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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.

Cavalerie L, Charron MV, Ezanno P, Dommergues L, Zumbo B, Cardinale E - PLoS ONE (2015)

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: CRVOI, Centre de Recherche et de Veille sur les maladies émergentes dans l'Océan Indien, F-97490 Sainte Clotilde, La Réunion, France; CIRAD, UMR CMAEE, F-97490, Sainte Clotilde, France; INRA, UMR 1309 CMAEE, F-34398, Montpellier, France; AgroParisTech, F-75005, Paris, France; Université de la Réunion, F-97715 Saint Denis, La Réunion, France.

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.

No MeSH data available.


Related in: MedlinePlus

Parameter contributions to the variance of other model outputs.A fractional factorial design was used. To facilitate the interpretation, parameters contributing to more than 10% of the variance are shown. Model outputs are: the mean number of infected vectors in the aquatic stage in case of persistence (meanIA); the maximum proportion of infectious ruminants during the 1st and 2nd years in case of persistence (maxIH1vs. maxIH2); the mean proportion of recovered animals in case of persistence (meanRH) from the 2nd year until the end of the simulation. See Table 1 for parameters and Fig 2 for scenario descriptions and S3 Fig for detailed parameter contributions.
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pone.0130838.g006: Parameter contributions to the variance of other model outputs.A fractional factorial design was used. To facilitate the interpretation, parameters contributing to more than 10% of the variance are shown. Model outputs are: the mean number of infected vectors in the aquatic stage in case of persistence (meanIA); the maximum proportion of infectious ruminants during the 1st and 2nd years in case of persistence (maxIH1vs. maxIH2); the mean proportion of recovered animals in case of persistence (meanRH) from the 2nd year until the end of the simulation. See Table 1 for parameters and Fig 2 for scenario descriptions and S3 Fig for detailed parameter contributions.

Mentions: The contribution of parameter variations to the variance of other outputs is shown in Fig 6 and S3 Fig. In all scenarios, adult vector mortality (mV) was the main contributor to variance of the mean number of infected vectors in the aquatic stage (meanIA), which varied from 50 (scenario a) to 500 (scenario d). For this output only vertical transmission rate (α) was shown to be an influential parameter (>2%).


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.

Cavalerie L, Charron MV, Ezanno P, Dommergues L, Zumbo B, Cardinale E - PLoS ONE (2015)

Parameter contributions to the variance of other model outputs.A fractional factorial design was used. To facilitate the interpretation, parameters contributing to more than 10% of the variance are shown. Model outputs are: the mean number of infected vectors in the aquatic stage in case of persistence (meanIA); the maximum proportion of infectious ruminants during the 1st and 2nd years in case of persistence (maxIH1vs. maxIH2); the mean proportion of recovered animals in case of persistence (meanRH) from the 2nd year until the end of the simulation. See Table 1 for parameters and Fig 2 for scenario descriptions and S3 Fig for detailed parameter contributions.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4493030&req=5

pone.0130838.g006: Parameter contributions to the variance of other model outputs.A fractional factorial design was used. To facilitate the interpretation, parameters contributing to more than 10% of the variance are shown. Model outputs are: the mean number of infected vectors in the aquatic stage in case of persistence (meanIA); the maximum proportion of infectious ruminants during the 1st and 2nd years in case of persistence (maxIH1vs. maxIH2); the mean proportion of recovered animals in case of persistence (meanRH) from the 2nd year until the end of the simulation. See Table 1 for parameters and Fig 2 for scenario descriptions and S3 Fig for detailed parameter contributions.
Mentions: The contribution of parameter variations to the variance of other outputs is shown in Fig 6 and S3 Fig. In all scenarios, adult vector mortality (mV) was the main contributor to variance of the mean number of infected vectors in the aquatic stage (meanIA), which varied from 50 (scenario a) to 500 (scenario d). For this output only vertical transmission rate (α) was shown to be an influential parameter (>2%).

Bottom Line: 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.

View Article: PubMed Central - PubMed

Affiliation: CRVOI, Centre de Recherche et de Veille sur les maladies émergentes dans l'Océan Indien, F-97490 Sainte Clotilde, La Réunion, France; CIRAD, UMR CMAEE, F-97490, Sainte Clotilde, France; INRA, UMR 1309 CMAEE, F-34398, Montpellier, France; AgroParisTech, F-75005, Paris, France; Université de la Réunion, F-97715 Saint Denis, La Réunion, France.

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.

No MeSH data available.


Related in: MedlinePlus