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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 virus persistence one year after introduction.A fractional factorial design was used. Persistence in scenario a did not vary and is not shown here. Parameters contributing to more than 2% of the variance have been retained (no interaction contributed to more than 2% of the variance). See Table 1 for parameters, Fig 2 for scenario descriptions and S3 Fig for detailed parameter contributions.
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pone.0130838.g005: Parameter contributions to the variance of virus persistence one year after introduction.A fractional factorial design was used. Persistence in scenario a did not vary and is not shown here. Parameters contributing to more than 2% of the variance have been retained (no interaction contributed to more than 2% of the variance). See Table 1 for parameters, Fig 2 for scenario descriptions and S3 Fig for detailed parameter contributions.

Mentions: In the sensitivity analysis, in scenario a, persistence reached 100% in most simulations. Hence, the contribution of different parameters to the variation of this output could not be analysed. For the other scenarios, eight parameters contributed to more than 2% of the variance of the persistence one year after the introduction of the virus (Fig 5 and S3 Fig) and explained more than 70% of the variance. Parameters common to the three scenarios were host population size (NHint), biting rate (q), mortality rate of adult vectors (mV), carrying capacity of vectors in aquatic stage (KA) and transmission probability from hosts to vectors (cHV). They had a similar contribution except biting rate (q), which contributed twice more in scenarios b and c than in scenario d. Conversely, viraemia duration (1/ρ) contributed to almost half of the persistence variance (43%) in scenario d, much less (7%) in scenario c, and was negligible in scenario b. Parameter θ, controlling maximal emergence rate, was influential only in scenarios b and c. Renewal rate of vectors was influential only in scenario d and at a low level (4% of the variance). Persistence five years after the introduction of the virus depended, in scenario b, on exactly the same parameters as in the first year. It was impossible to conclude for scenario c as the output distribution was bimodal (near 0 or 100%) instead of normal, which is obligatory for analysis of variance. In scenario d, biting rate (q) and host viraemia duration (1/ρ) were the most influential parameters on persistence variance until year five (17% and 24% respectively).


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 virus persistence one year after introduction.A fractional factorial design was used. Persistence in scenario a did not vary and is not shown here. Parameters contributing to more than 2% of the variance have been retained (no interaction contributed to more than 2% of the variance). See Table 1 for parameters, 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.g005: Parameter contributions to the variance of virus persistence one year after introduction.A fractional factorial design was used. Persistence in scenario a did not vary and is not shown here. Parameters contributing to more than 2% of the variance have been retained (no interaction contributed to more than 2% of the variance). See Table 1 for parameters, Fig 2 for scenario descriptions and S3 Fig for detailed parameter contributions.
Mentions: In the sensitivity analysis, in scenario a, persistence reached 100% in most simulations. Hence, the contribution of different parameters to the variation of this output could not be analysed. For the other scenarios, eight parameters contributed to more than 2% of the variance of the persistence one year after the introduction of the virus (Fig 5 and S3 Fig) and explained more than 70% of the variance. Parameters common to the three scenarios were host population size (NHint), biting rate (q), mortality rate of adult vectors (mV), carrying capacity of vectors in aquatic stage (KA) and transmission probability from hosts to vectors (cHV). They had a similar contribution except biting rate (q), which contributed twice more in scenarios b and c than in scenario d. Conversely, viraemia duration (1/ρ) contributed to almost half of the persistence variance (43%) in scenario d, much less (7%) in scenario c, and was negligible in scenario b. Parameter θ, controlling maximal emergence rate, was influential only in scenarios b and c. Renewal rate of vectors was influential only in scenario d and at a low level (4% of the variance). Persistence five years after the introduction of the virus depended, in scenario b, on exactly the same parameters as in the first year. It was impossible to conclude for scenario c as the output distribution was bimodal (near 0 or 100%) instead of normal, which is obligatory for analysis of variance. In scenario d, biting rate (q) and host viraemia duration (1/ρ) were the most influential parameters on persistence variance until year five (17% and 24% respectively).

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