PALUSAT projectis an initiative of the French Spatial Agency and the French Armed Forces Biomedical Research Institute. Main objective is to set up an operational predicting spatial and temporal tool for malaria risk using remote sensing information.

• Malaria epidemiology

The number of malaria cases, the exposed population and the spatial and temporal distribution of the disease are driven by 2 different types of factors: intrinsic and extrinsic. The intrinsic factors relate to the biology of the host or the anopheles mosquito vectors, as the acquired immunity of the population or the vector biological competence to transmit the parasite. The main extrinsic parameters are climatic, environmental and anthropological variables. They are key determinants of the availability and location of the larval habitats, the anopheles larvae and adult densities, their survival and capacity to transmit the parasite.

– Urbanization

Current estimates of the United Nations predict that half of the African population will live in urban areas by the year 2025. It is known that urbanization widely modifies the epidemiology of vector-borne diseases. A positive aspect of urbanization is a decrease of malaria incidence, as the environmental conditions are less favourable for transmission than in rural areas. On another hand, as the level of collective acquired immunity decreases, epidemics could arise, involving severe clinical episodes. In this context of epidemic malaria where transmission occurs in reduced places and time, risk mapping and implementation of early warning systems is of particular interest. Civilians and military personnel travelling in cities can also be exposed to malaria and the risk they can experience has to be better understood.

• Malaria and remote sensing data (more details in “Space and PALUSAT project”)

As extrinsic parameters of malaria epidemiology relate to climate and environment, some of them can be measured or evaluated by geospatial imagery. Numerous works have studied the link between remotely sensed data (satellite imagery and aerial photos) and different malaria parameters. Despite the growing urban population, few of them have undertaken the mapping of malaria in urban settings.

• Objectives

The objectives of the project are to:
— identify the distribution of the anopheline breeding sites,
— predict larval densities,
— predict adult (imago) densities,
— predict the transmission levels. The final goals are to:
— set up an operational predicting spatial and temporal tool for malaria risk in sub-Saharan African towns, using remote sensing information,
— provide important planning information on the likely level of malaria risk among nonimmune travellers and military personnel who could be briefly exposed to malaria transmission,
— provide important planning information to help to better focus control and prevention of malaria among the population living in sub-Saharan African cities.