Mobile Menu

COVID-19 Benefit Cost Analysis

Resources for Benefit-Cost Analyses to Inform COVID-19 Policymaking

March 25, 2021 update

This resource page is intended to help analysts and decision makers keep up with the rapidly growing policy analysis literature about interventions to address the COVID-19 pandemic. Studies seem to be forthcoming at a rate that almost approaches the speed at which the virus is spreading. As a service to the field, we are listing those studies that have come to our attention. We also look to readers to let us know if there are additional studies we should include.

At this stage in the pandemic, policy analyses will be inherently preliminary and reflect a higher level of imprecision than analyses of diseases and interventions where we have more history. But, each generation of studies can learn from and build on those that went before. So, we are listing virtually all the studies we find while recognizing that the specific policy comparisons being made and the underlying assumptions and estimates used must be considered somewhat tentative.

The Society expresses its thanks to all the analysts who have made early contributions to this literature. Part of being relevant is being timely, even when a lot of important information is missing or must be approximates. We look forward to seeing these early studies give rise to more thorough analyses. If you know of something that should be added, please send a citation to

Relevant Methodological Material from the Journal of Benefit-Cost Analysis:

How Much is A Human Life Worth?

While the Benefit-Cost Analysis field cannot answer this specific question, it can provide considerable guidance to decision makers who must weigh alternative ways of reducing the risk of death. The key concept here is the Value of a Statistical Life which indicates how much money people will pay to reduce their chance of dying or how much extra pay they demand to take on a job with a higher risk of death.

The policy debates over how to respond to COVID-19 have seen an explosion of interest in this concept. Here are several papers to help get you up to speed:

  • Valuing Mortality Risk in the Time of COVID-19 by James K. Hammitt, June 2020.
    • This paper examines whether the value per statistical life (VSL) for the United States, estimated as approximately $10 million, is too large. It lists several reasons for thinking so. First, VSL is a marginal rate of substitution and the potential risk reductions are non-marginal. The standard VSL model implies the rate of substitution of wealth for risk reduction decreases sharply once the value of risk reduction accounts for a substantial share of income. Second, mortality risk is concentrated among the elderly, for whom VSL may be smaller and who would benefit from a persistent risk reduction for a shorter period because of their shorter life expectancy. Third, the pandemic and responses to it have caused substantial losses in income that should decrease VSL. In contrast, VSL is plausibly larger for risks (like COVID-19) that are dreaded, uncertain, catastrophic, and ambiguous. 
  • Assessing Ways of Saving Lives During the COVID-19 Pandemic: A Conversation with Kip Viscusi Kip Viscusi, June 30, 2020.
    • This Society for Benefit-Cost Analysis webinar features an interview between two experts in the field of valuing mortality risk reductions: Kip Viscusi and Tom Kniesner.
  • Valuing COVID Mortality Risks, by Center for Health Decision Science, March 28, 2020.
  • Resource Pack: Valuing Health and Longevity in BCA by Center for Health Decision Science, 2020.
  • How Much is a Human Life Actually Worth? As the US economy reopens amid a deadly pandemic, a dire question looms. Let's weigh the risks and do the math, by Adam Rogers. 
    • This article in Wired gives a history of the concept of the value of a statistical life and how that concept has been used in policy making. It then looks at how this value can inform the debate over responses to the COVID-19 pandemic.
  • Do the Benefits of COVID-19 Policies Exceed the Costs? Exploring Uncertainties in the Age-VSL Relationship by Lisa Robinson, Ryan Sullivan, Jason F. Shogren, July 16, 2020.
    • This article compares the effects of three approaches often used to adjust the value of a statistical life (VSL) for age: an invariant population-average VSL; a constant value per statistical life-year (VSLY); and a VSL that follows an inverse-U pattern, peaking in middle age. The authors find that when applied to the U.S. age distribution of COVID-19 deaths, these approaches result in average VSL estimates of $10.6 million, $4.5 million, and $8.5 million. The differences in these values is substantial enough to alter the conclusions of frequently cited analyses of social distancing. 
  • COVID-19 and uncertainties in the value per statistical life by Lisa Robinson, August 5, 2020.
    • This short article nicely summarizes key uncertainties in measures of the value of statistical life.
  • Value of a Statistical Life under Large Mortality Risk Change: Theory and an Application to COVID-19 by Diego S. Cardoso and Ricardo Dahis, May 12, 2020.
    • This article tries to provide a practical approach to calculate the benefits of large mortality reductions where VSL estimates based on small risk changes may be inappropriate. The authors apply their approach to estimate the benefits of social distancing to combat COVID-19 in the United States and Brazil. They find that social distancing generates a benefit of $4 to 4.4 trillion in the United States, and $0.6 trillion in Brazil. Their results suggest that the constant VSL approach overestimates the benefits of social distancing by 74% on average.

Benefit-Cost Studies of COVID-19 Policy Options (most recent additions are at the bottom of this list)

  •  The Benefits and Costs of Flattening the Curve for COVID-19, by Linda Thunström, Stephen Newbold, David Finnoff, Madison Ashworth, and Jason Shogren, March 2020.
    • This paper is one of the first analyses of the benefits and costs in the United States of social distancing relative to an uncontrolled scenario without distancing. It uses data from prior epidemics and from current press reports and analyses. The authors conclude that assuming that social distancing can substantially reduce contacts among individuals, we find net benefits of roughly $5 trillion in our benchmark scenario. Several sensitivity tests are included. 
  • Does Social Distancing Matter? by Michael Greenstone and Vishan Nigam, Working Paper No. 2020-26, March 2020.
    • This paper estimates the net mortality benefits in the United States of moving between two scenarios modeled by Ferguson et al. (2020): a no policy alternative and a mitigation scenario that combines home isolation of suspect cases, home quarantine of those living in the same household as suspect cases, and social distancing of the elderly and others at most risk of severe disease. The authors estimate that the mortality benefits of social distancing are over $8 trillion.
  • "Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand." By Ferguson, Neil M., et al. March 16, 2020, London: Imperial College COVID-19 Response Team.
    • This paper provides estimates of mortality rates under a variety of scenarios.
  • The Macroeconomics of Epidemics! by Martin S. Eichenbaumy, Sergio Rebeloz, and Mathias Trabandtx, March 23, 2020.
    • This paper examines how decisions to cut back on consumption and work reduce the severity of an epidemic, as measured by total deaths, but also exacerbate the size of the recession caused by the epidemic. The authors find that the optimal containment policy increases the severity of the recession but saves roughly half a million lives in the U.S.
  • The Loss from Pandemic Influenza Risk, by Victoria Y Fan, Dean T Jamison, and Lawrence H Summers.
    • This paper looks at influenza pandemics in general to estimate loses relative to a no-epidemic scenario. Estimates are provided for countries at all income levels. 
  • Pandemics: Risks, Impacts, and Mitigation, by Nita Madhav, Ben Oppenheim, Mark Gallivan, Prime Mulembakani, Edward Rubin, and Nathan Wolfe.
    • This article provides a global perspective on the likelihood of pandemics, their effects, and policy steps to mitigate them.
  • This Time the Numbers Show We Can't Be Too Careful, by Cass Sunstein, Bloomberg Opinion, March 26, 2020, 12:30 PM EDT.
    • This brief policy piece summarizes some of the early COVID-19 benefit-cost studies and concludes that there is considerable danger in being overcautious in addressing the pandemic.
  • Confronting COVID-19: A Conversation with Columbia University Professor Scott Barrett, by Robert N. Stavins and Scott Barrett, March 27, 2020.
    • This 40-minute podcast interview starts with an overview of Professor Barrett's career. At minute 17.5 it turns to his views on a wide range of issues related to international cooperation, pandemics, the role of science in society, and benefit-cost analysis (at minute 26.5).
  • Economic analysis of COVID-19 responses (part 1 and part 2) by Julian C. Jamison, Incidental Economist,April 1, 2020.
    • These pieces highlight the importance of specifying both an intervention and counterfactual in public policy analyses; in this case a government lockdown policy compared with moderate social distancing (MSD). He goes on to summarize five studies that approximate that comparison and concludes most of the epidemiological gains come from MSD and in particular changing the behaviors of the most socially active individuals, the most at-risk individuals, and symptomatic individuals. These changes should occur early and be sustained throughout the crisis, but the marginal benefits of applying them to everybody else are relatively low.
  • Can masks help with reopening the economy? by Maria Polyakova, Jason Andrews, Stephen Luby and Jeremy Goldhaber-Fiebert. Stanford Institute for Economic Policy Research, April 2020.
    • This blog post concludes that the available evidence about whether wearing masks will curtail the spread of infectious disease is weak but nevertheless supports encouraging wide spread mask use.
  • Macroeconomic Implications of COVID-19: Can Negative Supply Shocks Cause Demand Shortages? by Veronica Guerrieri, Guido Lorenzoni, Ludwig Straub, Iván Werning. April 2, 2020.
    • This technical paper provides a detailed economic model of how a shock like the COVID-19 virus can affect the country. The authors use the model to assess the likely effectiveness of alternative macro policies being discussed. Werning provides a nice summary of the model on twitter.
  • Principles and Standards for Benefit-Cost Analysis of Public Health Preparedness and Pandemic Mitigation Programs, by Joseph Cook, Washington State University.
    • This chapter illustrates issues that might arise in conducting economic analyses of public health preparedness or pandemic mitigation programs. Some of the issues raised have been debated extensively elsewhere, such as the choice of a social discount rate, the importance of sensitivity analyses, and the use of distributional weights. Other issues such as incorporating externalities or macroeconomic effects have received less attention in the economic evaluation literature. The chapter aims to begin a discussion of appropriate principles and standards on both types of issues
  • Covid-19 Infection Externalities: Trading Off Lives vs. Livelihoodsby Zachary A. Bethune and Anton Korinek, NBER Working Paper No. 27009, April 2020.
    • This paper analyzes the externalities that arise when social and economic interactions transmit infectious diseases such as COVID-19. The authors show that private agents perceive the cost an additional infection to be around $80k whereas the social cost including infection externalities is more than three times higher, around $286k. This misvaluation has stark implications for how society ultimately overcomes the disease. They conclude that if targeting the infected is impossible, the optimal policy is still to aggressively contain and eliminate the disease, and the social cost of an extra infection rises to $586k.
  • Economic Effects of Coronavirus Outbreak (COVID-19) on the World Economy, by Fernandes, Nuno, March 22, 2020.
    • This report discusses the economic impact of the Coronavirus/COVID-19 crisis across industries, and countries. It also provides estimates of the potential global economic costs of COVID-19, and the GDP growth of different countries based on data from 30 countries, under different scenarios. The report shows the economic effects of outbreak are currently being underestimated, due to over-reliance on historical comparisons with SARS, or the 2008/2009 financial crisis. 
  • Some Basic Economics of COVID-19 Policy: A look at the trade-offs we face in regulating behavior during the pandemicby Casey Mulligan, Kevin Murphy, and Robert Topel, April 27, 2020. 
    • This paper lays out the trade-offs involved with regulating the behavior of the general population during the COVID-19 pandemic.  It draws on the authors well-known work about the value of health (Kevin M. Murphy and Robert H. Topel, The Value of Health and Longevity, Journal of Political Economy, October 2006) and provides a useful list of what we already know and highlights some key unknowns that remain. It then compares relative advantages and disadvantages of large-scale social distancing regulation to a policy of screen, test, trace and quarantine.  One important point is that the authors find that the optimal type and timing of strategies depends critically on whether we expect to contain the pandemic long-term or until a vaccine or cure arises or whether we focus on minimizing the long-run costs of a pandemic that will run its course. 
  • On the Economic Benefits and Costs of COVID-19 Mitigation Measures in Mexicoby  Irvin Rojas, May 4, 2020. 
    • This paper calculates the daily flows of COVID-19 cases under the current scenario of recommended social distance and restricted economic activity, and under a counterfactual uncontrolled scenario with no mitigation measures. The author finds that the net cost of the control in terms of aggregate output is twice as large as the estimated benefits. Details about the methods and sensitivity tests are provided to help readers assess the application of that finding.
  • Costs and Trade-Offs in the Fight Against the Covid-19 Pandemic: A Developing Country Perspective by Norman Loayza, May 15, 2020.
    • This World Bank policy brief documents the global economic contraction and its potential impact on developing countries. It argues that the pandemic crisis may hurt low- and middle-income countries disproportionately because most of them lack the resources and capacity to deal with a systemic shock of this nature. Furthermore, the author argues that, having more limited resources and capabilities but also younger populations, developing countries face different trade-offs in their fight against COVID-19 than advanced countries do.
  • Covid-19, Stay-at-Home Orders and Employment: Evidence from CPS Data. By Louis-Philippe Béland, Abel Brodeur, and Taylor Wright, May 23. 2020.
    • This paper reports that as of early May, stay-at-home orders and related policies had increased unemployment by nearly 4 percentage points, but reduced COVID-19 cases by 186,600 311,000, and deaths by 17,85123,325. It goes on to compute lost income ($18.6$21.4 billion), reduced government income tax revenues ($3.4$5.5 billion), increased unemployment insurance benefit payments ($5$5.8 billion) and reduced hospital costs ($0.7$1.2 billion). Despite the jobs lost, age adjusted value of statistical life suggests that stay-at-home orders are cost.
  • Trading Off Consumption and COVID-19 Deaths by Robert E. Hall,  Charles I. Jones, Peter J. Klenow, June 2020.
    • This note develops a framework for thinking about the following question: What is the maximum amount of consumption that a utilitarian welfare function would be willing to trade off to avoid the deaths associated with the pandemic? The answer depends crucially on the mortality rate associated with the coronavirus. If the mortality rate averages 0.81%, taken from the Imperial College London study, our answer is 41% of one year's consumption. If the mortality rate instead averages 0.44% across age groups, our answer is 28%.
  • Rationing Social Contact During the COVID-19 Pandemic: Transmission Risk and Social Benefits of US Locations by Seth Benzell, Avinash Collis, Christos Nicolaides, June 12, 2020.
    • Using location data from a large sample of smartphones, nationally representative consumer preference surveys, and government statistics, this article measures the relative transmission risk benefit and social cost of closing about thirty different location categories in the US (including shops, entertainments, and public spaces). The study finds that from February to March, there were larger declines in visits to locations that our measures imply should be closed first. The authors hope this analysis will help policymakers decide how to reopen their economies.
  • A Multi-Risk SIR Model with Optimally Targeted Lockdown by Daron Acemoglu, Victor Chernozhukov, Iván Werning, Michael D. Whinston. May 2020.
    • This paper develops a multi-risk SIR model where infection, hospitalization, and fatality rates vary between the young, the middle-aged and the old. The model enables a tractable quantitative analysis of optimal policy similar to those already developed in the context of the homogeneous-agent SIR models. The model implies that for the U.S. optimal policies that differentially targeting risk/age groups significantly outperform optimal uniform policies and most of the gains can be realized by having stricter lockdown policies on the oldest group. In addition, the paper presents the impacts of social distancing, the matching technology, the expected arrival time of a vaccine, and testing with or without tracing on optimal policies. Overall, the model suggests that targeted policies that are combined with measures that reduce interactions between groups and increase testing and isolation of the infected can minimize both economic losses and deaths.
  • Determining the optimal duration of the COVID-19 suppression policy: A cost-benefit analysis  by Anna Scherbina, May 1 2020.
    • This analysis looks at strict suppression policies and less restrictive mitigation policies. Assuming that the suppression phase will be replaced by the mitigation phase until a vaccine availability, the author finds that the optimal duration of the suppression phase is shorter the higher its economic cost and the more effectively both phases reduce virus transmission. It also concludes that the often proposed on-off suppression policy is less economically efficient than a continuous suppression regime imposed at the beginning of an outbreak.
  • Closing Schools for COVID-19; A Cost-Benefit Analysis  By Noah Stein and Rob Moore, Scioto Analysis, June 2020.
    • This paper projects that an additional four-month closing of Ohio schools in the fall of 2020 would likely save 100-210 lives but would come at significant cost to K-12 students in the form of future earnings.
  • Rationing Social Contact During the COVID-19 Pandemic: Transmission Risk and Social Benefits of US Locations by Seth Benzell, Avinash Collis, and Christos Nicolaides, June 2020.
    • The analysis described in this Proceedings of the National Academy of Sciences uses location data from a large sample of smartphones, nationally representative consumer preference surveys, and government statistics, the authors measure the relative transmission risk benefit and social cost of closing about thirty different location categories in the US. They find that from February to March, there were larger declines in visits to locations that their measures imply should be closed first.
  • The Benefits of Coronavirus Suppression: A Cost-Benefit Analysis of the Response to the First Wave of COVID-19 by James Broughel and Michael Kotrous, June 11, 2020.
    • These authors argue for using a measure of lost productivity to value lives lost due to COVID rather than using a value-of-statistical life estimates. Correspondingly, they report net benefits from social isolation measures that tend to be less than those based on the VSL approach.
  • Do the Benefits of COVID19 Policies Exceed the Costs? Exploring Uncertainties in the Age–VSL Relationship by Lisa A. Robinson, Ryan Sullivan, Jason F. Shogren, July 16, 2020.
    • This article explores the implications of theory and empirical studies, which suggest that the relationship between age and VSL is uncertain. It compares the effects of three approaches: (1) an invariant populationaverage VSL; (2) a constant value per statistical lifeyear (VSLY); and (3) a VSL that follows an inverseU pattern, peaking in middle age. The authors find that when applied to the U.S. age distribution of COVID19 deaths, these approaches result in average VSL estimates of $10.63 million, $4.47 million, and $8.31 million. Applying these estimates would significantly affect the conclusions of frequently cited analyses of social distancing. The authors also highlight other characteristics of COVID19 deaths that may increase or decrease the VSL estimates (e.g., the health status and income level of those affected, the size of the risk change, and the extent to which the risk is dreaded, uncertain, involuntarily incurred, and outside of one's control). 
  • Forming COVID-19 Policy Under Uncertainty by Charles Manski, August 1, 2020.
    • This paper applies Manski’s thinking about uncertainty in policy analysis to the challenges of assessing COVID-19 policies. He notes that COVID policy making must cope with uncertainties about the nature of the disease, transmission dynamics, and behavioral responses and do so highly limited data. He concludes that current epidemiological and macroeconomic modeling cannot deliver realistically optimal policy. However, he suggests a way forward based on "adaptive policy diversification".
  • The Covid-19 Pandemic and the $16 Trillion Virus by David M. Cutler and Lawrence H. Summers, October 12, 2020.
    • This very brief article summarizes useful estimates of the major costs of the COVID-19 epidemic and finds that the estimated cumulative financial costs in the United States exceed $16 trillion, or approximately 90% of the annual gross domestic product. Approximately half of this amount is the lost income from the COVID-19–induced recession; the remainder is the economic effects of shorter and less healthy life. Given this huge cost, the authors note that policies that can materially reduce the spread of SARS-CoV-2 have enormous social value.
  • Modeling, Macroeconomics, and Benefit-Cost Analysis of Social Distancing Efforts to Control COVID-19 Covid-19 by Jason Shorgren and John Hassler, October 14, 2020.
    • This webinar, which is available on the Society‘s website, featured the two keynote speakers who had been scheduled for the Society‘s 2020 European Conference. Professor Shogren talks about the strategy, choices, and results of his team‘s efforts to be the first ones to publish an estimate of the net social benefits of social distancing to address the spread of COVID-19. Professor Hassler talks about integrating macroeconomic and epidemiological methods to produce informative integrated assessment models of the effects and net benefits of social distancing. The presentations along with the discussion stimulated by moderator Christian Gollier provide a useful guide to providing policy relevant estimates of major social policies. 
  • Integrated Epi-Econ Assessment byTimo Boppart, Karl Harmenberg, John Hassler, Per Krusell, and Jonna Olsson, December 2020.
    • These authors develop a model that has useful implications for benefit-cost analyses of COVID-19 control strategies. Specifically, the authors formulate an economic time use model and add to it an epidemiological SIR block. In the event of an epidemic, households shift their leisure time from activities with a high degree of social interaction to activities with less, and also choose to work more from home. The model highlights the different actions taken by young individuals, who are less severely affected by the disease, and by old individuals, who are more vulnerable. The model is calibrated to time-use data from ATUS, employment data, epidemiological data, and estimates of the value of a statistical life. There are qualitative as well as quantitative differences between the competitive equilibrium and social planner allocation and, moreover, these depend critically on when a cure arrives. The article concludes that due to the role played by social activities in people's welfare, simple indicators such as deaths and GDP are insufficient for judging overall outcomes.
  • A COVID-19 Primer: Analyzing Health Care Claims, Administrative Data, and Public Use Files (9th update) by Alex Bohl and Michelle Roozeboom-Baker, December 23, 2020.
    • This primer is designed to help researchers, data scientists, and others who analyze health care claims or administrative data to better understand, track, and contain COVID-19. Readers can use this guidance to help them assess data on health care use and costs linked to COVID-19, create models for risk identification, and pinpoint complications that may follow a COVID-19 diagnosis.
  • The Benefits of Coronavirus Suppression: A Cost-Benefit Analysis of the Response to the First Wave of COVID-19 in the United States by James Broughel and Michael Kotrous, November 2020; revised 4 Feb 2021.

    • This paper estimates the benefits and costs of state suppression policies to bend the curve during the initial outbreak of COVID-19 in the United States. It employs a value-of-production approach that values benefits and costs in terms of additions or subtractions to total production. Relative to a baseline in which only the infected and at-risk populations mitigate the spread of coronavirus, the authors estimate that total benefits of suppression policies are between $605.9 billion and $841.1 billion from early March 2020 to August 1, 2020 while the relative costs are estimated to be between $214.2 billion and $331.5 billion. The results indicate that the net benefits of suppression policies to slow the spread of COVID-19 are positive and may be substantial.

  • Could the United States Benefit from a Lockdown? A Cost-Benefit Analysis by Anna Scherbina, January 2021.

    • The author estimates that with the promised rate of vaccinations, if no additional non-pharmaceutical interventions are implemented, 406,000 additional lives will be lost and the future cost of the pandemic will reach $2.4 trillion, or 11% of GDP. She then uses a cost-benefit analysis, to assess whether it is optimal for the United States to introduce a nation-wide lockdown. She finds that a lockdown would be optimal and, depending on the assumptions, it should last between two and four weeks and will generate a net benefit of up to $1.2 trillion.

  • On the Economic Benefits and Costs of COVID-19 Mitigation Measures in Mexico by Irvin Rojas, May 2020.

    • Using official sources, the author estimates that social distancing will reduce the number of COVID-19 cases in 65% relative to a counterfactual uncontrolled scenario with no mitigation measures. The benefits of the distancing policy are monetized as 697 billion USD and the net cost of mitigation in terms of output gap over a 60-months recovery period represents 29% of 2019 Mexico's GDP. 

  • Addressing the COVID-19 Pandemic: Comparing Alternative Value Frameworks by Maddalena Ferranna, JP Sevilla, David E. Bloom, Mar 2021.

    • This working paper looks at how benefit-cost analysis, utilitarianism, and prioritarianism tend to address important ethical choices in COVID-19 policy making. The authors argue that the relative regressivity of COVID-19 burdens and control policy costs suggests that analyses should focus on distributional issues. Utilitarianism and prioritarianism, in that order, increasingly favor income redistribution mechanisms compared with benefit-cost analysis. The concern for the worse-off implies that prioritarianism is more likely than utilitarianism or benefit-cost analysis to target young and socioeconomically disadvantaged individuals in the allocation of scarce vaccine doses.

General COVID-19 Resources

  • The SSRN maintains a page highlighting the array of work published in its network on COVID-19.
  • The Johns Hopkins University's COVID-19 Dashboard provides very useful and widely circulated counts of the number of COVID-19 cases, deaths, and recoveries around the world
  • The New England Journal of Medicine is making all of its articles related to COVID-19 available for free through its website.
  • The Journal of the American Medical Association also has a website with articles that summarize COVID-19 related medical care
  • How the Virus Got Out by Jin WuWeiyi CaiDerek Watkins and James Glanz, March 22, 2020.
    • The New York Times provides a great graphic showing how international travel patterns spread the virus across the world. (Note: this graphic has a lot of data any may take a while to load on your computer.)
  • What Policymakers Can Do to Defeat COVID-19 by Vivian Ho and Heidi Russell, blog of Rice University's Baker Institute for Public Policy, April 13, 2020.
    • This widely circulated blog, which includes lots of links to other sources, lists a number of treatment and policy options for addressing the pandemic.
  • Policy Implications of Models of the Spread of Coronavirus: Perspectives and Opportunities for Economists by Christopher Avery, William Bossert, Adam Clark Glenn Ellison, Sara Fisher Ellison, NBER Working Paper 27007, April 2020.
    • This paper provides a critical review of models of the spread of the coronavirus (SARS-CoV-2) epidemic that have been influential in recent policy decisions. There is tremendous opportunity for social scientists to advance the relevant literature as new and better data becomes available to bolster economic outcomes and save lives
  • Epidemiology’s Time of Need: COVID-19 Calls for Epidemic-Related Economics by Christopher Avery, William Bossert, Adam Clark Glenn Ellison, Sara Fisher Ellison, 

    • We authors describe the structure and use of epidemiology models of disease transmission, with an emphasis on the susceptible/infected/recovered (SIR) model. They discuss high-profile forecasts of cases and deaths that have been based on these models, what went wrong with the early forecasts, and how they have adapted to the current COVID pandemic. They highlight three distinct areas where economists would be well positioned to contribute to this literature: modeling heterogeneity of susceptible populations in various dimensions, accommodating endogeneity of the parameters governing disease spread, and helping to understand the importance of political economy issues in disease suppression.

  • Epidemiology’s Time of Need: COVID-19 Calls for Epidemic-Related Economics by Eleanor J. Murray, Journal of Economic Perspectives, Fall 2020.

    • The author provides an epidemiologist’s perspective on how economists can help improve our COVID-19 response. She begins with a discussion of how the goals of infectious disease modeling differ between applied and academic research settings and how some criticisms of epidemiology models are based on confusing these categories. She then examines the tradeoff between data and assumptions in epidemiology. Early in a pandemic, an applied model must rely on a combination of limited data and assumptions. But as the pandemic evolves, it (perhaps counterintuitively) turns out that the quality of the data does not always improve and that key parameters may shift in unpredictable ways. She then turns to some implications for epidemiology modeling and explains both what the public got wrong in interpreting these models and what epidemiologists got wrong in explaining them.

  • NBER Papers on Health Economics.
    • Not surprisingly, researchers in the National Bureau of Economic Research have produces a flood of papers on topics related to COVID-19 policies. In addition to the NBER papers listed elsewhere, here is a selected list of relevant papers as of April 20:
      • Estimating the COVID-19 Infection Rate: Anatomy of an Inference Problem by Charles Manski and Francesca Molinari: w27023
      • The Subways Seeded the Massive Coronavirus Epidemic in New York City by Jeffrey Harris: w27021
      • Lock-downs Loneliness and Life Satisfaction by Daniel Hamermesh: w27018
      • How Are Small Businesses Adjusting to COVID-19? Early Evidence from a Survey by Alexander Bartik, Marianne Bertrand, Zoë B. Cullen, Edward Glaeser, Michael Luca, and Christopher Stanton: w26989
  • COVID Economics; Vetted and Real-Time Papers.
    • This free online journal was launched by the Centre for Economic Policy Research (CEPR) in March 2020.  It brings together formal investigations of the economic issues emanating from the COVID outbreak, based on explicit theory and/or empirical evidence, to improve the knowledge base. CEPR is a network of over 1,500 research economists based mostly in European universities.
  • COVID-19 Analysis Resource Packs
    • The Harvard T.H. Chan School of Public Health provides a number of resource packs that will be useful to people teaching about COVID-19 policy or conducting research in that area. The packs include: Expressing Probability: Words or Numbers; Pandemic Prepardeness; Ethics, Human Rights, and Pandemics; COVID-19 and Racism; COVID-19 in the U.S. State Variation & Disparities; COVID-19 Data Visualizations; and Diagnostic Tests, Bayes, and COVID-19. Of particular use to researchers in the Resource Pack of COVID-19 Scientific Portals. This pack has links to 16 sites that track research publications related to COVID-19.

Covid Impact Survey

The Data Foundation is releasing data collected in mid-2020 by the COVID Impact Survey. The survey is an effort to provide national and regional statistics about physical health, mental health, economic security, and social dynamics in the United States during the coronavirus pandemic. 

The results released provide reliable estimates at the national level as well as for 10 states and 8 metropolitan areas, including for California, Colorado, Florida, Louisiana, Minnesota, Missouri, Montana, New York, Oregon, Texas, Atlanta, Baltimore, Birmingham, Chicago, Cleveland, Columbus, Phoenix, and Pittsburgh.

Key findings include:

  • Regional variations in compliance and lack of participation for 18-22 year olds with social distancing and wearing face masks continue to suggest either mixed messaging or unwillingness to comply with CDC guidance. Policymakers and CDC could deploy additional efforts to reinforce guidance and potential benefits for the American people in taking appropriate precautions to avoid the spread of coronavirus. 

  • Slight reductions in behaviors such as avoiding crowds and visiting restaurants across the country suggest growing COVID fatigue with certain restrictions in place as well as variations in how such measures are implemented across the country. Officials could more consistently communicate expectations and policies within their jurisdictions, including those practices that may still be necessary even when existing restrictions or stay-at-home orders are lifted.

  • Shifting views on the willingness for COVID-19 testing and participation in app-based tracking, with considerable regional and demographic variation, suggest that once policymakers decide on how to apply testing programs, education of the population will likely be needed to encourage participation.

  • Economic effects and food insecurity affect some demographics and household structures more than others. Policymakers could consider those disproportionately affected in determining strategies, for example, that more effectively encourage symptomatic individuals to stay home from work or to provide support for those who may fear losing their jobs if missing work because of illness.

The COVID Impact Survey is unique in that its methodological approach relies on an address-based random sample and also includes a range of questions about physical health, mental health, and economic security on a single survey. 

The survey was administered by NORC at the University of Chicago and the project is supported by the David and Lucile Packard Foundation, Alfred P. Sloan Foundation, and the Federal Reserve Bank of Minneapolis. Additional details about the COVID Impact Survey, including a complete de-identified, open dataset are available at for ongoing research and analysis.