Towards real-time prediction of Rift Valley fever epidemics in Africa

Abstract

Outbreaks of Rift Valley fever (RVF) virus in Africa are characterized by distinct spatial and temporal patterns that are directly related to specific environmental parameters associated with mosquito vectors that function in the maintenance (endemic) and transmission (epizootic) cycles of the virus. National Oceanic and Atmospheric Administration (NOAA) satellites with limited resolution (1 km) can indirectly measure rainfall inexpensively over subcontinental or continental areas at a high temporal frequency, and identify regions with a high potential for viral activity. Within regions of likely viral activity, mosquito vector-breeding habitats (dambos) are identified and mapped with archived, high-quality, cloud-free, higher resolution data from LANDSAT (thematic mapper resolution 30 m) and SPOT (multispectral resolution 20 m) satellites. Active sensors, like airborne synthetic aperture radar systems (range resolution 1.6 m), are capable of detecting flooded habitats, even through cloud cover. By identifying flooded habitats within regions with a high likelihood of RVF activity, the potential source foci of an outbreak may be detected close to real-time and control efforts implemented prior to the start of a RVF epidemic/epizootic.