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The effect of large-scale anti-contagion policies on the COVID-19 pandemic.
Nature. 2020 08; 584(7820):262-267.Nat

Abstract

Governments around the world are responding to the coronavirus disease 2019 (COVID-19) pandemic1, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with unprecedented policies designed to slow the growth rate of infections. Many policies, such as closing schools and restricting populations to their homes, impose large and visible costs on society; however, their benefits cannot be directly observed and are currently understood only through process-based simulations2-4. Here we compile data on 1,700 local, regional and national non-pharmaceutical interventions that were deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France and the United States. We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth5,6, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of approximately 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different effects on different populations, but we obtain consistent evidence that the policy packages that were deployed to reduce the rate of transmission achieved large, beneficial and measurable health outcomes. We estimate that across these 6 countries, interventions prevented or delayed on the order of 61 million confirmed cases, corresponding to averting approximately 495 million total infections. These findings may help to inform decisions regarding whether or when these policies should be deployed, intensified or lifted, and they can support policy-making in the more than 180 other countries in which COVID-19 has been reported7.

Authors+Show Affiliations

Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. shsiang@berkeley.edu. National Bureau of Economic Research, Cambridge, MA, USA. shsiang@berkeley.edu. Centre for Economic Policy Research, London, UK. shsiang@berkeley.edu.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Agricultural & Resource Economics, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Manaaki Whenua - Landcare Research, Auckland, New Zealand.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Energy & Resources Group, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Agricultural & Resource Economics, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Agricultural & Resource Economics, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Agricultural & Resource Economics, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Agricultural & Resource Economics, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Agricultural & Resource Economics, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA. Electrical Engineering & Computer Science Department, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA.Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley, Berkeley, CA, USA.

Pub Type(s)

Journal Article
Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

Language

eng

PubMed ID

32512578

Citation

Hsiang, Solomon, et al. "The Effect of Large-scale Anti-contagion Policies On the COVID-19 Pandemic." Nature, vol. 584, no. 7820, 2020, pp. 262-267.
Hsiang S, Allen D, Annan-Phan S, et al. The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Nature. 2020;584(7820):262-267.
Hsiang, S., Allen, D., Annan-Phan, S., Bell, K., Bolliger, I., Chong, T., Druckenmiller, H., Huang, L. Y., Hultgren, A., Krasovich, E., Lau, P., Lee, J., Rolf, E., Tseng, J., & Wu, T. (2020). The effect of large-scale anti-contagion policies on the COVID-19 pandemic. Nature, 584(7820), 262-267. https://doi.org/10.1038/s41586-020-2404-8
Hsiang S, et al. The Effect of Large-scale Anti-contagion Policies On the COVID-19 Pandemic. Nature. 2020;584(7820):262-267. PubMed PMID: 32512578.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - The effect of large-scale anti-contagion policies on the COVID-19 pandemic. AU - Hsiang,Solomon, AU - Allen,Daniel, AU - Annan-Phan,Sébastien, AU - Bell,Kendon, AU - Bolliger,Ian, AU - Chong,Trinetta, AU - Druckenmiller,Hannah, AU - Huang,Luna Yue, AU - Hultgren,Andrew, AU - Krasovich,Emma, AU - Lau,Peiley, AU - Lee,Jaecheol, AU - Rolf,Esther, AU - Tseng,Jeanette, AU - Wu,Tiffany, Y1 - 2020/06/08/ PY - 2020/03/22/received PY - 2020/05/26/accepted PY - 2020/6/9/pubmed PY - 2020/8/25/medline PY - 2020/6/9/entrez SP - 262 EP - 267 JF - Nature JO - Nature VL - 584 IS - 7820 N2 - Governments around the world are responding to the coronavirus disease 2019 (COVID-19) pandemic1, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), with unprecedented policies designed to slow the growth rate of infections. Many policies, such as closing schools and restricting populations to their homes, impose large and visible costs on society; however, their benefits cannot be directly observed and are currently understood only through process-based simulations2-4. Here we compile data on 1,700 local, regional and national non-pharmaceutical interventions that were deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France and the United States. We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth5,6, to empirically evaluate the effect that these anti-contagion policies have had on the growth rate of infections. In the absence of policy actions, we estimate that early infections of COVID-19 exhibit exponential growth rates of approximately 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different effects on different populations, but we obtain consistent evidence that the policy packages that were deployed to reduce the rate of transmission achieved large, beneficial and measurable health outcomes. We estimate that across these 6 countries, interventions prevented or delayed on the order of 61 million confirmed cases, corresponding to averting approximately 495 million total infections. These findings may help to inform decisions regarding whether or when these policies should be deployed, intensified or lifted, and they can support policy-making in the more than 180 other countries in which COVID-19 has been reported7. SN - 1476-4687 UR - https://www.unboundmedicine.com/medline/citation/32512578/The_effect_of_large_scale_anti_contagion_policies_on_the_COVID_19_pandemic_ L2 - https://doi.org/10.1038/s41586-020-2404-8 DB - PRIME DP - Unbound Medicine ER -