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

• Published in: PloS one Vol. 16; no. 6; p. e0252827
• Main Authors: Banholzer, Nicolas, van Weenen, Eva, Lison, Adrian, Cenedese, Alberto, Seeliger, Arne, Kratzwald, Bernhard, Tschernutter, Daniel, Salles, Joan Puig, Bottrighi, Pierluigi, Lehtinen, Sonja, Feuerriegel, Stefan, Vach, Werner
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 02.06.2021; Public Library of Science (PLoS)
• Subjects: Bans; Bayes Theorem; Bayesian analysis; Biology and life sciences; Computer and Information Sciences; Coronaviruses; COVID-19; COVID-19 - prevention & control; Disease Outbreaks - prevention & control; Disease Outbreaks - statistics & numerical data; Disease transmission; Drafting software; Economics; Editing; Engineering and Technology; Environmental science; Environmental sciences; Epidemics; Epidemics - prevention & control; Epidemics - statistics & numerical data; Evaluation; Funding; Humans; Infections; Management; Medicine and Health Sciences; Methodology; People and places; Pharmaceuticals; Physical Distancing; Physical Sciences; Public health; Public health administration; Quarantine - methods; Quarantine - trends; Retrospective Studies; SARS-CoV-2 - pathogenicity; Severe acute respiratory syndrome coronavirus 2; Shelter in place; Social Sciences; Technology; Viral diseases; Visualization; Switzerland; Canada; Australia; United States > US; Norway
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0252827

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.