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Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2

Intermediate host species provide a crucial link in the emergence of zoonotic infectious diseases, serving as a population where an emerging pathogen can mutate to become human-transmissible. Identifying such species is thus a key component of predicting and possibly mitigating future epidemics. Des...

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Detalles Bibliográficos
Autor principal: Royce, Katherine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier Ltd. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142741/
https://www.ncbi.nlm.nih.gov/pubmed/34044007
http://dx.doi.org/10.1016/j.jtbi.2021.110761
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author Royce, Katherine
author_facet Royce, Katherine
author_sort Royce, Katherine
collection PubMed
description Intermediate host species provide a crucial link in the emergence of zoonotic infectious diseases, serving as a population where an emerging pathogen can mutate to become human-transmissible. Identifying such species is thus a key component of predicting and possibly mitigating future epidemics. Despite this importance, intermediate host species have not been investigated in much detail, and have generally only been identified by testing for the presence of pathogens in multiple candidate species. In this paper, we present a mathematical model able to identify likely intermediate host species for emerging zoonoses based on ecological data for the candidates and epidemiological data for the pathogen. Since coronaviruses frequently emerge through intermediate host species and, at the time of writing, pose an urgent pandemic threat, we apply the model to the three emerging coronaviruses of the twenty-first century, accurately predicting palm civets as intermediate hosts for SARS-CoV-1 and dromedary camels as intermediate hosts for MERS. Further, we suggest mink, pangolins, and ferrets as intermediate host species for SARS-CoV-2. With the capacity to evaluate intermediate host likelihood among different species, researchers can focus testing for possible infection sources and interventions more effectively.
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spelling pubmed-81427412021-05-25 Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2 Royce, Katherine J Theor Biol Article Intermediate host species provide a crucial link in the emergence of zoonotic infectious diseases, serving as a population where an emerging pathogen can mutate to become human-transmissible. Identifying such species is thus a key component of predicting and possibly mitigating future epidemics. Despite this importance, intermediate host species have not been investigated in much detail, and have generally only been identified by testing for the presence of pathogens in multiple candidate species. In this paper, we present a mathematical model able to identify likely intermediate host species for emerging zoonoses based on ecological data for the candidates and epidemiological data for the pathogen. Since coronaviruses frequently emerge through intermediate host species and, at the time of writing, pose an urgent pandemic threat, we apply the model to the three emerging coronaviruses of the twenty-first century, accurately predicting palm civets as intermediate hosts for SARS-CoV-1 and dromedary camels as intermediate hosts for MERS. Further, we suggest mink, pangolins, and ferrets as intermediate host species for SARS-CoV-2. With the capacity to evaluate intermediate host likelihood among different species, researchers can focus testing for possible infection sources and interventions more effectively. Elsevier Ltd. 2021-10-07 2021-05-24 /pmc/articles/PMC8142741/ /pubmed/34044007 http://dx.doi.org/10.1016/j.jtbi.2021.110761 Text en © 2021 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Article
Royce, Katherine
Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2
title Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2
title_full Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2
title_fullStr Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2
title_full_unstemmed Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2
title_short Application of a novel mathematical model to identify intermediate hosts of SARS-CoV-2
title_sort application of a novel mathematical model to identify intermediate hosts of sars-cov-2
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8142741/
https://www.ncbi.nlm.nih.gov/pubmed/34044007
http://dx.doi.org/10.1016/j.jtbi.2021.110761
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