Epidemic outcomes following government responses to COVID-19: Insights from nearly 100,000 models

Author:

Bendavid Eran12ORCID,Patel Chirag J.3ORCID

Affiliation:

1. Department of Medicine, Stanford University, Stanford, CA, USA.

2. Department of Health Policy, Stanford University, Stanford, CA, USA.

3. Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.

Abstract

Government responses to COVID-19 are among the most globally impactful events of the 21st century. The extent to which responses—such as school closures—were associated with changes in COVID-19 outcomes remains unsettled. Multiverse analyses offer a systematic approach to testing a large range of models. We used daily data on 16 government responses in 181 countries in 2020–2021, and 4 outcomes—cases, infections, COVID-19 deaths, and all-cause excess deaths—to construct 99,736 analytic models. Among those, 42% suggest outcomes improved following more stringent responses (“helpful”). No subanalysis (e.g. limited to cases as outcome) demonstrated a preponderance of helpful or unhelpful associations. Among the 14 associations with P values < 1 × 10 −30 , 5 were helpful and 9 unhelpful. In summary, we find no patterns in the overall set of models that suggests a clear relationship between COVID-19 government responses and outcomes. Strong claims about government responses’ impacts on COVID-19 may lack empirical support.

Publisher

American Association for the Advancement of Science (AAAS)

Reference53 articles.

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