Abstract
BACKGROUND: Approximately 125 million travellers visit malaria-endemic countries annually and about 10,000 cases of malaria are reported after returning home. Due to the fact that malaria is insect vector transmitted, the environment is a key determinant of the spread of infection. Geo-climatic factors (such as temperature, moisture, water quality) determine the presence of Anopheles breeding sites, vector densities, adult mosquito survival rate, longevity and vector capacity. Several studies have shown the association between environmental factors and malaria incidence in autochthonous population. The association between the incidence of clinical malaria cases among non-immune travellers and environmental factors is yet to be evaluated. The objective of the present study was to identify, at a country scale (Ivory Coast), the environmental factors that are associated with clinical malaria among non-immune travellers, opening the way for a remote sensing-based counselling for malaria risk prevention among travellers. METHODS: The study sample consisted in 87 cohorts, including 4,531 French soldiers who travelled to Ivory Coast, during approximately four months, between September 2002 and December 2006. Their daily locations were recorded during the entire trip. The association between the incidence of clinical malaria and other factors (including individual, collective and environmental factors evaluated by remote sensing methods) was analysed in a random effect mixed Poisson regression model to take into account the sampling design. RESULTS: One hundred and forty clinical malaria cases were recorded during 572,363 person-days of survey, corresponding to an incidence density of 7.4 clinical malaria episodes per 1,000 person-months under survey. The risk of clinical malaria was significantly associated with the cumulative time spent in areas with NDVI > 0.35 (RR = 2,42), a mean temperature higher than 27°C (RR = 2,4), a longer period of dryness during the preceding month (RR = 0,275) and the cumulative time spent in urban areas (RR = 0,52). CONCLUSIONS: The present results suggest that remotely-sensed environmental data could be used as good predictors of the risk of clinical malaria among vulnerable individuals travelling through African endemic areas.