ArticlePloS one2015
A Stochastic Model to Study Rift Valley Fever Persistence with Different Seasonal Patterns of Vector Abundance: New Insights on the Endemicity in the Tropical Island of Mayotte.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Significance of vertical transmission of arboviruses in mosquito-borne disease epidemiology.Parasites & vectors · 2025Pooled it
- Mechanistic models of Rift Valley fever virus transmission: A systematic review.PLoS neglected tropical diseases · 2022Pooled it
- Rift Valley fever, Mauritania, 2020: Lessons from a one health approach.One health (Amsterdam, Netherlands) · 2022Article
- The role of livestock movements in the spread of Rift Valley fever virus in animals and humans in Mayotte, 2018-19.PLoS neglected tropical diseases · 2021Article
- Transient disease dynamics across ecological scales.Theoretical ecology · 2021Article
- Informing Rift Valley Fever preparedness by mapping seasonally varying environmental suitability.International journal of infectious diseases : IJID : official publication of the International Society for Infectious Diseases · 2020Article
- Estimation of Rift Valley fever virus spillover to humans during the Mayotte 2018-2019 epidemic.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
- Rift Valley Fever: risk of persistence, spread and impact in Mayotte (France).EFSA journal. European Food Safety Authority · 2020Article
- EMULSION: Transparent and flexible multiscale stochastic models in human, animal and plant epidemiology.PLoS computational biology · 2019Article
- Culicoides Latreille in the sun: faunistic inventory of Culicoides species (Diptera: Ceratopogonidae) in Mayotte (Comoros Archipelago, Indian Ocean).Parasites & vectors · 2019Article
- Drivers for Rift Valley fever emergence in Mayotte: A Bayesian modelling approach.PLoS neglected tropical diseases · 2017Article
- The Epidemiology of Rift Valley Fever in Mayotte: Insights and Perspectives from 11 Years of Data.PLoS neglected tropical diseases · 2016Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rift Valley fever (RVF) is a zoonotic vector-borne disease causing abortion storms in cattle and human epidemics in Africa. Our aim was to evaluate RVF persistence in a seasonal and isolated population and to apply it to Mayotte Island (Indian Ocean), where the virus was still silently circulating four years after its last known introduction in 2007. We proposed a stochastic model to estimate RVF persistence over several years and under four seasonal patterns of vector abundance. Firstly, the model predicted a wide range of virus spread patterns, from obligate persistence in a constant or tropical environment (without needing vertical transmission or reintroduction) to frequent extinctions in a drier climate. We then identified for each scenario of seasonality the parameters that most influenced prediction variations. Persistence was sensitive to vector lifespan and biting rate in a tropical climate, and to host viraemia duration and vector lifespan in a drier climate. The first epizootic peak was primarily sensitive to viraemia duration and thus likely to be controlled by vaccination, whereas subsequent peaks were sensitive to vector lifespan and biting rate in a tropical climate, and to host birth rate and viraemia duration in arid climates. Finally, we parameterized the model according to Mayotte known environment. Mosquito captures estimated the abundance of eight potential RVF vectors. Review of RVF competence studies on these species allowed adjusting transmission probabilities per bite. Ruminant serological data since 2004 and three new cross-sectional seroprevalence studies are presented. Transmission rates had to be divided by more than five to best fit observed data. Five years after introduction, RVF persisted in more than 10% of the simulations, even under this scenario of low transmission. Hence, active surveillance must be maintained to better understand the risk related to RVF persistence and to prevent new introductions.
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