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Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study

BACKGROUND: Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases, such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual q...

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Autores principales: Peak, Corey M., Kahn, Rebecca, Grad, Yonatan H., Childs, Lauren M., Li, Ruoran, Lipsitch, Marc, Buckee, Caroline O.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239061/
https://www.ncbi.nlm.nih.gov/pubmed/32511440
http://dx.doi.org/10.1101/2020.03.05.20031088
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author Peak, Corey M.
Kahn, Rebecca
Grad, Yonatan H.
Childs, Lauren M.
Li, Ruoran
Lipsitch, Marc
Buckee, Caroline O.
author_facet Peak, Corey M.
Kahn, Rebecca
Grad, Yonatan H.
Childs, Lauren M.
Li, Ruoran
Lipsitch, Marc
Buckee, Caroline O.
author_sort Peak, Corey M.
collection PubMed
description BACKGROUND: Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases, such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual quarantine can more effectively control COVID-19 than active monitoring. As an epidemic grows, it is also important to consider when these interventions are no longer feasible, and broader mitigation measures must be implemented. METHODS: To estimate the comparative efficacy of these case-based interventions to control COVID-19, we fit a stochastic branching model to reported parameters for the dynamics of the disease. Specifically, we fit to the incubation period distribution and each of two sets of the serial interval distribution: a shorter one with a mean serial interval of 4.8 days and a longer one with a mean of 7.5 days. To assess variable resource settings, we consider two feasibility settings: a high feasibility setting with 90% of contacts traced, a half-day average delay in tracing and symptom recognition, and 90% effective isolation; and low feasibility setting with 50% of contacts traced, a two-day average delay, and 50% effective isolation. FINDINGS: Our results suggest that individual quarantine in high feasibility settings where at least three-quarters of infected contacts are individually quarantined contains an outbreak of COVID-19 with a short serial interval (4.8 days) 84% of the time. However, in settings where this performance is unrealistically high and the outbreak continues to grow, so too will the burden of the number of contacts traced for active monitoring or quarantine. When resources are prioritized for scalable interventions such as social distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to mitigation efforts. INTERPRETATION: Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission in order to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine vs. active monitoring of contacts. To the extent these interventions can be implemented they can help mitigate the spread of COVID-19.
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spelling pubmed-72390612020-06-07 Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study Peak, Corey M. Kahn, Rebecca Grad, Yonatan H. Childs, Lauren M. Li, Ruoran Lipsitch, Marc Buckee, Caroline O. medRxiv Article BACKGROUND: Voluntary individual quarantine and voluntary active monitoring of contacts are core disease control strategies for emerging infectious diseases, such as COVID-19. Given the impact of quarantine on resources and individual liberty, it is vital to assess under what conditions individual quarantine can more effectively control COVID-19 than active monitoring. As an epidemic grows, it is also important to consider when these interventions are no longer feasible, and broader mitigation measures must be implemented. METHODS: To estimate the comparative efficacy of these case-based interventions to control COVID-19, we fit a stochastic branching model to reported parameters for the dynamics of the disease. Specifically, we fit to the incubation period distribution and each of two sets of the serial interval distribution: a shorter one with a mean serial interval of 4.8 days and a longer one with a mean of 7.5 days. To assess variable resource settings, we consider two feasibility settings: a high feasibility setting with 90% of contacts traced, a half-day average delay in tracing and symptom recognition, and 90% effective isolation; and low feasibility setting with 50% of contacts traced, a two-day average delay, and 50% effective isolation. FINDINGS: Our results suggest that individual quarantine in high feasibility settings where at least three-quarters of infected contacts are individually quarantined contains an outbreak of COVID-19 with a short serial interval (4.8 days) 84% of the time. However, in settings where this performance is unrealistically high and the outbreak continues to grow, so too will the burden of the number of contacts traced for active monitoring or quarantine. When resources are prioritized for scalable interventions such as social distancing, we show active monitoring or individual quarantine of high-risk contacts can contribute synergistically to mitigation efforts. INTERPRETATION: Our model highlights the urgent need for more data on the serial interval and the extent of presymptomatic transmission in order to make data-driven policy decisions regarding the cost-benefit comparisons of individual quarantine vs. active monitoring of contacts. To the extent these interventions can be implemented they can help mitigate the spread of COVID-19. Cold Spring Harbor Laboratory 2020-04-26 /pmc/articles/PMC7239061/ /pubmed/32511440 http://dx.doi.org/10.1101/2020.03.05.20031088 Text en http://creativecommons.org/licenses/by/4.0/It is made available under a CC-BY 4.0 International license (http://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Peak, Corey M.
Kahn, Rebecca
Grad, Yonatan H.
Childs, Lauren M.
Li, Ruoran
Lipsitch, Marc
Buckee, Caroline O.
Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study
title Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study
title_full Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study
title_fullStr Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study
title_full_unstemmed Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study
title_short Comparative Impact of Individual Quarantine vs. Active Monitoring of Contacts for the Mitigation of COVID-19: a modelling study
title_sort comparative impact of individual quarantine vs. active monitoring of contacts for the mitigation of covid-19: a modelling study
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7239061/
https://www.ncbi.nlm.nih.gov/pubmed/32511440
http://dx.doi.org/10.1101/2020.03.05.20031088
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