The effects of large-scale anti-contagion policies, such as lockdowns and travel restrictions, that have been implemented by governments to slow down the rate of infections with SARS-CoV-2 are quantified for six countries in a paper. The authors use econometric methods to determine the health benefits of these policies, and find that the interventions may have prevented or delayed around 62m confirmed cases of COVID-19 across the six countries.
Throughout the current pandemic, governments worldwide have introduced diverse social policies – which can have considerable social and economic costs – including lockdowns, travel restrictions and closures of schools and businesses. These measures try to reduce the transmission of the SARS-CoV-2 virus by limiting contact among people. However, although epidemiological modelling can inform decisions about which measures to adopt, the direct assessment of the effects of these policies on infection rates is challenging.
Solomon Hsiang and colleagues at the Global Policy Laboratory, Goldman School of Public Policy, University of California – Berkeley and the National Bureau of Economic Research & Centre for Economic Policy Research at Cambridge, analysed data on the daily infection rates of SARS-CoV-2, COVID-19 case definitions and the timing of anti-contagion policies implemented up until 6 April 2020 in China, South Korea, Italy, Iran, France and the US. They compared the infection growth rates before and after the implementation of more than 1,700 local, regional and national policies in these countries.
They found that without anti-contagion policies in place, early infection rates of SARS-CoV-2 grew by 68% per day in Iran and an average of 38% per day across the other five countries. Using econometric modelling typically applied to assessing how policies affect economic growth, the authors show that large-scale social policies have substantially slowed the growth rate of SARS-CoV-2 infections, with measurable beneficial health outcomes in most cases. They estimate that across the six studied countries, the policy packages prevented or delayed some 62m confirmed cases, corresponding to averting around 530m total infections.
The authors suggest that they will be able to further refine their findings as more regional data become available, but when combined with epidemiological simulations, these empirical observations could help to inform governments as they evaluate whether and when to extend or lift these policies.
Abstract
Governments around the world are responding to the novel coronavirus (COVID-19) pandemic1 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 simulations2–4. 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 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 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.
Authors
Solomon Hsiang, Daniel Allen, Sébastien Annan-Phan, Kendon Bell, Ian Bolliger, Trinetta Chong, Hannah Druckenmiller, Luna Yue Huang, Andrew Hultgren, Emma Krasovich, Peiley Lau, Jaecheol Lee, Esther Rolf, Jeanette Tseng, Tiffany Wu
[link url="https://www.nature.com/articles/s41586-020-2404-8"]Nature abstract[/link]