Estimating the effects of non-pharmaceutical interventions on the number of new infections with COVID-19 during the first epidemic wave

Abstract

The novel coronavirus (SARS-CoV-2) has rapidly developed into a global epidemic. To control its spread, countries have implemented non-pharmaceutical interventions (NPIs), such as school closures, bans of small gatherings, or even stay-at-home orders. Here we study the effectiveness of seven NPIs in reducing the number of new infections, which was inferred from the reported cases of COVID-19 using a semi-mechanistic Bayesian hierarchical model. Based on data from the first epidemic wave of n = 20 countries (i.e., the United States, Canada, Australia, the EU-15 countries, Norway, and Switzerland), we estimate the relative reduction in the number of new infections attributed to each NPI. Among the NPIs considered, bans of large gatherings were most effective, followed by venue and school closures, whereas stay-at-home orders and work-from-home orders were least effective. With this retrospective cross-country analysis, we provide estimates regarding the effectiveness of different NPIs during the first epidemic wave.

No causal effect of school closures in Japan on the spread of COVID-19 in spring 2020

“…Because the numbers of cases are nonnegative integers (Supplementary Fig. 2 ), some studies rely on negative binomial regression 21 , 22 , 41 . Therefore, we also applied negative binomial regression to our matched data 52 , using the log of the population size as an offset variable so that various sized municipalities are comparable.…”

Understanding the effectiveness of government interventions against the resurgence of COVID-19 in Europe

“…Recall that our model requires external knowledge of the delay between infection and case confirmation as well as the delay between infection and death reporting. Many previous studies use estimates for delay distribution based on the data from the first wave 2 , 65 . However, these delay distributions may be different in the second wave due to sustained investment in testing capabilities and healthcare.…”

Surveillance of SARS-CoV-2 transmission in educational institutions, August to December 2020, Germany

“…Based on data from the first wave of COVID-19, a number of modelling studies provide inconclusive guidance to policy makers. While two publications, one from several countries and one from Switzerland [ 9 , 10 ], concluded that school closures contributed markedly to the reduction of SARS-CoV-2 transmission and individual mobility, respectively, two other studies, one using cross-country data and one from Japan rated school closures among the least effective measures to reduce COVID-19 incidence rates [ 11 , 12 ]. Accordingly, a recent review on SARS-CoV-2 setting-specific transmission rates concluded that there is ‘limited data to explore transmission patterns in […] schools […], highlighting the need for further research in such settings’ [ 13 ].…”