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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ftdoajarticles:oai:doaj.org/article:c77a64ce7d734fafa66b2e645858387c 2023-05-15T15:06:00+02:00 Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach. Raphaëlle Métras Guillaume Fournié Laure Dommergues Anton Camacho Lisa Cavalerie Philippe Mérot Matt J Keeling Catherine Cêtre-Sossah Eric Cardinale W John Edmunds 2017-07-01T00:00:00Z https://doi.org/10.1371/journal.pntd.0005767 https://doaj.org/article/c77a64ce7d734fafa66b2e645858387c EN eng Public Library of Science (PLoS) http://europepmc.org/articles/PMC5540619?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0005767 https://doaj.org/article/c77a64ce7d734fafa66b2e645858387c PLoS Neglected Tropical Diseases, Vol 11, Iss 7, p e0005767 (2017) Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 article 2017 ftdoajarticles https://doi.org/10.1371/journal.pntd.0005767 2022-12-31T03:26:02Z 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. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic PLOS Neglected Tropical Diseases 11 7 e0005767 |
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Open Polar |
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Directory of Open Access Journals: DOAJ Articles |
op_collection_id |
ftdoajarticles |
language |
English |
topic |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
spellingShingle |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 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. |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Public aspects of medicine RA1-1270 |
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 in Journal/Newspaper |
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 |
title |
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_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_sort |
drivers for rift valley fever emergence in mayotte: a bayesian modelling approach. |
publisher |
Public Library of Science (PLoS) |
publishDate |
2017 |
url |
https://doi.org/10.1371/journal.pntd.0005767 https://doaj.org/article/c77a64ce7d734fafa66b2e645858387c |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
PLoS Neglected Tropical Diseases, Vol 11, Iss 7, p e0005767 (2017) |
op_relation |
http://europepmc.org/articles/PMC5540619?pdf=render https://doaj.org/toc/1935-2727 https://doaj.org/toc/1935-2735 1935-2727 1935-2735 doi:10.1371/journal.pntd.0005767 https://doaj.org/article/c77a64ce7d734fafa66b2e645858387c |
op_doi |
https://doi.org/10.1371/journal.pntd.0005767 |
container_title |
PLOS Neglected Tropical Diseases |
container_volume |
11 |
container_issue |
7 |
container_start_page |
e0005767 |
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1766337679315697664 |