Evidence map›Paper›PMID 36966780›Full record

Observational studyLancet (London, England)2023

Assessing COVID-19 pandemic policies and behaviours and their economic and educational trade-offs across US states from Jan 1, 2020, to July 31, 2022: an observational analysis.

Thomas J Bollyky, Emma Castro, Aleksandr Y Aravkin, Kayleigh Bhangdia, Jeremy Dalos, Erin N Hulland, Samantha Kiernan, Amy Lastuka, Theresa A McHugh, Samuel M Ostroff and 48 more

Full text readObservational Study
In one paragraph

Observational study in Lancet (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

80 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. Article
  6. Article
  7. Disparities in Advance Care Planning: Did COVID-19 Change Anything?Journal of the American Geriatrics Society · 2026
    Article
  8. Article
  9. The psychological ability to adopt recommended coping responses reduced infections during the COVID-19 pandemic.Proceedings of the National Academy of Sciences of the United States of America · 2026
    Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Pandemic-Era Shifts in Life Expectancy in Hawai'i, 2018-2022.Asia-Pacific journal of public health · 2025
    Article
  19. Article
  20. Disparities in 2020 Life Expectancy by Race and Ethnicity in Hawai'i.Hawai'i journal of health & social welfare · 2025
    Article

20 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

58 authors.

Thomas J BollykyCouncil on Foreign Relations, Washington, DC, USA.
Emma CastroInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Aleksandr Y AravkinInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Applied Mathematics, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Kayleigh BhangdiaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Jeremy DalosInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Erin N HullandInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Global Health, University of Washington, Seattle, WA, USA.
Samantha KiernanCouncil on Foreign Relations, Washington, DC, USA.
Amy LastukaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Theresa A McHughInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Samuel M OstroffInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Henry M Jackson School of International Studies, University of Washington, Seattle, WA, USA.
Peng ZhengInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Hamza Tariq ChaudhryCouncil on Foreign Relations, Washington, DC, USA; Department of Public Policy, Harvard University, Cambridge, MA, USA.
Elle RuggieroCouncil on Foreign Relations, Washington, DC, USA.
Isabella TurilliCouncil on Foreign Relations, Washington, DC, USA.
Christopher AdolphDepartment of Political Science, University of Washington, Seattle, WA, USA; Center for Statistics and the Social Sciences, University of Washington, Seattle, WA, USA.
Joanne O AmlagInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Bree Bang-JensenUniversity of Pittsburgh, Pitssburgh, PA, USA.
Ryan M BarberInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Austin CarterInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Cassidy ChangInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Rebecca M CogenInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
James K CollinsInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Xiaochen DaiInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
William James DangelInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Carolyn DapperInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Amanda DeenInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Alexandra EastusInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Health Management and Policy, Drexel University, Philadelphia, PA, USA.
Megan EricksonInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Tatiana FedosseevaInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Abraham D FlaxmanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Nancy FullmanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
John R GilesInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Gaorui GuoInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Simon I HayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Jiawei HeInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Monika HelakSeattle, WA, USA.
Bethany M HuntleyInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Vincent C IannucciInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Kasey E KinzelInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Kate E LeGrandInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Beatrice MagistroMunk School of Global Affairs and Public Policy, University of Toronto, Toronto, ON, Canada.
Ali H MokdadInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Hasan NassereldineInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Yaz OztenInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Maja PasovicInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
David M PigottInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Robert C ReinerInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Grace ReinkeInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Austin E SchumacherInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Elizabeth SerieuxInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Emma E SpurlockDepartment of Social and Behavioral Sciences, Yale University, New Haven, CT, USA; Yale School of Public Health-Social and Behavioral Sciences, Yale University, New Haven, CT, USA.
Christopher E TroegerInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Anh Truc VoInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Theo VosInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Rebecca WalcottEvans School of Public Policy & Governance, University of Washington, Seattle, WA, USA.
Shafagh YazdaniInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.
Christopher J L MurrayInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA.
Joseph L DielemanInstitute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA; Department of Health Metrics Sciences, School of Medicine, University of Washington, Seattle, WA, USA. Electronic address: dieleman@uw.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe USA struggled in responding to the COVID-19 pandemic, but not all states struggled equally. Identifying the factors associated with cross-state variation in infection and mortality rates could help to improve responses to this and future pandemics. We sought to answer five key policy-relevant questions regarding the following: 1) what roles social, economic, and racial inequities had in interstate variation in COVID-19 outcomes; 2) whether states with greater health-care and public health capacity had better outcomes; 3) how politics influenced the results; 4) whether states that imposed more policy mandates and sustained them longer had better outcomes; and 5) whether there were trade-offs between a state having fewer cumulative SARS-CoV-2 infections and total COVID-19 deaths and its economic and educational outcomes.

methodsData disaggregated by US state were extracted from public databases, including COVID-19 infection and mortality estimates from the Institute for Health Metrics and Evaluation's (IHME) COVID-19 database; Bureau of Economic Analysis data on state gross domestic product (GDP); Federal Reserve economic data on employment rates; National Center for Education Statistics data on student standardised test scores; and US Census Bureau data on race and ethnicity by state. We standardised infection rates for population density and death rates for age and the prevalence of major comorbidities to facilitate comparison of states' successes in mitigating the effects of COVID-19. We regressed these health outcomes on prepandemic state characteristics (such as educational attainment and health spending per capita), policies adopted by states during the pandemic (such as mask mandates and business closures), and population-level behavioural responses (such as vaccine coverage and mobility). We explored potential mechanisms connecting state-level factors to individual-level behaviours using linear regression. We quantified reductions in state GDP, employment, and student test scores during the pandemic to identify policy and behavioural responses associated with these outcomes and to assess trade-offs between these outcomes and COVID-19 outcomes. Significance was defined as p<0·05.

findingsStandardised cumulative COVID-19 death rates for the period from Jan 1, 2020, to July 31, 2022 varied across the USA (national rate 372 deaths per 100 000 population [95% uncertainty interval [UI] 364-379]), with the lowest standardised rates in Hawaii (147 deaths per 100 000 [127-196]) and New Hampshire (215 per 100 000 [183-271]) and the highest in Arizona (581 per 100 000 [509-672]) and Washington, DC (526 per 100 000 [425-631]). A lower poverty rate, higher mean number of years of education, and a greater proportion of people expressing interpersonal trust were statistically associated with lower infection and death rates, and states where larger percentages of the population identify as Black (non-Hispanic) or Hispanic were associated with higher cumulative death rates. Access to quality health care (measured by the IHME's Healthcare Access and Quality Index) was associated with fewer total COVID-19 deaths and SARS-CoV-2 infections, but higher public health spending and more public health personnel per capita were not, at the state level. The political affiliation of the state governor was not associated with lower SARS-CoV-2 infection or COVID-19 death rates, but worse COVID-19 outcomes were associated with the proportion of a state's voters who voted for the 2020 Republican presidential candidate. State governments' uses of protective mandates were associated with lower infection rates, as were mask use, lower mobility, and higher vaccination rate, while vaccination rates were associated with lower death rates. State GDP and student reading test scores were not associated with state COVD-19 policy responses, infection rates, or death rates. Employment, however, had a statistically significant relationship with restaurant closures and greater infections and deaths: on average, 1574 (95% UI 884-7107) additional infections per 10 000 population were associated in states with a one percentage point increase in employment rate. Several policy mandates and protective behaviours were associated with lower fourth-grade mathematics test scores, but our study results did not find a link to state-level estimates of school closures.

interpretationCOVID-19 magnified the polarisation and persistent social, economic, and racial inequities that already existed across US society, but the next pandemic threat need not do the same. US states that mitigated those structural inequalities, deployed science-based interventions such as vaccination and targeted vaccine mandates, and promoted their adoption across society were able to match the best-performing nations in minimising COVID-19 death rates. These findings could contribute to the design and targeting of clinical and policy interventions to facilitate better health outcomes in future crises.

fundingBill & Melinda Gates Foundation, J Stanton, T Gillespie, J and E Nordstrom, and Bloomberg Philanthropies.

Indexed as

COVID-19Educational StatusHumansPandemicsPolicySARS-CoV-2

Identifiers

PMID36966780
PMCPMC10036128

What OpenQuestion holds

Textfull text, public
LicenceCC BY
measurements read43
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.