Differential impact of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States

Abstract

Background The widespread pandemic of novel coronavirus disease 2019 (COVID-19) poses an unprecedented global health crisis. In the United States (US), different state governments have adopted various combinations of non-pharmaceutical public health interventions (NPIs), such as non-essential business closures and gathering bans, to mitigate the epidemic from February to April, 2020. Quantitative assessment on the effectiveness of NPIs is greatly needed to assist in guiding individualized decision making for adjustment of interventions in the US and around the world. However, the impacts of these approaches remain uncertain. Methods Based on the reported cases, the effective reproduction number (Rt) of COVID-19 epidemic for 50 states in the US was estimated. Measurements on the effectiveness of nine different NPIs were conducted by assessing risk ratios (RRs) between Rt and NPIs through a generalized linear model (GLM). Results Different NPIs were found to have led to different levels of reduction in Rt. Stay-at-home contributed approximately 51% (95% CI 46–57%), wearing (face) masks 29% (15–42%), gathering ban (more than 10 people) 19% (14–24%), non-essential business closure 16% (10–21%), declaration of emergency 13% (8–17%), interstate travel restriction 11% (5–16%), school closure 10% (7–14%), initial business closure 10% (6–14%), and gathering ban (more than 50 people) 7% (2–11%). Conclusions This retrospective assessment of NPIs on Rt has shown that NPIs played critical roles on epidemic control in the US in the past several months. The quantitative results could guide individualized decision making for future adjustment of NPIs in the US and other countries for COVID-19 and other similar infectious diseases.

Effectiveness of public health measures in reducing the incidence of covid-19, SARS-CoV-2 transmission, and covid-19 mortality: systematic review and meta-analysis

“…Specifically, a natural experiment across 200 countries showed 45.7% fewer covid-19 related mortality in countries where mask wearing was mandatory (table 1). 49 Another natural experiment study in the US reported a 29% reduction in SARS-CoV-2 transmission (measured as the time varying reproductive number Rt) (risk ratio 0.71, 95% confidence interval 0.58 to 0.75) in states where mask wearing was mandatory 58…”

“…All the studies that assessed stay at home or isolation measures reported reductions in transmission of SARS-CoV-2 (table 2). A retrospective cohort study from the US reported a significant reduction in the odds of having a positive reproductive number (R0) result (odds ratio 0.07, 95% confidence interval 0.01 to 0.37),41 and a natural experiment reported a 51% reduction in time varying reproductive number (Rt) (risk ratio 0.49, 95% confidence interval 0.43 to 0.54) 58…”

Mask use in community settings in the context of COVID-19: A systematic review of ecological data

“…All studies reported a protective benefit in terms of either reduced incidence, mortality, hospitalization, or a combination of these outcomes. This review summarized the literature up to March 2021, since which time a number of additional studies have reported a protective benefit impact of community mask wearing by the general public in community settings using ecological data [42] , [43] , [44] , [45] , [46] . While the results of these individual studies support the findings of this review, the large amount of research being done to assess community mask wearing warrants future systematic assessment.…”

Artificial intelligence for COVID-19: battling the pandemic with computational intelligence

“… Houston, Texas, May 1, 2020 – June 29, 2020 risk-stratified SIR-HCD The proposed model obtained lower mean squared error (MSE) and higher prediction accuracy compared to other models, and supports counterfactual analysis. Liu et al (May 2021) [150] investigate the influence (reproduction number) of non-pharmaceutical public health interventions on COVID-19 epidemics in the United States COVID Tracking Project ( https://covidtracking.com ) a generalized linear model (GLM) Different NPIs showed different levels of reproduction numbers. The stay-at-home played the most important role and contributed approximately 51% (95% CI 46%-57%).…”