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Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination

Lassa virus is a significant burden on human health throughout its endemic region in West Africa, with most human infections the result of spillover from the primary rodent reservoir of the virus, the natal multimammate mouse, M. natalensis. Here we develop a Bayesian methodology for estimating epid...

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Autores principales: Nuismer, Scott L., Remien, Christopher H., Basinski, Andrew J., Varrelman, Tanner, Layman, Nathan, Rosenke, Kyle, Bird, Brian, Jarvis, Michael, Barry, Peter, Hanley, Patrick W., Fichet-Calvet, Elisabeth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529244/
https://www.ncbi.nlm.nih.gov/pubmed/32956349
http://dx.doi.org/10.1371/journal.pntd.0007920
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author Nuismer, Scott L.
Remien, Christopher H.
Basinski, Andrew J.
Varrelman, Tanner
Layman, Nathan
Rosenke, Kyle
Bird, Brian
Jarvis, Michael
Barry, Peter
Hanley, Patrick W.
Fichet-Calvet, Elisabeth
author_facet Nuismer, Scott L.
Remien, Christopher H.
Basinski, Andrew J.
Varrelman, Tanner
Layman, Nathan
Rosenke, Kyle
Bird, Brian
Jarvis, Michael
Barry, Peter
Hanley, Patrick W.
Fichet-Calvet, Elisabeth
author_sort Nuismer, Scott L.
collection PubMed
description Lassa virus is a significant burden on human health throughout its endemic region in West Africa, with most human infections the result of spillover from the primary rodent reservoir of the virus, the natal multimammate mouse, M. natalensis. Here we develop a Bayesian methodology for estimating epidemiological parameters of Lassa virus within its rodent reservoir and for generating probabilistic predictions for the efficacy of rodent vaccination programs. Our approach uses Approximate Bayesian Computation (ABC) to integrate mechanistic mathematical models, remotely-sensed precipitation data, and Lassa virus surveillance data from rodent populations. Using simulated data, we show that our method accurately estimates key model parameters, even when surveillance data are available from only a relatively small number of points in space and time. Applying our method to previously published data from two villages in Guinea estimates the time-averaged R(0) of Lassa virus to be 1.74 and 1.54 for rodent populations in the villages of Bantou and Tanganya, respectively. Using the posterior distribution for model parameters derived from these Guinean populations, we evaluate the likely efficacy of vaccination programs relying on distribution of vaccine-laced baits. Our results demonstrate that effective and durable reductions in the risk of Lassa virus spillover into the human population will require repeated distribution of large quantities of vaccine.
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spelling pubmed-75292442020-10-02 Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination Nuismer, Scott L. Remien, Christopher H. Basinski, Andrew J. Varrelman, Tanner Layman, Nathan Rosenke, Kyle Bird, Brian Jarvis, Michael Barry, Peter Hanley, Patrick W. Fichet-Calvet, Elisabeth PLoS Negl Trop Dis Research Article Lassa virus is a significant burden on human health throughout its endemic region in West Africa, with most human infections the result of spillover from the primary rodent reservoir of the virus, the natal multimammate mouse, M. natalensis. Here we develop a Bayesian methodology for estimating epidemiological parameters of Lassa virus within its rodent reservoir and for generating probabilistic predictions for the efficacy of rodent vaccination programs. Our approach uses Approximate Bayesian Computation (ABC) to integrate mechanistic mathematical models, remotely-sensed precipitation data, and Lassa virus surveillance data from rodent populations. Using simulated data, we show that our method accurately estimates key model parameters, even when surveillance data are available from only a relatively small number of points in space and time. Applying our method to previously published data from two villages in Guinea estimates the time-averaged R(0) of Lassa virus to be 1.74 and 1.54 for rodent populations in the villages of Bantou and Tanganya, respectively. Using the posterior distribution for model parameters derived from these Guinean populations, we evaluate the likely efficacy of vaccination programs relying on distribution of vaccine-laced baits. Our results demonstrate that effective and durable reductions in the risk of Lassa virus spillover into the human population will require repeated distribution of large quantities of vaccine. Public Library of Science 2020-09-21 /pmc/articles/PMC7529244/ /pubmed/32956349 http://dx.doi.org/10.1371/journal.pntd.0007920 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Nuismer, Scott L.
Remien, Christopher H.
Basinski, Andrew J.
Varrelman, Tanner
Layman, Nathan
Rosenke, Kyle
Bird, Brian
Jarvis, Michael
Barry, Peter
Hanley, Patrick W.
Fichet-Calvet, Elisabeth
Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination
title Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination
title_full Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination
title_fullStr Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination
title_full_unstemmed Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination
title_short Bayesian estimation of Lassa virus epidemiological parameters: Implications for spillover prevention using wildlife vaccination
title_sort bayesian estimation of lassa virus epidemiological parameters: implications for spillover prevention using wildlife vaccination
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7529244/
https://www.ncbi.nlm.nih.gov/pubmed/32956349
http://dx.doi.org/10.1371/journal.pntd.0007920
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