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The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one

Since COVID-19 spread globally in early 2020 and was declared a pandemic by the World Health Organization (WHO) in March, many countries are managing the local epidemics effectively through intervention measures that limit transmission. The challenges of immigration of new infections into regions an...

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Autores principales: Engen, Steinar, Tian, Huaiyu, Yang, Ruifu, Bjørnstad, Ottar N., Whittington, Jason D., Stenseth, Nils Chr.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187990/
https://www.ncbi.nlm.nih.gov/pubmed/34113453
http://dx.doi.org/10.1098/rsos.202234
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author Engen, Steinar
Tian, Huaiyu
Yang, Ruifu
Bjørnstad, Ottar N.
Whittington, Jason D.
Stenseth, Nils Chr.
author_facet Engen, Steinar
Tian, Huaiyu
Yang, Ruifu
Bjørnstad, Ottar N.
Whittington, Jason D.
Stenseth, Nils Chr.
author_sort Engen, Steinar
collection PubMed
description Since COVID-19 spread globally in early 2020 and was declared a pandemic by the World Health Organization (WHO) in March, many countries are managing the local epidemics effectively through intervention measures that limit transmission. The challenges of immigration of new infections into regions and asymptomatic infections remain. Standard deterministic compartmental models are inappropriate for sub- or peri-critical epidemics (reproductive number close to or less than one), so individual-based models are often used by simulating transmission from an infected person to others. However, to be realistic, these models require a large number of parameters, each with its own set of uncertainties and lack of analytic tractability. Here, we apply stochastic age-structured Leslie theory with a long history in ecological research to provide some new insights to epidemic dynamics fuelled by external imports. We model the dynamics of an epidemic when R(0) is below one, representing COVID-19 transmission following the successful application of intervention measures, and the transmission dynamics expected when infections migrate into a region. The model framework allows more rapid prediction of the shape and size of an epidemic to improve scaling of the response. During an epidemic when the numbers of infected individuals are rapidly changing, this will help clarify the situation of the pandemic and guide faster and more effective intervention.
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spelling pubmed-81879902021-06-09 The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one Engen, Steinar Tian, Huaiyu Yang, Ruifu Bjørnstad, Ottar N. Whittington, Jason D. Stenseth, Nils Chr. R Soc Open Sci Ecology, Conservation, and Global Change Biology Since COVID-19 spread globally in early 2020 and was declared a pandemic by the World Health Organization (WHO) in March, many countries are managing the local epidemics effectively through intervention measures that limit transmission. The challenges of immigration of new infections into regions and asymptomatic infections remain. Standard deterministic compartmental models are inappropriate for sub- or peri-critical epidemics (reproductive number close to or less than one), so individual-based models are often used by simulating transmission from an infected person to others. However, to be realistic, these models require a large number of parameters, each with its own set of uncertainties and lack of analytic tractability. Here, we apply stochastic age-structured Leslie theory with a long history in ecological research to provide some new insights to epidemic dynamics fuelled by external imports. We model the dynamics of an epidemic when R(0) is below one, representing COVID-19 transmission following the successful application of intervention measures, and the transmission dynamics expected when infections migrate into a region. The model framework allows more rapid prediction of the shape and size of an epidemic to improve scaling of the response. During an epidemic when the numbers of infected individuals are rapidly changing, this will help clarify the situation of the pandemic and guide faster and more effective intervention. The Royal Society 2021-06-09 /pmc/articles/PMC8187990/ /pubmed/34113453 http://dx.doi.org/10.1098/rsos.202234 Text en © 2021 The Authors. https://creativecommons.org/licenses/by/4.0/Published by the Royal Society under the terms of the Creative Commons Attribution License http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, provided the original author and source are credited.
spellingShingle Ecology, Conservation, and Global Change Biology
Engen, Steinar
Tian, Huaiyu
Yang, Ruifu
Bjørnstad, Ottar N.
Whittington, Jason D.
Stenseth, Nils Chr.
The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one
title The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one
title_full The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one
title_fullStr The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one
title_full_unstemmed The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one
title_short The ecological dynamics of the coronavirus epidemics during transmission from outside sources when R(0) is successfully managed below one
title_sort ecological dynamics of the coronavirus epidemics during transmission from outside sources when r(0) is successfully managed below one
topic Ecology, Conservation, and Global Change Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8187990/
https://www.ncbi.nlm.nih.gov/pubmed/34113453
http://dx.doi.org/10.1098/rsos.202234
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