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Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan

Recent outbreaks of coronavirus disease 2019 (COVID-19) has led a global pandemic cross the world. Most countries took two main interventions: suppression like immediate lockdown cities at epicenter or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both str...

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Autores principales: Yang, Po, Qi, Jun, Zhang, Shuhao, Wang, Xulong, Bi, Gaoshan, Yang, Yun, Sheng, Bin, Yang, Geng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7410247/
https://www.ncbi.nlm.nih.gov/pubmed/32760081
http://dx.doi.org/10.1371/journal.pone.0236857
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author Yang, Po
Qi, Jun
Zhang, Shuhao
Wang, Xulong
Bi, Gaoshan
Yang, Yun
Sheng, Bin
Yang, Geng
author_facet Yang, Po
Qi, Jun
Zhang, Shuhao
Wang, Xulong
Bi, Gaoshan
Yang, Yun
Sheng, Bin
Yang, Geng
author_sort Yang, Po
collection PubMed
description Recent outbreaks of coronavirus disease 2019 (COVID-19) has led a global pandemic cross the world. Most countries took two main interventions: suppression like immediate lockdown cities at epicenter or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both strategies have their apparent merits and limitations; it becomes extremely hard to conduct one intervention as the most feasible way to all countries. Targeting at this problem, this paper conducted a feasibility study by defining a mathematical model named SEMCR, it extended traditional SEIR (Susceptible-Exposed-Infectious-Recovered) model by adding two key features: a direct connection between Exposed and Recovered populations, and separating infections into mild and critical cases. It defined parameters to classify two stages of COVID-19 control: active contain by isolation of cases and contacts, passive contain by suppression or mitigation. The model was fitted and evaluated with public dataset containing daily number of confirmed active cases including Wuhan and London during January 2020 and March 2020. The simulated results showed that 1) Immediate suppression taken in Wuhan significantly reduced the total exposed and infectious populations, but it has to be consistently maintained at least 90 days (by the middle of April 2020). Without taking this intervention, we predict the number of infections would have been 73 folders higher by the middle of April 2020. Its success requires efficient government initiatives and effective collaborative governance for mobilizing of corporate resources to provide essential goods. This mode may be not suitable to other countries without efficient collaborative governance and sufficient health resources. 2) In London, it is possible to take a hybrid intervention of suppression and mitigation for every 2 or 3 weeks over a longer period to balance the total infections and economic loss. While the total infectious populations in this scenario would be possibly 2 times than the one taking suppression, economic loss and recovery of London would be less affected. 3) Both in Wuhan and London cases, one important issue of fitting practical data was that there were a portion (probably 62.9% in Wuhan) of self-recovered populations that were asymptomatic or mild symptomatic. This finding has been recently confirmed by other studies that the seroprevalence in Wuhan varied between 3.2% and 3.8% in different sub-regions. It highlights that the epidemic is far from coming to an end by means of herd immunity. Early release of intervention intensity potentially increased a risk of the second outbreak.
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spelling pubmed-74102472020-08-13 Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan Yang, Po Qi, Jun Zhang, Shuhao Wang, Xulong Bi, Gaoshan Yang, Yun Sheng, Bin Yang, Geng PLoS One Research Article Recent outbreaks of coronavirus disease 2019 (COVID-19) has led a global pandemic cross the world. Most countries took two main interventions: suppression like immediate lockdown cities at epicenter or mitigation that slows down but not stopping epidemic for reducing peak healthcare demand. Both strategies have their apparent merits and limitations; it becomes extremely hard to conduct one intervention as the most feasible way to all countries. Targeting at this problem, this paper conducted a feasibility study by defining a mathematical model named SEMCR, it extended traditional SEIR (Susceptible-Exposed-Infectious-Recovered) model by adding two key features: a direct connection between Exposed and Recovered populations, and separating infections into mild and critical cases. It defined parameters to classify two stages of COVID-19 control: active contain by isolation of cases and contacts, passive contain by suppression or mitigation. The model was fitted and evaluated with public dataset containing daily number of confirmed active cases including Wuhan and London during January 2020 and March 2020. The simulated results showed that 1) Immediate suppression taken in Wuhan significantly reduced the total exposed and infectious populations, but it has to be consistently maintained at least 90 days (by the middle of April 2020). Without taking this intervention, we predict the number of infections would have been 73 folders higher by the middle of April 2020. Its success requires efficient government initiatives and effective collaborative governance for mobilizing of corporate resources to provide essential goods. This mode may be not suitable to other countries without efficient collaborative governance and sufficient health resources. 2) In London, it is possible to take a hybrid intervention of suppression and mitigation for every 2 or 3 weeks over a longer period to balance the total infections and economic loss. While the total infectious populations in this scenario would be possibly 2 times than the one taking suppression, economic loss and recovery of London would be less affected. 3) Both in Wuhan and London cases, one important issue of fitting practical data was that there were a portion (probably 62.9% in Wuhan) of self-recovered populations that were asymptomatic or mild symptomatic. This finding has been recently confirmed by other studies that the seroprevalence in Wuhan varied between 3.2% and 3.8% in different sub-regions. It highlights that the epidemic is far from coming to an end by means of herd immunity. Early release of intervention intensity potentially increased a risk of the second outbreak. Public Library of Science 2020-08-06 /pmc/articles/PMC7410247/ /pubmed/32760081 http://dx.doi.org/10.1371/journal.pone.0236857 Text en © 2020 Yang et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yang, Po
Qi, Jun
Zhang, Shuhao
Wang, Xulong
Bi, Gaoshan
Yang, Yun
Sheng, Bin
Yang, Geng
Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan
title Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan
title_full Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan
title_fullStr Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan
title_full_unstemmed Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan
title_short Feasibility study of mitigation and suppression strategies for controlling COVID-19 outbreaks in London and Wuhan
title_sort feasibility study of mitigation and suppression strategies for controlling covid-19 outbreaks in london and wuhan
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7410247/
https://www.ncbi.nlm.nih.gov/pubmed/32760081
http://dx.doi.org/10.1371/journal.pone.0236857
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