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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...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7529244 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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