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Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach

Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the...

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Autores principales: Métras, Raphaëlle, Fournié, Guillaume, Dommergues, Laure, Camacho, Anton, Cavalerie, Lisa, Mérot, Philippe, Keeling, Matt J., Cêtre-Sossah, Catherine, Cardinale, Eric, Edmunds, W. John
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540619/
https://www.ncbi.nlm.nih.gov/pubmed/28732006
http://dx.doi.org/10.1371/journal.pntd.0005767
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author Métras, Raphaëlle
Fournié, Guillaume
Dommergues, Laure
Camacho, Anton
Cavalerie, Lisa
Mérot, Philippe
Keeling, Matt J.
Cêtre-Sossah, Catherine
Cardinale, Eric
Edmunds, W. John
author_facet Métras, Raphaëlle
Fournié, Guillaume
Dommergues, Laure
Camacho, Anton
Cavalerie, Lisa
Mérot, Philippe
Keeling, Matt J.
Cêtre-Sossah, Catherine
Cardinale, Eric
Edmunds, W. John
author_sort Métras, Raphaëlle
collection PubMed
description Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data.
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spelling pubmed-55406192017-08-12 Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach Métras, Raphaëlle Fournié, Guillaume Dommergues, Laure Camacho, Anton Cavalerie, Lisa Mérot, Philippe Keeling, Matt J. Cêtre-Sossah, Catherine Cardinale, Eric Edmunds, W. John PLoS Negl Trop Dis Research Article Rift Valley fever (RVF) is a major zoonotic and arboviral hemorrhagic fever. The conditions leading to RVF epidemics are still unclear, and the relative role of climatic and anthropogenic factors may vary between ecosystems. Here, we estimate the most likely scenario that led to RVF emergence on the island of Mayotte, following the 2006–2007 African epidemic. We developed the first mathematical model for RVF that accounts for climate, animal imports and livestock susceptibility, which is fitted to a 12-years dataset. RVF emergence was found to be triggered by the import of infectious animals, whilst transmissibility was approximated as a linear or exponential function of vegetation density. Model forecasts indicated a very low probability of virus endemicity in 2017, and therefore of re-emergence in a closed system (i.e. without import of infected animals). However, the very high proportion of naive animals reached in 2016 implies that the island remains vulnerable to the import of infectious animals. We recommend reinforcing surveillance in livestock, should RVF be reported is neighbouring territories. Our model should be tested elsewhere, with ecosystem-specific data. Public Library of Science 2017-07-21 /pmc/articles/PMC5540619/ /pubmed/28732006 http://dx.doi.org/10.1371/journal.pntd.0005767 Text en © 2017 Métras 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
Métras, Raphaëlle
Fournié, Guillaume
Dommergues, Laure
Camacho, Anton
Cavalerie, Lisa
Mérot, Philippe
Keeling, Matt J.
Cêtre-Sossah, Catherine
Cardinale, Eric
Edmunds, W. John
Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach
title Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach
title_full Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach
title_fullStr Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach
title_full_unstemmed Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach
title_short Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach
title_sort drivers for rift valley fever emergence in mayotte: a bayesian modelling approach
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5540619/
https://www.ncbi.nlm.nih.gov/pubmed/28732006
http://dx.doi.org/10.1371/journal.pntd.0005767
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