Title: bolliger32/gpl-covid: 0.4.1

Type Software Ian Bolliger, Jeanette Tseng, Daniel Allen, Kendon Bell, Trinetta Chong, Sébastien Annan-Phan, Esther Rolf, Yue 'Luna' Huang, Hannah Druckenmiller, Emma Krasovich, Peiley Lau, Andrew Hultgren, Jaecheol Lee, Solomon Hsiang (2020): bolliger32/gpl-covid: 0.4.1. Zenodo. Software. https://zenodo.org/record/3829194

Authors: Ian Bolliger (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Energy & Resources Group, UC Berkeley) ; Jeanette Tseng (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley) ; Daniel Allen (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley) ; Kendon Bell (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Manaaki Whenua – Landcare Research, New Zealand) ; Trinetta Chong (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley) ; Sébastien Annan-Phan (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Agricultural & Resource Economics, UC Berkeley) ; Esther Rolf (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Electrical Engineering & Computer Science, UC Berkeley) ; Yue 'Luna' Huang (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Agricultural & Resource Economics, UC Berkeley) ; Hannah Druckenmiller (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Agricultural & Resource Economics, UC Berkeley) ; Emma Krasovich (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley) ; Peiley Lau (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Agricultural & Resource Economics, UC Berkeley) ; Andrew Hultgren (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Agricultural & Resource Economics, UC Berkeley) ; Jaecheol Lee (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; Agricultural & Resource Economics, UC Berkeley) ; Solomon Hsiang (Global Policy Laboratory, Goldman School of Public Policy, UC Berkeley; National Bureau of Economic Research & Centre for Economic Policy Research) ;

Links

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Summary

Governments around the world are responding to the novel coronavirus (COVID-19) pandemic \cite{wu2020new} with unprecedented policies designed to slow the growth rate of infections. Many actions, such as closing schools and restricting populations to their homes, impose large and visible costs on society, but their benefits cannot be directly observed and are currently understood only through process-based simulations. Here, we compile new data on 1,717 local, regional, and national non-pharmaceutical interventions deployed in the ongoing pandemic across localities in China, South Korea, Italy, Iran, France, and the United States (US). We then apply reduced-form econometric methods, commonly used to measure the effect of policies on economic growth, 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 roughly 38% per day. We find that anti-contagion policies have significantly and substantially slowed this growth. Some policies have different impacts on different populations, but we obtain consistent evidence that the policy packages now deployed are achieving large, beneficial, and measurable health outcomes. We estimate that across these six countries, interventions prevented or delayed on the order of 62 million confirmed cases, corresponding to averting roughly 530 million total infections. These findings may help inform whether or when these policies should be deployed, intensified, or lifted, and they can support decision-making in the other 180+ countries where COVID-19 has been reported.

More information

• DOI: 10.5281/zenodo.3829194
• Language: en

Subjects

• COVID-19

Dates

• Publication date: 2020
• Issued: May 15, 2020

Rights

• info:eu-repo/semantics/openAccess Open Access

Format

electronic resource

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