Impact of non-pharmaceutical interventions on documented cases of COVID-19

Abstract

Background: The novel coronavirus (SARS-CoV-2) has rapidly evolved into a global epidemic. To control its spread, countries have implemented non-pharmaceutical interventions (NPIs), such as school or border closures, while others have even enforced a complete lockdown. Here we study the effectiveness of NPIs in reducing documented cases of COVID-19. Methods: We empirically estimate the impact of NPIs on documented COVID-19 cases in a cross-country analysis. A Bayesian hierarchical model with a time-delayed effect for each NPI allows us to quantify the relative reduction in the number of new cases attributed to each NPI. Based on this model, a cross-country analysis is performed using documented cases through April 15, 2020 from n = 20 countries (i.e., the United States, Canada, Australia, the EU-15 countries, Norway, and Switzerland). Documented case numbers are selected because they are essential for decision-makers in the area of health-policy when monitoring and evaluating current control mechanisms. Findings: Based on our model, we compare the effectiveness of NPIs up to now, i.e., in the early stages of the outbreak. Venue closures are associated with a reduction in the number of new cases by 36 % (95% credible interval [CrI] 20-48 %), closely * Corresponding author. † These authors contributed equally. : medRxiv preprint followed by gathering bans (34 %; 95% CrI 21-45 %), border closures (31 %; 95% CrI 19-42 %), and work bans on non-essential business activities (31 %; 95% CrI 16-44 %). Event bans lead to a slightly less pronounced reduction (23 %; 95% CrI 8-35 %). School closures (8 %; 95% CrI 0-23 %) and lockdowns (5 %; 95% CrI 0-14 %) appear to be the least effective among the NPIs considered in this analysis.Interpretation: This cross-country analysis provides early estimates regarding the effectiveness of different NPIs for controlling the COVID-19 epidemic. These findings are relevant for evaluating current health-policies and will be refined as more data becomes available.

Impact of policy interventions and social distancing on SARS-CoV-2 transmission in the United States

“…Retrospective analyses of NPI impact on disease spread, to date, have primarily consisted of cross-country analyses or focused on outcomes in China. 2,20,21,[23][24][25] In one comparison of 20 countries, Banholzer et al found public venue closures to be the most effective NPI in reducing new cases, followed by public gathering bans, non-essential business closures, and international travel restrictions, with school closures decreasing case count minimally. Interestingly, they found 'lockdowns' to be among the least effective policies in mitigating disease spread.…”

“…Mandated policies including limitations on mass gatherings, business closures, and stay-at-home orders have aimed to encourage social distancing and flatten the curve. [2][3][4] As of April 30, 2020, over 3,249,000 COVID-19 cases have been confirmed worldwide, with more than 1,067,000 cases and 62,000 resulting deaths in the United States. 5 In an effort to contain the virus, broad shutdowns have resulted in severe economic impacts including 26 million Americans filing for unemployment within a 5 week period.…”

“…[13][14][15][16][17][18][19] Recent reports have begun exploring the effectiveness of social distancing in reducing disease spread at the country level and local county level. 2,[20][21][22] Mandated NPIs have also been associated with reduced transmission of SARS-CoV-2 in Wuhan. 23 Further, the United States CDC has demonstrated that social distancing policies have reduced community mobility in Seattle, San Francisco, New York City, and New Orleans.…”

Impact of COVID-19 epidemic curtailment strategies in selected Indian states: an analysis by reproduction number and doubling time with incidence modelling

“…This reduction can mainly be explained by reduced number of contacts among people owing to movement restrictions. Studies on the impact of lockdown in other countries also reported reduction in reproductive number which translates in to flattening of the curve and delaying of peak (14)(15)(16)(17)(18)(19). Yet as mentioned earlier, the effective R0 estimations are dynamic and may change over age structure, time and nature of intervention.…”

A viral perspective on worldwide non-pharmaceutical interventions against COVID-19

“…These studies yielded conflicting conclusions. Depending on data sources and epidemiological model design assumptions, some studies identified lockdown (stay at home order) as the most effective intervention 5,9 while others found little additional impact, if any, compared to other interventions 4,6,10 . Epidemiological studies of interventions against an epidemic face several challenges.…”