PREDICTING KEY MALARIA TRANSMISSION FACTORS, BITING AND ENTOMOLOGICALINOCULATION RATES, USING MODELED SOIL-MOISTURE IN KENYA

While malaria transmission varies seasonally, large inter-annual heter ogeneity of malaria incidence occurs. Variability in entomological par ameters, biting rates and entomological inoculation rates (EIR) have b een strongly associated with attack rates in children. The goal of thi s study was to assess the weather's impact on weekly biting and EIR in the endemic area of Kisian, Kenya. Entomological data collected by th e U.S. Army from March 1986 through June 1988 at Kisian, Kenya was ana lysed with concurrent weather data from nearby Kisumu airport. A soil moisture model of surface-water availability was used to combine multi ple weather parameters with landcover and soil features to improve dis ease prediction. Modelling soil moisture substantially improved predic tion of biting rates compared to rainfall; soil moisture lagged two we eks explained up to 45% of An. gambiae biting variability, compared to 8% for raw precipitation. For An. funestus, soil moisture explained 3 2% variability, peaking after a 4-week lag. The interspecies differenc e in response to soil moisture was significant (P < 0.00001). A satell ite normalized differential vegetation index (NDVI) of the study site yielded a similar correlation (r(2) = 0.42 An. gambiae). Modelled soil moisture accounted for up to 56% variability of Art. gambiae EIR, pea king at a lag of six weeks. The relationship between temperature and A n. gambiae biting rates was less robust; maximum temperature r(2) = -0 .20, and minimum temperature r(2) = 0.12 after lagging one week. Benef its of hydrological modelling ore compared to raw weather parameters a nd to satellite NDVI. These findings can improve both current malaria risk assessments and those based on El Nino forecasts or global climat e change model projections.