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The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories
BACKGROUND: Non-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 aroun...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861967/ https://www.ncbi.nlm.nih.gov/pubmed/33541353 http://dx.doi.org/10.1186/s12916-020-01872-8 |
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author | Liu, Yang Morgenstern, Christian Kelly, James Lowe, Rachel Jit, Mark |
author_facet | Liu, Yang Morgenstern, Christian Kelly, James Lowe, Rachel Jit, Mark |
author_sort | Liu, Yang |
collection | PubMed |
description | BACKGROUND: Non-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. METHODS: We 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 (R(t)) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in R(t), 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. RESULTS: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced R(t). 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. CONCLUSION: Understanding 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-020-01872-8. |
format | Online Article Text |
id | pubmed-7861967 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-78619672021-02-05 The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories Liu, Yang Morgenstern, Christian Kelly, James Lowe, Rachel Jit, Mark BMC Med Research Article BACKGROUND: Non-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. METHODS: We 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 (R(t)) of COVID-19 against different NPIs. We examined different model specifications to account for the temporal lag between NPIs and changes in R(t), 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. RESULTS: There was strong evidence for an association between two NPIs (school closure, internal movement restrictions) and reduced R(t). 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. CONCLUSION: Understanding 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. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12916-020-01872-8. BioMed Central 2021-02-05 /pmc/articles/PMC7861967/ /pubmed/33541353 http://dx.doi.org/10.1186/s12916-020-01872-8 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Article Liu, Yang Morgenstern, Christian Kelly, James Lowe, Rachel Jit, Mark The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories |
title | The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories |
title_full | The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories |
title_fullStr | The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories |
title_full_unstemmed | The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories |
title_short | The impact of non-pharmaceutical interventions on SARS-CoV-2 transmission across 130 countries and territories |
title_sort | impact of non-pharmaceutical interventions on sars-cov-2 transmission across 130 countries and territories |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7861967/ https://www.ncbi.nlm.nih.gov/pubmed/33541353 http://dx.doi.org/10.1186/s12916-020-01872-8 |
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