ABSTRACT
In 2005, a serological study was carried out on horses in five ecologically contrasted zones of the Senegal River basin (Senegal) to assess West Nile virus (WNV) transmission and investigate underlying environmental risk factors. In each study zone, horses were randomly selected and blood samples taken. A land-cover map of the five study areas was built using two satellite ETM+ images. Blood samples were screened by ELISA for anti-WNV IgM and IgG and positive samples were confirmed by seroneutralization. Environmental data were analysed using a principal components analysis. The overall IgG seroprevalence rate was 85% (n=367; 95% CI 0.81-0.89). The proximity to sea water, flooded banks and salted mudflats were identified as protective factors. These environmental components are unfavourable to the presence of Culex mosquitoes suggesting that in Senegal, the distribution of the vector species is more limiting for WNV transmission than for the hosts' distribution.
Subject(s)
Horse Diseases/epidemiology , West Nile Fever/veterinary , Animals , Antibodies, Viral/blood , Culex/physiology , Culex/virology , Demography , Ecosystem , Environment , Horse Diseases/virology , Horses , Immunoglobulin G/blood , Insect Vectors/physiology , Insect Vectors/virology , Risk Factors , Rivers , Senegal/epidemiology , Seroepidemiologic Studies , West Nile Fever/epidemiology , West Nile virus/immunologyABSTRACT
The avian influenza (AI) epidemic is threatening Africa mainly because the flyways of migratory birds link the endemic and newly infected countries with disease-free areas in this continent and because of the risk of introduction through trade. Risk analysis provides a set of tools for supporting decision making by the veterinary services and other stakeholders, resulting in more effective surveillance and emergency preparedness. The risk assessment process could be split into three different steps: 1) risk release through the migratory birds and the official and unofficial poultry-product marketing chains; 2) risk exposure by means of studying interfaces among imported and exposed poultry and among wild and domestic birds; and 3) risk consequences for establishing the probability of AI spreading within the poultry population and the probability of it escaping detection. A conceptual framework is presented based on preliminary data and field missions carried out in Ethiopia. Field surveys and expert opinion will be necessary for the parameterization of the risk model. Spatial analysis will be used to identify high risk of exposure among wild and domestic birds. Risk communication and risk management will be based on the findings from the risk assessment model.
