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

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 pat- terns, from obligate persistence in a constant or tropical environment (without needing verti- cal 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 cli- mate, 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. Transmis- sion 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. (Résumé d'auteur

Seasonal and spatial heterogeneities in host and vector abundances impact the spatiotemporal spread of bluetongue

Bluetongue (BT) can cause severe livestock losses and large direct and indirect costs for farmers. To propose targeted control strategies as alternative to massive vaccination, there is a need to better understand how BT virus spread in space and time according to local characteristics of host and vector populations. Our objective was to assess, using a modelling approach, how spatiotemporal heterogeneities in abundance and distribution of hosts and vectors impact the occurrence and amplitude of local and regional BT epidemics. We built a reaction–diffusion model accounting for the seasonality in vector abundance and the active dispersal of vectors. Because of the scale chosen, and movement restrictions imposed during epidemics, host movements and wind-induced passive vector movements were neglected. Four levels of complexity were addressed using a theoretical approach, from a homogeneous to a heterogeneous environment in abundance and distribution of hosts and vectors. These scenarios were illustrated using data on abundance and distribution of hosts and vectors in a real geographical area. We have shown that local epidemics can occur earlier and be larger in scale far from the primary case rather than close to it. Moreover, spatial heterogeneities in hosts and vectors delay the epidemic peak and decrease the infection prevalence. The results obtained on a real area confirmed those obtained on a theoretical domain. Although developed to represent BTV spatiotemporal spread, our model can be used to study other vector-borne diseases of animals with a local to regional spread by vector diffusion

The MAELIA multi-agent platform for integrated assessment of low-water management issues

International audienceThe MAELIA project is developing an agent-based modeling and simulation platform to study the environmental, economic and social impacts of various regulations regarding water use and water management in combination with climate change. It is applied to the case of the French Adour-Garonne Basin, which is the most concerned in France by water scarcity during the low-water period. An integrated approach has been chosen to model this social-ecological system: the model combines spatiotemporal models of ecologic (e.g. rainfall and temperature changes, water flow and plant growth) and socio-economic (e.g. farmer decision-making process, management of low-water flow, demography, land use and land cover changes) processes and sub-models of cognitive sharing among agents (e.g. weather forecast, normative constraints on behaviors

Impact Assessment Modeling of Low-Water Management Policy

International audienceWe briefly present the main steps involved in designing and developing a platform for the numerical simulation of environmental and social impacts of the implementation of new environmental norms related to low-water management in France (MAELIA Project: multi-agents for environmental norms impact assessment). Some results are highlighted concerning in particular the structure of the underlying low-water management model and the process and agents' activity modeling

A metapopulation mechanistic model for Rift Valley Fever virus persistence within the Comoros archipelago

International audienc

Seasonal spread and control of Bluetongue in cattle

Bluetongue is a seasonal midge-borne disease of ruminants with economic consequences on herd productivity and animal trade. Recently, two new modes of transmission have been demonstrated in cattle for Bluetongue virus serotype 8 (BTV8): vertical and pseudo-vertical transmission. Our objective was to model the seasonal spread of BTV8 over several years in a homogeneous population of cattle, and to evaluate the effectiveness of vaccination strategies. We built a deterministic mathematical model accounting for the seasonality in vector abundance and all the modes of transmission. We proposed a counterpart of the basic reproduction number (R0) in a seasonal context (RS). Set A(t) is the number of secondary cases produced by a primary case introduced at time t. RS is the average of A(t). It is a function of midge abundance and vaccination strategy. We also used A*, the maximum of A(t), as an indicator of the risk of an epidemic. Without vaccination, the model predicted a large first epidemic peak followed by smaller annual peaks if RS>1. When RS1. Vaccination reduced RS and A* to less than one, but almost perfect vaccine efficacy and coverage were required to ensure no epidemics occurred. However, a lower coverage resulting in RS>1 could decrease infection prevalence. A further step would be to optimize vaccination strategies by targeting an appropriate period of the year to implement the vaccination

A metapopulation model to understand Rift Valley Fever persistence in the Comoros archipelago

National audienc

Rs, a counterpart of the basic reproduction number in a seasonal context

International audienc

Modeling and simulated a fungal disease epidemic over a heterogeneous plot

International audienc

Modeling and simulated a fungal disease epidemic over a heterogeneous plot

International audienc