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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Main Authors: Raphaëlle Métras, Guillaume Fournié, Laure Dommergues, Anton Camacho, Lisa Cavalerie, Philippe Mérot, Matt J Keeling, Catherine Cêtre-Sossah, Eric Cardinale, W John Edmunds
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2017-07-01
Series:PLoS Neglected Tropical Diseases
Online Access:https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0005767&type=printable
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author Raphaëlle Métras
Guillaume Fournié
Laure Dommergues
Anton Camacho
Lisa Cavalerie
Philippe Mérot
Matt J Keeling
Catherine Cêtre-Sossah
Eric Cardinale
W John Edmunds
author_facet Raphaëlle Métras
Guillaume Fournié
Laure Dommergues
Anton Camacho
Lisa Cavalerie
Philippe Mérot
Matt J Keeling
Catherine Cêtre-Sossah
Eric Cardinale
W John Edmunds
author_sort Raphaëlle Métras
collection DOAJ
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.
format Article
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institution DOAJ
issn 1935-2727
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language English
publishDate 2017-07-01
publisher Public Library of Science (PLoS)
record_format Article
series PLoS Neglected Tropical Diseases
spelling doaj-art-c77a64ce7d734fafa66b2e645858387c2025-08-20T03:07:40ZengPublic Library of Science (PLoS)PLoS Neglected Tropical Diseases1935-27271935-27352017-07-01117e000576710.1371/journal.pntd.0005767Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach.Raphaëlle MétrasGuillaume FourniéLaure DommerguesAnton CamachoLisa CavaleriePhilippe MérotMatt J KeelingCatherine Cêtre-SossahEric CardinaleW John EdmundsRift 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.https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0005767&type=printable
spellingShingle Raphaëlle Métras
Guillaume Fournié
Laure Dommergues
Anton Camacho
Lisa Cavalerie
Philippe Mérot
Matt J Keeling
Catherine Cêtre-Sossah
Eric Cardinale
W John Edmunds
Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach.
PLoS Neglected Tropical Diseases
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
url https://journals.plos.org/plosntds/article/file?id=10.1371/journal.pntd.0005767&type=printable
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