Abstract

BackgroundNon-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). However, empirical evidence of the effectiveness of specific NPIs has been inconsistent. We assessed the effectiveness of NPIs around internal containment and closure, international travel restrictions, economic measures, and health system actions on SARS-CoV-2 transmission in 130 countries and territories.MethodsWe used panel (longitudinal) regression to estimate the effectiveness of 13 categories of NPIs in reducing SARS-CoV-2 transmission using data from January to June 2020. First, we examined the temporal association between NPIs using hierarchical cluster analyses. We then regressed the time-varying reproduction number (Rt) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in Rt, levels of NPI intensity, time-varying changes in NPI effect, and variable selection criteria. Results were interpreted taking into account both the range of model specifications and temporal clustering of NPIs.ResultsThere was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced Rt. Another three NPIs (workplace closure, income support, and debt/contract relief) had strong evidence of effectiveness when ignoring their level of intensity, while two NPIs (public events cancellation, restriction on gatherings) had strong evidence of their effectiveness only when evaluating their implementation at maximum capacity (e.g. restrictions on 1000+ people gathering were not effective, restrictions on < 10 people gathering were). Evidence about the effectiveness of the remaining NPIs (stay-at-home requirements, public information campaigns, public transport closure, international travel controls, testing, contact tracing) was inconsistent and inconclusive. We found temporal clustering between many of the NPIs. Effect sizes varied depending on whether or not we included data after peak NPI intensity.ConclusionUnderstanding the impact that specific NPIs have had on SARS-CoV-2 transmission is complicated by temporal clustering, time-dependent variation in effects, and differences in NPI intensity. However, the effectiveness of school closure and internal movement restrictions appears robust across different model specifications, with some evidence that other NPIs may also be effective under particular conditions. This provides empirical evidence for the potential effectiveness of many, although not all, actions policy-makers are taking to respond to the COVID-19 pandemic.

Highlights

  • Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19)

  • Countries have used a range of non-pharmaceutical interventions (NPIs) such as testing suspected cases followed by isolation of confirmed cases and quarantine of their contacts, physical distancing measures such as schools and workplaces closures, income support for households affected by COVID19 and associated interventions, and domestic and international travel restrictions [3]

  • Statistical interpretation For both the any effort and the maximum effort scenarios, we examined a range of model specifications including (i) different variable selection criteria: AIC and BIC, (ii) different temporal lags between the timing of NPIs and changes in reproduction number (Rt), and (iii) different time series lengths: one ending on 22 June 2020 and the other truncated to 13 April 2020, when NPI intensity peaked

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Summary

Introduction

Non-pharmaceutical interventions (NPIs) are used to reduce transmission of SARS coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19). Countries have used a range of non-pharmaceutical interventions (NPIs) such as testing suspected cases followed by isolation of confirmed cases and quarantine of their contacts, physical distancing measures such as schools and workplaces closures, income support for households affected by COVID19 and associated interventions, and domestic and international travel restrictions [3]. These interventions aim to prevent infection introduction, contain outbreaks, and reduce peak epidemic size so that healthcare systems do not become overwhelmed. The psychological, social, and economic cost of interventions needs to be balanced against their potential effectiveness in reducing SARS-CoV-2 spread

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