates: Three Essays on Labor Supply and Demand, Nontraditional Families, and Family Policy , Samantha Schenck, Economics

Endogenous Capacity, Multiple Equilibria and Thirlwall's Law: Theory and an Empirical Application to Mexico: 1950 - 2012. , Juan Alberto Vázquez Muñoz, Economics

Three Essays on the Macroeconomic Impacts of Rent Seeking , Kurt von Seekamm, Economics

Dissertations from 2015 2015

Essays on Growth Complementarity Between Agriculture and Industry in Developing Countries , Joao Paulo de Souza, Economics

Structural Transformation, Culture, and Women’s Labor Force Participation in Turkey , yasemin dildar, Economics

Essays on Information, Income, and the Sharing Economy , Anders F. Fremstad, Economics

Essays on Inequality, Credit Constraints, and Growth in Contemporary Mexico , Leopoldo Gómez-Ramírez, Economics

Three Essays on Macroeconomic Implications of Contemporary Financial Intermediation , Hyun Woong Park, Economics

The Labor Share Question in China , Hao Qi, Economics

Three essays on economic inequality and environmental degradation , Klara Zwickl, Economics

Dissertations from 2014 2014

Common Pool Resources and Rural Livelihoods in Stung Treng Province of Cambodia , Pitchaya Boonsrirat, Economics

The financialization of the nonfinancial corporation in the post-1970 U.S. economy , Leila Emami Davis, Economics

The Financial Underpinnings of the EU Crisis: Financial Deregulation, Privatization, and Asymmetric State Power , Nina Q. Eichacker, Economics

THE FINANCIAL SECTOR AND INCLUSIVE DEVELOPMENT IN AFRICA: ESSAYS ON ACCESS TO FINANCE FOR SMALL AND MEDIUM-SIZED ENTERPRISES IN SOUTH SUDAN AND KENYA , James A. Garang, Economics

OUTPUT FLUCTUATIONS AND ECONOMIC GROWTH IN LATIN AMERICA IN THE AFTERMATH OF THE GREAT RECESSION , Gonzalo Hernandez Jimenez, Economics

TEMPORARY EMPLOYMENT AND EARNINGS INEQUALITY IN SOUTH KOREA , Hyeon-Kyeong Kim, Economics

Three Essays in Macroeconomic History , Joshua W. Mason, Economics

Essays on the Evolution of Inequality , Cem Oyvat, Economics

FINANCIALIZATION OF THE COMMODITIES FUTURES MARKETS AND ITS EFFECTS ON PRICES , Manisha Pradhananga, Economics

Productive Stagnation and Unproductive Accumulation in the United States, 1947-2011. , Tomas N. Rotta, Economics

Advertising and the Creation of Exchange Value , Zoe Sherman, Economics

Understanding Income Inequality in the United States , Mark J. Stelzner, Economics

CARE TIME IN THE U.S.: MEASURES, DETERMINANTS, AND IMPLICATIONS , Joo Yeoun Suh, Economics

Essays on the minimum wage , Ben Zipperer, Economics

Dissertations from 2013 2013

Credit Chains, Credit Bubles, and Financial Fragility: Explaining The U.S. Financial Crisis of 2007-09 , Thomas L Bernardin, Economics

A Knife Hidden in Roses: Development and Gender Violence in the Dominican Republic , Cruz Caridad Bueno, Economics

Sustaining Rural Livelihoods in Upper Svaneti, Republic of Georgia , Robin J Kemkes, Economics

Contract as Contested Terrain: An Economic History of Law and the Rise of American Capitalism , Daniel P MacDonald, Economics

Essays on the Rising Demand for Convenience in Meal Provisioning in the United States , Tamara Ohler, Economics

Social Emulation, the Evolution of Gender Norms, and Intergenerational Transfers: Three Essays on the Economics of Social Interactions , Seung-Yun Oh, Economics

Decollectivization and Rural Poverty in Post-Mao China: A Critique of the Conventional Wisdom , Zhaochang Peng, Economics

Capitalist Crisis and Capitalist Reaction: The Profit Squeeze, the Business Roundtable, and the Capitalist Class Mobilization of the 1970s , Alejandro Reuss, Economics

The Economics of Same-Sex Couple Households: Essays on Work, Wages, and Poverty , Alyssa Schneebaum, Economics

The Political Economy of Cultural Production: Essays on Music and Class , Ian J. Seda Irizarry, Economics

Essays Of Human Capital Formation , Owen Thompson, Economics

Dissertations from 2012 2012

Knowledge, Gender, and Production Relations in India's Informal Economy , Amit Basole, Economics

Macroeconomic and Microeconomic Determinants of Informal Employment: The Case of Clothing Traders in Johannesburg, South Africa , Jennifer E Cohen, Economics

The Relationship Between Mass Incarceration and Crime in the Neoliberal Period in the United States , Geert Leo Dhondt, Economics

Fair Trade, Agrarian Cooperatives, and Rural Livelihoods in Peru , Noah Enelow, Economics

Organic Farming and Rural Transformations in the European Union: A Political Economy approach , Charalampos Konstantinidis, Economics

The Sources of Financial Profit: A Theoretical and Empirical Investigation of the Transformation of Banking in the US , Iren G. Levina, Economics

A Minskian Approach to Financial Crises with a Behavioural Twist: A Reappraisal of the 2000-2001 Financial Crisis in Turkey , Mathieu Perron-Dufour, Economics

Essays on Urban Sprawl, Race, and Ethnicity , Jared M. Ragusett, Economics

Agriculture and Class: Contradictions of Midwestern Family Farms Across the Twentieth Century , Elizabeth Ann Ramey, Economics

Women In Conflict, Peacebuilding And Reconstruction: Insights From The Aftermath Of Nepal's Maoist Insurgency , Smita Ramnarain, Economics

Money, Reality, and Value: Non-Commodity Money in Marxian Political Economy , Joseph Thomas Rebello, Economics

Three essays on oil scarcity, global warming and energy prices , Matthew Riddle, Economics

The Political Economy of Agrarian Change in the People's Republic of China , Zhun Xu, Economics

Dissertations from 2011 2011

State Hegemony and Sustainable Development: A Political Economy Analysis of Two Local Experiences in Turkey , Bengi Akbulut, Economics

Financial evolution and the declining effectiveness of US monetary policy since the 1980s , Hasan Comert

Why China Grew: Understanding the Financial Structure of Late Development , Adam S. Hersh, Economics

Solving the "Coffee Paradox": Understanding Ethiopia's Coffee Cooperatives Through Elinor Ostrom's Theory of the Commons , Susan Ruth Holmberg, Economics

Migration, Remittances And Intra-Household Allocation In Northern Ghana: Does Gender Matter? , Lynda Joyce Pickbourn, Economics

Youth and Economic Development: A Case Study of Out-of-School Time Programs for Low-Income Youth in New York State , Kristen Maeve Powlick, Economics

The Real Exchange Rate And Economic Development , Martin Rapetti, Economics

Essays on International Reserve Accumulation and Cooperation in Latin America , Luis Daniel Rosero, Economics

Three Essays on Racial Disparities in Infant Health and Air Pollution Exposure , Helen Scharber, Economics

Dissertations from 2010 2010

Capitalism in Post-Colonial India: Primative Accumulation Under Dirigiste and Laissez Faire Regimes , Rajesh Bhattacharya, Economics

Uneven Development and the Terms of Trade: A Theoretical and Empirical Analysis , Bilge Erten, Economics

Gendered Vulnerabilities After Genocide: Three Essays on Post-Conflict Rwanda , Catherine Ruth Finnoff, Economics

The Employment Impacts of Economy-wide Investments in Renewable Energy and Energy Efficiency , Heidi Garrett-Peltier, Economics

Household Employer Payroll Tax Evasion: An Exploration Based on IRS Data and on Interviews with Employers and Domestic Workers , Catherine B. Haskins, Economics

Racial Inequality and Affirmative Action in Malaysia and South Africa , Hwok-Aun Lee, Economics

Essays on Behavioral Labor Economics , Philip Pablo Mellizo, Economics

Three Essays on the Political Economy of Live Stock Sector in Turkey , Hasan Tekguc, Economics

The Impact Of Public Employment On Health , Wei Zhang, Economics

Dissertations from 2009 2009

Effort, work hours, and income inequality: Three essays on the behavioral effects of wage inequality , Michael Carr

Essays on investment, real exchange rate, and central bank in a financially liberalized Turkey , Deger Eryar

Essays On Investment, Real Exchange Rate, And Central Bank In A Financially Liberalized Turkey , Deger Eryar, Economics

Labor Turnover in the Child-Care Industry: Voice and Exit , Lynn A. Hatch, Economics

Three Essays on Conflict and Cooperation , Sungha Hwang, Economics

Economic Reforms in East African Countries: The Impact on Government Revenue and Public Investment , Adam Beni Swebe Mwakalobo, Economics

Post-Marxism After Althusser: A Critique Of The Alternatives , Ceren Ozselcuk, Economics

Essays on Financial Behavior and its Macroeconomic Causes and Implications , Soon Ryoo, Economics

Skill Mismatch and Wage Inequality in the U.S. , Fabian Slonimczyk, Economics

Linkages Between Inequality And Environmental Degradation: An Interregional Perspective , Marina S Vornovytskyy, Economics

Dissertations from 2008 2008

Migrant women and economic justice: A *class analysis of Anatolian -German women in homemaking and cleaning services , Esra Erdem

Emigrant or sojourner? The determinants of Mexican labor migration strategies to the United States , Florian K Kaufmann

Macrofinancial risk management in the U.S. economy: Regulation, derivatives, and liquidity preference , Marcelo Milan

Essays on behavioral economics , Wesley Jose Pech

The impact of land ownership inequality on rural factor markets , Fatma Gul Unal

Three essays on family care, time allocation, and economic well -being , Jayoung Yoon

Dissertations from 2007 2007

Capital flight and foreign direct investment in the Middle East and North Africa: Comparative development and institutional analysis , Abdullah Almounsor

Investment under financial liberalization: Channels of liquidity and uncertainty , Armagan Gezici

Three essays on social dilemmas with heterogeneous agents , Mark Howard

Between the market and the milpa: Market engagements, peasant livelihood strategies, and the on -farm conservation of crop genetic diversity in the Guatemalan highlands , S. Ryan Isakson

Late neoclassical economics: Restoration of theoretical humanism in contemporary mainstream economics , Yahya Mete Madra

Inequality and the Human Development Index , Elizabeth Anne Stanton

Dissertations from 2006 2006

Institutional settings and organizational forms: Three essays , Alper Duman

Labor market characteristics and the determinants of political support for social insurance , Anil Duman

State power, world trade, and the class structure of a nation: An overdeterminist class theory of national tariff policy , Erik E Guzik

Unions and the strategy of class transformation: The case of the Broadway musicians , Catherine P Mulder

Children's work and opportunities for education: Consequences of gender and household wealth , Sevinc Rende

The economics of immigration: Household and employment dynamics , Maliha Safri

Dissertations from 2005 2005

Capital flight from Southeast Asia: Case studies on Indonesia, Malaysia, the Philippines, and Thailand , Edsel L. Beja

Rethinking municipal privatization: A Marxian class analysis of the privatization of New York City's Central Park , Oliver David Cooke

Financial liberalization and its distributional consequences: An empirical exploration , Arjun Jayadev

Three essays on gender, land rights, and collective action in Brazil's rural political economy , Merrilee Mardon

Land markets, female land rights and agricultural productivity in Paraguayan agriculture , Thomas Masterson

Workers' struggles and transformations of capitalism at industrial enterprises in Russia, 1985–2000 , Maxim V Maximov

Economy and society: Class relations and the process of economic growth , Erik K Olsen

Gender, liberalization and agrarian change in Telangana , Smriti Rao

The contradictory imperatives of New Deal banking reforms. , Ellen D. Russell, Economics

Equity in community -based sustainable development: A case study in western India , Priya Parvathy Sangameswaran

Mandated wage floors and the wage structure: Analyzing the ripple effects of minimum and prevailing wage laws , Jeannette Wicks-Lim

Public enterprises in mixed economies: Their impact on economic growth and social equity , Andong Zhu

Dissertations from 2004 2004

An economic analysis of prison labor in the United States , Asatar P Bair

Three essays on income, inequality and environmental degradation , Rachel A Bouvier

The implementation and enforcement of environmental regulations in a less developed market economy: Evidence from Uruguay , Marcelo F Caffera

Race, altruism and trust: Experimental evidence from South Africa , Justine Claire Keswell

Exchanging entailments: The contested meaning of commodity exchange , Philip M Kozel

Three essays on capital account liberalization and economic growth: New measures, new estimates and the experience of South Korea , Kang-Kook Lee

Enterprise hybrids and alternative growth dynamics , Kenneth M Levin

Social interaction and economic institution , Yongjin Park

Research and policy considerations in the valuation and the allocation of environmental and health commodities , Mihail Samnaliev

Immiserizing growth: Globalization and agrarian change in Telangana, South India between 1985 and 2000 , Vamsicharan Vakulabharanam

Social networks and labor market outcomes: Theoretical expansions and econometric analysis , Russell E Williams

Dissertations from 2003 2003

Three essays on the evolution of cooperation , Jung-Kyoo Choi

Economic size and long -term growth: An empirical analysis of the consequences of small economic size on investment, productivity and income growth , Pavel E Isa

Essays on categorical inequality, non-linear income dynamics and social mobility in South Africa , Malcolm M Keswell

The effectiveness of tax incentives in attracting investment: The case of Puerto Rico , Carlos F Liard-Muriente

A theoretical and statistical exploration into the effects of morals, personality and uncertainty on hypothetical bias in contingent valuation , Joseph D Ogrodowczyk

The role of the stock market in influencing firm investment in China , Feng Xiao

Dissertations from 2002 2002

Essays on the threat effects of foreign direct investment on labor markets , Minsik Choi

An international analysis of child welfare , Nasrin Dalirazar

Fiscal faux pas? An empirical analysis of the revenue and expenditure implications of trade liberalization , Barsha Khattry

Property from the sky: The creation of property rights in the radio spectrum in the United States , Elizabeth M Kruse

Three essays on China's state owned enterprises: Towards an alternative to privatization , Minqi Li

From welfare rights to welfare fights: Neo -liberalism and the retrenchment of social provision , John Arthur O'Connor

Political community and individual gain: Aristotle, Adam Smith and the problem of exchange , Kimberly Kaethe Sims

Rethinking prostitution: Analyzing an informal sector industry , Marjolein Katrien van der Veen

Dissertations from 2001 2001

Land and labor markets among paddy producers in the Nepalese Tarai , Ravi Bhandari

What drives equity values: fundamentals or net flows? An empircal analysis of the 1982--1999 United States stock market boom , Lawrence Lee Evans

Investment, labor demand, and political conflict in South Africa , James S Heintz

Education, Inequality and Economic Mobility in South Africa , Thomas Nathaniel Hertz

Employer work -family programs: Essays on policy implementation, employee preferences, and parental childcare choices , Sally Jane Kiser

Valuing environmental health risks: A comparison of stated preference techniques applied to groundwater contamination , Tammy Barlow McDonald

Endogenous quality and intra-industry trade , Edward Allan McPhail

Perceptions of Massachusetts family and consumer sciences education professionals regarding the importance and use of the National Standards for Family and Consumer Sciences Education in Massachusetts , Jo Ann Pullen

From feudal serfs to independent contractors: Class and African American women's paid domestic labor, 1863–1980 , Cecilia M Rio

A home of one's own: Overcoming gender and familial status barriers to homeownership , Judith K Robinson

Springfield Armory as industrial policy: Interchangeable parts and the precision corridor , Bruce K Tull

Dissertations from 2000 2000

Intergroup inequality, social identity and economic outcomes , Katherine E Baird

Engendering Globalization: Household Structures, Female Labor Supply and Economic Growth , Elissa Braunstein

Capital, conditionality, and free markets: The International Monetary Fund, the World Bank, and the effects of the neoliberal transformation in Latin America and the Caribbean , Andres Carbacho-Burgos

Rural institutions, poverty and cooperation: Learning from experiments and conjoint analysis in the field , Juan-Camilo Cardenas

Understanding the equal split as a bargaining convention and the role of residual claimancy in team production: Three essays in behavioral and experimental economics , Jeffrey Paul Carpenter

Enforcing market -based environmental policies , Carlos A Chavez Rebolledo

A comparative analysis of three economic theories focusing upon the international trade of hazardous waste (the case of electric arc furnace dust) , Amy Silverstein Cramer

The political economy of transformation in Hungary , Anita Dancs

Cross -media transfers of pollution and risk , Janine Marie Dombrowski

Essays on endogenous preferences and public generosity , Christina Margareta Fong

Con nuestro trabajo y sudor: Indigenous women and the construction of colonial society in 16th and 17th century Peru , Karen B Graubart

Banks, insider lending and industries of the Connecticut River Valley of Massachusetts, 1813–1860 , Paul Andre Lockard

Existence value: A reappraisal and cross -cultural comparison , Billy Manoka

Quality management systems and the estimation of market power exertion , Corinna Michaela Noelke

The power of personality: Labor market rewards and the transmission of earnings , Melissa Anne Osborne

Accumulation and European unemployment , Engelbert Richard Stockhammer

Modeling Superfund: A hazardous waste bargaining model with rational threats , Mary Anderson Taft

Welfare, inequality, and resource depletion: A reassessment of Brazilian economic growth, 1965–1993 , Mariano Torras

Dissertations from 1999 1999

Steadying the husband, uplifting the race: The Pittsburgh Urban League's promotion of black female domesticity during the Great Black Migration , Nina Elizabeth Banks

The origins of parallel segmented labor and product markets: A reciprocity-based agency model with an application to motor freight , Stephen V Burks

R&D, advertising, and profits: Economic theory, empirical evidence, and consequences for transfer pricing policy , David W DeRamus

Rethinking demand: A critique and reformulation of Marxian theories of price , David Leo Kristjanson

Wealth, the power to set terms, and the financing and control of firms , Paul N Malherbe

Intra -family transfers and the household division of labor: A case study of migration and remittance behavior in South Africa , Dorrit Ruth Posel

Transportation network policy modeling for congestion and pollution control: A variational inequality approach , Padma Ramanujam

The political economy of organized baseball: Analysis of a unique industry , Ross David Weiner

Dissertations from 1998 1998

The internationalization of production and its effects on the domestic behavior of United States manufacturing multinational firms , James Michael Burke

Neoliberal and neostructuralist theories of competitiveness and flexible labor: The case of Chile's manufactured exports, 1973-1996 , Fernando Ignacio Leiva

An econometric study of the export sector of Somalia , Mohamed A Osman

Financial liberalization, multinational banks and investment: Three essays on the cases of Hungary and Poland , Christian Erik Weller

Dissertations from 1997 1997

Structuralism and individualism in economic analysis: The "contractionary devaluation debate" in development economics , S Charusheela

Financial liberalization in Mexico, 1989-1993 , Colin Danby

CEO pay, agency, and the theory of the firm , Frederick Dexter Guy

Food quality regulation under trade agreements: Effects on the supply of food safety and competitiveness , Neal Hilton Hooker

Agency problems in the capital markets and the employment relationship: The possibility of efficiency-enhancing institutional innovation: An empirical case-study , Pierre Laliberte

New directions in the political economy of consumption , Allan Henry MacNeill

Capabilities and processes of industrial growth: The case of Argentina and the Argentine auto industry , Marcela Monica Miozzo

Manufacturers' responses to new nutrition labeling regulations , Eliza Maria Mojduszka

Rethinking rural development: Making peasant organizations work. The case of Paraguay , Jose R Molinas Vega

Property regimes, technology, and environmental degradation in Cuban agriculture , Hector R Saez

International multi-sector, multi-instrument financial modeling and computation: Statics and dynamics , Stavros Siokos

Three essays on government decision-making to implement and enforce environmental policies , Kristin Ellen Skrabis

Dissertations from 1996 1996

An economic critique of urban planning and the 'postmodern' city: Los Angeles , Enid Arvidson

Dissertations from 1995 1995

Trade liberalization and income distribution: Three essays with reference to the case of Mexico and the North American Free Trade Agreement (NAFTA) , Mehrene E Larudee

Dissertations from 1994 1994

Subjectivism and the limits of F. A. Hayek's political economy , Theodore A Burczak

International currencies and endogenous enforcement , Roohi Prem

Three essays on key currencies and currency blocs , Ellen Tierney

Dissertations from 1993 1993

Capitalist regulation and unequal integration: The case of Puerto Rico , Jaime Eduardo Benson

Production and reproduction: Family policy and gender inequality in East and West Germany , Lynn Susan Duggan

Dissertations from 1992 1992

Capital controls and long-term economic growth , Jessica G Nembhard

Dissertations from 1990 1990

Concentration and product diversity in culture-based industries: A case study of the music recording industry , Peter James Alexander

Dissertations from 1987 1987

THE DETERMINANTS OF THE ECONOMIC POLICIES OF STATES IN THE THIRD WORLD: THE AGRARIAN POLICIES OF THE ETHIOPIAN STATE, 1941-1974 , HENOCK KIFLE

Dissertations from 1986 1986

The Political-Economy of Nuclear Power 1946-1982 , Steven Mark Cohn, Economics

Dissertations from 1985 1985

THE IMPACT OF PUBLIC SECTOR EMPLOYMENT ON RACIAL INEQUALITY: 1950 TO 1984 (BLACK, AFFIRMATIVE ACTION, GOVERNMENT, UNEMPLOYMENT, LABOR) , PETER GEORGE BOHMER

THE GROWTH OF NONMARRIAGE AMONG U.S. WOMEN, 1954-1983 (MARRIAGE, FAMILY, HOUSEHOLDS, UNITED STATES) , ELAINE DENISE MCCRATE

Dissertations from 1983 1983

TAXATION AND PUBLIC SCHOOL FINANCE REFORM IN CONNECTICUT , MICHAEL ROBERT FEDEROW

Dissertations from 1982 1982

Evolution of a Hospital Labor System: Technology, Coercion, and Conflict , Jean E. Fisher, Economics

Dissertations from 1981 1981

THE DEVELOPMENT OF THE MARKET ECONOMY IN COLONIAL MASSACHUSETTS , RONA STEPHANIE WEISS

Dissertations from 1980 1980

Justice and economic theory. , Barry Stewart Clark, Economics

Dissertations from 1976 1976

EVALUATION OF NEOCLASSICAL THEORY OF PRICE, PRODUCTION AND THE DISTRIBUTION OF INCOME. , MANUCHER DARESHURI

Dissertations from 1970 1970

COST PROBLEMS OF THE RUTLAND RAILROAD AND ITS SUCCESSORS FROM--1937 TO 1968 , ROBERT DAVID SMITH

Advanced Search

• Notify me via email or RSS
• Collections
• Disciplines

Author Corner

• Login for Faculty Authors
• Faculty Author Gallery
• Expert Gallery
• University Libraries
• UMass Amherst

This page is sponsored by the University Libraries.

© 2009 University of Massachusetts Amherst • Site Policies

Privacy Copyright

Search Results

How big is the household housing burden? Evidence from the ECB Consumer Expectations Survey

Prepared by Omiros Kouvavas and Desislava Rusinova

In recent quarters, euro area households have been faced with higher housing costs, including mortgage costs. According to the ECB Consumer Expectations Survey, in the years since the outbreak of the COVID-19 pandemic and amid the surge in energy prices, households in the eleven largest euro area countries have seen rising housing costs, including expenditure on rent or higher mortgage interest payments, home maintenance and utilities (such as gas, electricity and water). [ 1 ] Chart A, panel a), shows the dynamics of the overall monthly housing-related burden for outright owners, renters and mortgagors. In January 2024 households were paying an average of €765 per month in total housing-related costs, including utilities, home maintenance and rent or mortgage costs. Over the period from July 2022 – the beginning of the interest rate hiking cycle - to January 2024, the average housing costs reported in the Consumer Expectations Survey rose cumulatively by around 10.2%, compared with a cumulative rise in the Harmonised Index of Consumer Prices (HICP) of 5.5%. Additionally, the dispersion in the monthly housing costs for each of the ownership types has increased. For mortgagors in particular, the higher costs would seem to be driven by the upper end of the distribution, with the cost for the lower end remaining relatively constant. This greater dispersion might suggest heterogeneous effects across mortgagors, i.e. while households with existing fixed-rate mortgages have not, as yet, been affected significantly by the ECB’s monetary policy tightening and the successive interest rate hikes, households taking out new loans or renewing or refinancing existing mortgages are already facing increased interest rate payments.

Housing costs differ across ownership types and by country. Chart A, panel b), shows the percentage change in housing costs from July 2022 to January 2024 for all three categories of households, namely outright owners, mortgagors and renters. The overall costs have increased by around 6% for outright owners, but by 12% and 9% for mortgagors and renters respectively. Different factors are at play in each case: i) for outright owners, the change is driven by rising home maintenance costs, although utility costs have fallen slightly owing to the recent moderation of energy prices following their surge in the course of 2022; ii) for mortgagors, the primary driver has been the increase in mortgage payments attributable to higher interest rates on existing variable-rate mortgages and even more noticeably on new, renewed and refinanced mortgage loans; and iii) for renters, costs have largely followed rent developments, as well as utility price trends owing to renters’ having less flexibility in absorbing unexpected expenses [ 2 ] . [ 3 ] With regard to individual euro area countries, Chart A, panel c), shows that there is significant cross-country heterogeneity in housing costs and that the difference between costs excluding mortgage payments and those including such payments is substantial, especially for countries such as Italy and Spain that tend to have a higher proportion of adjustable-rate mortgages.

Average housing costs

a) By ownership type over time

(monthly costs in EUR)

b) Cumulative change between July 2022 and January 2024

(percentage changes; percentage point contributions)

c) By country for January 2024

Sources: ECB Consumer Expectations Survey and ECB calculations. Notes: The calculations are based on weighted estimates. Average total housing costs comprise home maintenance and utility costs, together with rent for renter households or debt repayments for mortgagors, these costs being winsorised for each ownership type. It is assumed that for mortgagors, debt repayment primarily consists of the payment of principal and interest on mortgages. In panel b), housing costs include home maintenance and, for renters, also comprise rent. In panel c), countries are ordered by housing costs in descending order.

Since 2022 growth in household nominal income has largely offset the rise in housing costs, and the ratio of housing costs to income has therefore remained relatively stable. The housing cost ratio, defined as total housing costs divided by disposable income, has remained unchanged overall since the beginning of 2022. Chart B, panel a), shows that this is largely the case for all categories, i.e. outright owners, renters and mortgagors. Housing costs take up around 20% of disposable income for outright owners, 40% for renters and 35% for mortgagors. Nevertheless, this differs across income groups, with the housing cost ratio having increased slightly for the top 20% of earners among mortgage and renter households, but remaining fairly stable for the bottom 50% of earners. This difference reflects, on the one hand, the fact that higher-income households are more likely to take out mortgages and generally do so for larger amounts, while, on the other hand, there has been stronger income growth for lower-income households, possibly attributable in part to recent targeted income-support measures implemented by the larger euro area governments. [ 4 ] As Chart B, panel b), shows, including mortgage costs as a factor adds substantially to the average housing-related burden.

Housing cost to income ratio

(percentages)

b) By country for January 2024

Sources: ECB Consumer Expectations Survey and ECB calculations. Notes: The housing cost ratio is calculated at micro level for each household by dividing the housing cost by household disposable income, and the mean household housing cost ratio is then determined for each ownership type for each country. Countries are ordered by the values of the housing cost ratio in descending order.

Among lower-income groups, a substantial proportion of households are overburdened by their housing costs. According to Eurostat’s definition, households are considered to be overburdened if their total housing-related costs take up more than 40% of household disposable income. Chart C plots the proportions of overburdened households for the eleven euro area countries covered by the Consumer Expectations Survey, broken down by income quintile and ownership type. The proportions vary dramatically across income categories. In the lowest income quintile more than 60% of households are overburdened, and in particular renter households. Although the proportion of overburdened households in the higher income quintiles is substantially lower, it nevertheless encompasses about 45% of households in the second income quintile and over 20% of those in the third quintile. “Overburdened” households with a higher income are mostly mortgagors who face difficulties in paying their mortgage costs. Interestingly, the share of overburdened households in the fourth income quintile is higher than in the third, driven by mortgagors. This may reflect the fact that, in the low interest rate environment of the past, such households took out disproportionately more mortgage debt relative to their incomes.

Share of overburdened households by income quintile for January 2024

(percentages of respondents)

Sources: ECB Consumer Expectations Survey, Eurostat and ECB calculations. Notes: The calculations are based on weighted estimates. The overburden ratio is the proportion of households with housing costs exceeding 40% of their disposable household income and is calculated for all three ownership types. The proportion of overburdened households for each type is then stacked to obtain the total proportion of overburdened households per income quintile.

More households, and in particular lower-income households, have indicated in recent months that they expect to make late payments of their rent or mortgage and/or their utilities. Given the present and future effects of both increased interest rates and loss of purchasing power owing to inflation, the ability of households to meet their housing-related costs and mortgage payments is a source of concern, especially for lower-income households. In recent years, some 5-10% of low-income households have stated that they have made a late payment of rent or a mortgage and/or utilities in the past three months (Chart D, panel a). This percentage has remained relatively stable over time, although it decreased slightly in the first quarter of 2024. By contrast, the forward-looking indicator of late payment risk, measured as the proportion of households expecting to make a late payment in the next three months, has risen substantially among lower-income households. In the first quarter of 2024, the proportion of households expecting to make late payments for utilities or rent rose to over 20%, up from about 15% in 2023, and nearly doubled to 30% for late mortgage payments.

Housing cost ratios are positively correlated with the frequency of late payment, the strongest correlation being for mortgage and renter households. Average housing costs to income ratios differ substantially across countries, as does the frequency of late payments for households of different ownership types. The correlation is, however, strong across all ownership categories (Chart D, panel b). The increased risk of making late payments as housing costs rise is the largest for renters, who also have the highest average values for the housing cost ratio and for the probability of late payment. With regard to renters, any change in either indicator, which tends to be more prevalent for lower-income households, needs to be monitored carefully, given that this might have major consequences for both household consumption behaviour and indebtedness.

Late payment

a) By type of late payment over time

(percentages of respondents by income)

b) By ownership type across countries

(percentages of respondents; percentages of income)

Sources: ECB Consumer Expectations Survey, Eurostat and ECB calculations. Notes: The calculations are based on weighted estimates. In panel a), the housing cost ratio refers to the sum of the relevant cost categories (namely rent, or a mortgage, utilities and home maintenance) for each ownership type divided by disposable household income. The late payment indicator takes a value of one if a household has made a late payment in the past three months in at least one of the cost categories. Expected late payments takes a value of one if a household expects to make a late payment in the next three months in at least one of the cost categories. The values for the years 2022 and 2023 are annual averages, whereas the value for 2024 is for January only. In panel b), the housing cost ratio refers to the average ratio of total housing costs to disposable household income for the respective ownership type, calculated at micro level. Greece is excluded from the regression lines.

For general information on the Consumer Expectations Survey, see “ ECB Consumer Expectations Survey: overview and first evaluation ”, Occasional Paper Series , No 287, ECB, December 2021.

For more information on the varying impact of utility prices on ownership types see, for example, Carliner, M., “ Reducing Energy Costs in Rental Housing – The Need and the Potential ”, Research Brief, No. 13, Issue 2, Joint Center for Housing Studies of Harvard University, December 2013.

Mortgage costs account for a substantial proportion of the user cost of housing and their increase is related to the interest-rate changes of recent times. The rise seen in the user cost of housing is, however, also associated with the long-standing decline in housing investment – see Box 4, entitled “ Housing investment and the user cost of housing in the euro area ” in this issue of the Economic Bulletin.

See Box 5, entitled “ A primer on measuring household income ”, Economic Bulletin , Issue 8, ECB, 2023.

Our website uses cookies

We are always working to improve this website for our users. To do this, we use the anonymous data provided by cookies. Learn more about how we use cookies

We have updated our privacy policy

We are always working to improve this website for our users. To do this, we use the anonymous data provided by cookies. See what has changed in our privacy policy

Your cookie preference has expired

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• HHS Author Manuscripts

Conducting Research on the Economics of Hypertension to Improve Cardiovascular Health

Guijing wang.

1 Division for Heart Disease and Stroke Prevention, Centers for Disease Control and Prevention, Atlanta, Georgia

Scott D. Grosse

2 National Center on Birth Defects and Developmental Disabilities, Centers for Disease Control and Prevention, Atlanta, Georgia

Michael W. Schooley

Hypertension, a major contributor to cardiovascular disease (CVD) including heart disease and stroke, is one of the leading contributors of global burden of disease and a growing public health problem worldwide. 1 In the U.S., about 75.2 million adults (one in every three) had hypertension during 2013–2014. 2 In 2014, hypertension was listed as a primary or contributing cause of 427,631 American deaths, and heart disease and stroke were the first-and fifth-leading causes of death respectively. 3 Economically, hypertension cost the nation about $51.2 billion per year, and total CVD cost the nation about $316.1 billion per year during 2012–2013. 4 Reducing the health and economic burden of hypertension and CVD is a public health priority.

Substantial knowledge regarding the epidemiology, pharmacologic and non-pharmacologic treatments, and genetics of hypertension is available; however, many people with hypertension remain undiagnosed or undertreated because health systems cannot efficiently identify or treat them, often because of poor access to health care. 5 Hypertension control remains a major public health challenge. 6 To promote effective hypertension prevention and control, a better understanding of the economic aspects of hypertension is important. The Division for Heart Disease and Stroke Prevention (DHDSP), Centers for Disease Control and Prevention, routinely conducts applied research that evaluates program cost, cost of illness, and cost effectiveness to address this need. This commentary highlights some challenges in quantifying the economic impact, recent research, and future research opportunities of hypertension based on the applied research from DHDSP.

DEFINING AND QUANTIFYING ECONOMIC COSTS OF HYPERTENSION

Hypertension is (1) a serious health condition requiring timely and sustained treatment; (2) an independent risk factor for many costly chronic diseases including heart disease, stroke, and chronic renal disease; and (3) a general health indicator that might be associated with other diseases and conditions unrelated to hypertension. Because of these facts, quantifying the economic costs of hypertension is particularly challenging.

Economic costs of hypertension include both direct medical costs and indirect costs such as productivity loss. Direct medical costs are the costs incurred for medical products and services used to prevent, detect, or treat a disease and its complications. 7 These costs include the costs of inpatient stays, emergency room visits, physician visits, laboratory and imaging tests, home health care, and prescription medications. Although such costs are relatively straightforward to estimate because of readily available data and standardized methods, differences in study perspectives and scope of the costs, such as “charges” versus “payments,” can still present challenges to standardization. Nevertheless, cost estimates are easily understood and accepted by most decision makers and other stakeholders. Direct medical costs of hypertension include costs for hypertension treatment (i.e., hypertension treatment costs) and costs of comorbidities attributable to hypertension (i.e., hypertension-attributable costs). Hypertension-associated costs, which includes treatment and comorbidity-attributable costs, together approximate the economic burden of hypertension.

Limiting the economic cost estimates to hypertension treatment cost alone can substantially underestimate the economic burden of hypertension because it ignores the fact that hypertension is a major risk factor for many other costly diseases. One study suggested that hypertension treatment costs accounted for only 12.1% of hypertension-associated cost. 8 Another study estimated that hypertension treatment costs accounted for about 21% of hypertension-associated cost, cardiovascular complications accounted for 27%, and other diagnoses for 52%. 9 The former study also showed that the composition of the treatment cost was substantially different from the composition of hypertension-associated costs ( Figure 1 ). 8

Source : Based on findings from “National Estimate of Cost of Illness for Hypertension and Non-persistence With Drug Therapy Using the Medical Expenditure Panel Survey” by SE Graden, PhD dissertation, Ohio State University, 2003.

Indirect costs are incurred from productivity loss because of morbidity and disease-related premature mortality. 7 Although indirect costs are a significant public health burden, few studies on the indirect cost of hypertension exist. One study estimated the indirect cost of hypertension to U.S. employers in 2004 at $392 per eligible employee per year, which includes presenteeism, work absence, and short-term disability. 10 The cost of hypertension was found to be highest among ten studied health conditions including heart disease, mental disorders, and arthritis. Furthermore, the costs were generally higher than direct medical costs. Another study projected the indirect costs of hypertension at $27.2 billion in 2015, accounting for about 23% of total costs, with direct medical costs of $91.4 billion. 11

People with hypertension-related complications, such as heart disease and stroke, may require a substantial amount of informal care, including assistance with activities of daily living. This is especially true for older adults. Thus, calculating the economic burden of hypertension should also include the costs of informal caregiving. Studies have estimated the costs of informal caregiving associated with stroke in the elderly and the cost associated with heart failure in people aged >50 years. 12 , 13 Some of these costs could be attributed to hypertension.

RECENT DEVELOPMENT IN RESEARCH ON ECONOMICS OF HYPERTENSION

Recent research on the economics of hypertension in the DHDSP has started to address the priority areas of hypertension as a secondary diagnosis, informal caregiving, and evaluation of program cost and cost effectiveness. Almost all previous cost-of-illness literature has relied on data that have only included the costs for hypertension when it was listed as a primary diagnosis on medical records. 9 Recent research in DHDSP addressed hospitalization costs associated with hypertension as a secondary diagnosis. 14 Medical costs by primary and secondary diagnosis status for heart failure, acute myocardial infarction, ischemic heart disease, and stroke have also been investigated. Methods employed by and findings from these studies can be used as a foundation for further cost-effectiveness evaluations and investigation of comorbidity and aging issues related to many chronic conditions.

Another major contribution to the field is estimating informal caregiving costs for patients with heart failure and stroke. 12 , 13 Using a difference-in-difference approach, propensity score matching technique, and two-part models, incremental informal caregiving hours and costs associated with stroke and heart failure were examined. Some of these costs should be attributed to hypertension. These studies provided much needed information for further investigating the economic burden associated with hypertension and other chronic conditions.

Finally, much needed research in the evaluation of program cost and effectiveness has been conducted. A cost analysis of a community health worker program in rural Vermont provided a framework for cost evaluations using data from administrative records and personal interviews. 15 An effectiveness evaluation of full coverage for antihypertension drugs in China’s rural communities suggested it was a viable means of enhancing medication adherence while reducing total medical costs. 16 The cost effectiveness of a hypertension control intervention in community health centers in China was also examined. 17 These research methods and findings could be used to support community-based interventions for hypertension control.

FUTURE RESEARCH ON THE ECONOMICS OF HYPERTENSION

The substantial health and economic burden associated with hypertension suggests that hypertension prevention is a growing public health priority. Expanding the literature on the economics of hypertension can support such a priority. Several specific areas for future economic research may be particularly relevant to expand and improve efforts for promoting cardiovascular health:

• The economics of health disparities: Addressing health disparities is a public health imperative in the U.S. Researchers have examined health disparity issues in chronic conditions including hypertension. However, little research has documented the economic aspects of disparities, such as the impact of health disparities on medical costs or the cost effectiveness of reducing health disparities. Such economic information can support community- and local-level interventions promoting cardiovascular health in disparate population groups.
• Indirect costs and costs of informal caregiving associated with hypertension: More research is needed to better estimate indirect costs. Furthermore, the burden of chronic diseases and an aging population may increase the demand for formal and informal caregiving, especially for the elderly. Information on productivity loss as well as formal and informal caregiving can be used to more fully estimate the economic burden and help identify the necessary resources to support healthy aging.
• Economic analyses of comorbidities: Multiple chronic conditions are common among people with hypertension. For example, more than 66% of people with hypertension have three or more other chronic conditions among Medicare fee-for-service beneficiaries. 18 However, more needs to be done to accurately estimate comorbidity costs and avoid counting the same costs for multiple conditions (i.e., double counting).

These and other priorities are addressed in research from DHDSP. The articles presented in this supplement highlight some of the economic research in these areas. Ongoing and future research will continue to advance our knowledge and generate improved methods regarding the economics of hypertension. This supplement and other economic research can be used to develop, improve, and assess public health interventions for better cardiovascular health.

Acknowledgments

Publication of this article was supported by the U.S. Centers for Disease Control and Prevention (CDC), an Agency of the U.S. Department of Health and Human Services, and the Association for Prevention Teaching and Research (APTR) Cooperative Agreement No. 1U36 OE000005.

The findings and conclusions in this publication are those of the authors and do not necessarily represent the official position of the CDC.

No financial disclosures were reported by the authors of this paper.

This article is part of a supplement issue titled The Economics of Hypertension and Cardiovascular Disease.

The US's blowout debt burden is one piece of a global problem, IMF warns

• Runaway US debt levels at risks to global stability, the International Monetary Fund said in a report.
• Spiking Treasury yields are associated with exchange rate turbulence and higher interest rates elsewhere.
• The Congressional Budget Office projects debt-to-GDP levels to reach 116% by 2054.

Ballooning US debt will weigh on more than just Washington, as spiraling borrowing costs have the potential to distort the global economy, according to the International Monetary Fund.

In its latest Fiscal Monitor report, the fund expects US deficit to more than triple overspending levels in other advanced economies by 2025, projected to hit 7.1%.

"Loose fiscal policy in the United States exerts upward pressure on global interest rates and the dollar," Vitor Gaspar, director of the IMF's fiscal affairs department, said in a related press briefing . "It pushes up funding costs in the rest of the world, thereby exacerbating existing fragilities and risks."

Related stories

Specifically, the report made reference to the impact that debt has on Treasury yields, as the government must increasingly offer higher returns in order to keep attracting buyers. 

But such large and sudden rate increases are often associated with exchange rate turbulence across global markets, while a 1 percentage point spike in US interest can lead to a ramp up in foreign long-term nominal rates.

Markets have already gotten a taste of debt-related yield jumps, after a US credit downgrade sent 10- and 30-year rates surging above 5% in October . 

The IMF didn't just raise flags on the US, but warned that China's deficit and debt levels were concerning: "How these two economies manage their fiscal policies could therefore have profound effects on the global economy and pose significant risks," the report warned.  

For its part, Washington has undergone "remarkably large fiscal slippages," the IMF said, referencing falling taxes and a doubling in government spending between 2022 and 2023, despite strong growth.

If this trend continues, the Congressional Budget Office expects US debt to reach 116% of GDP by 2054 , where it currently equaled 97% in 2023. Some analysts have called this unsustainable , and a path towards national default.

Others have touted that solutions are straightforward , as long as political backing can be secured. That includes a bipartisan willingness to cut spending, as well as tax hikes across income levels. 

Watch: What Happens If The US Hits The Debt Ceiling And Defaults

• Main content