Abstract
Abstract The World Health Organization (WHO) has highlighted identification and monitoring of vector populations as an important component of global vector-borne disease surveillance efforts. EO and RVF map data could play a crucial role in identifying risk locations for mosquito-borne diseases globally on the basis of habitat and climate variables. EO and RVF map data are also useful for measuring or mapping a range of environmental parameters that help determine mosquito vector occurrence and abundance and the rate of development of mosquito-borne parasites and pathogens in mosquito vectors. The EO and RVF map data have been sufficiently high spatial and temporal resolution, applied research could develop weather-based and environment-based forecasting of high-risk locations and time periods for mosquito-borne diseases using statistical models. The maps generated by this project indicate and outline the RVF risk areas associated with surface water ponding, mosquito breeding, and cattle grazing for a test area in Senegal. This strategy could include the following recommendations to effectively mitigate the exposure of cattle to RVF, and thus to minimise infection risk for humans: establish a joint communication strategy by integrating information of the forecasted risk bulletins into the National Information System of Surveillance of Epidemics used by the Ministry of Livestock in Senegal and the Headquarters of the Directorate of Veterinary Services of Senegal and its local representatives in rural districts, relocate livestock grazing areas away from risk zones, with warning signs in local languages posted near the ponds to inform breeders to keep their animals at least 500 m away from the ponds, and issue regular bulletins so the Directorate of Veterinary Services of Senegal can organise and optimise vaccination campaigns in the riskiest zones.