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Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread
BACKGROUND: During the early stage of the COVID-19 pandemic, many countries implemented non-pharmaceutical interventions (NPIs) to control the transmission of SARS-CoV-2, the causative pathogen of COVID-19. Among those NPIs, stay-at-home and quarantine measures were widely adopted and enforced. Unde...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326419/ https://www.ncbi.nlm.nih.gov/pubmed/35896977 http://dx.doi.org/10.1186/s12879-022-07636-4 |
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author | Zhang, Renquan Wang, Yu Lv, Zheng Pei, Sen |
author_facet | Zhang, Renquan Wang, Yu Lv, Zheng Pei, Sen |
author_sort | Zhang, Renquan |
collection | PubMed |
description | BACKGROUND: During the early stage of the COVID-19 pandemic, many countries implemented non-pharmaceutical interventions (NPIs) to control the transmission of SARS-CoV-2, the causative pathogen of COVID-19. Among those NPIs, stay-at-home and quarantine measures were widely adopted and enforced. Understanding the effectiveness of stay-at-home and quarantine measures can inform decision-making and control planning during the ongoing COVID-19 pandemic and for future disease outbreaks. METHODS: In this study, we use mathematical models to evaluate the impact of stay-at-home and quarantine measures on COVID-19 spread in four cities that experienced large-scale outbreaks in the spring of 2020: Wuhan, New York, Milan, and London. We develop a susceptible-exposed-infected-removed (SEIR)-type model with components of self-isolation and quarantine and couple this disease transmission model with a data assimilation method. By calibrating the model to case data, we estimate key epidemiological parameters before lockdown in each city. We further examine the impact of stay-at-home and quarantine rates on COVID-19 spread after lockdown using counterfactual model simulations. RESULTS: Results indicate that self-isolation of susceptible population is necessary to contain the outbreak. At a given rate, self-isolation of susceptible population induced by stay-at-home orders is more effective than quarantine of SARS-CoV-2 contacts in reducing effective reproductive numbers [Formula: see text] . Variation in self-isolation and quarantine rates can also considerably affect the duration of outbreaks, attack rates and peak timing. We generate counterfactual simulations to estimate effectiveness of stay-at-home and quarantine measures. Without these two measures, the cumulative confirmed cases could be much higher than reported numbers within 40 days after lockdown in Wuhan, New York, Milan, and London. CONCLUSIONS: Our findings underscore the essential role of stay-at-home orders and quarantine of SARS-CoV-2 contacts during the early phase of the pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07636-4. |
format | Online Article Text |
id | pubmed-9326419 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-93264192022-07-27 Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread Zhang, Renquan Wang, Yu Lv, Zheng Pei, Sen BMC Infect Dis Research BACKGROUND: During the early stage of the COVID-19 pandemic, many countries implemented non-pharmaceutical interventions (NPIs) to control the transmission of SARS-CoV-2, the causative pathogen of COVID-19. Among those NPIs, stay-at-home and quarantine measures were widely adopted and enforced. Understanding the effectiveness of stay-at-home and quarantine measures can inform decision-making and control planning during the ongoing COVID-19 pandemic and for future disease outbreaks. METHODS: In this study, we use mathematical models to evaluate the impact of stay-at-home and quarantine measures on COVID-19 spread in four cities that experienced large-scale outbreaks in the spring of 2020: Wuhan, New York, Milan, and London. We develop a susceptible-exposed-infected-removed (SEIR)-type model with components of self-isolation and quarantine and couple this disease transmission model with a data assimilation method. By calibrating the model to case data, we estimate key epidemiological parameters before lockdown in each city. We further examine the impact of stay-at-home and quarantine rates on COVID-19 spread after lockdown using counterfactual model simulations. RESULTS: Results indicate that self-isolation of susceptible population is necessary to contain the outbreak. At a given rate, self-isolation of susceptible population induced by stay-at-home orders is more effective than quarantine of SARS-CoV-2 contacts in reducing effective reproductive numbers [Formula: see text] . Variation in self-isolation and quarantine rates can also considerably affect the duration of outbreaks, attack rates and peak timing. We generate counterfactual simulations to estimate effectiveness of stay-at-home and quarantine measures. Without these two measures, the cumulative confirmed cases could be much higher than reported numbers within 40 days after lockdown in Wuhan, New York, Milan, and London. CONCLUSIONS: Our findings underscore the essential role of stay-at-home orders and quarantine of SARS-CoV-2 contacts during the early phase of the pandemic. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12879-022-07636-4. BioMed Central 2022-07-27 /pmc/articles/PMC9326419/ /pubmed/35896977 http://dx.doi.org/10.1186/s12879-022-07636-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Zhang, Renquan Wang, Yu Lv, Zheng Pei, Sen Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread |
title | Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread |
title_full | Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread |
title_fullStr | Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread |
title_full_unstemmed | Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread |
title_short | Evaluating the impact of stay-at-home and quarantine measures on COVID-19 spread |
title_sort | evaluating the impact of stay-at-home and quarantine measures on covid-19 spread |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326419/ https://www.ncbi.nlm.nih.gov/pubmed/35896977 http://dx.doi.org/10.1186/s12879-022-07636-4 |
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