Abstract
BackgroundMalaria epidemics remain a serious threat to human populations living in the highlands of East Africa where transmission is unstable and climate sensitive. An existing early malaria epidemic prediction model required further development, validations and automation before its wide use and application in the region. The model has a lead-time of two to four months between the detection of the epidemic signal and the evolution of the epidemic. The validated models would be of great use in the early detection and prevention of malaria epidemics.MethodsConfirmed inpatient malaria data were collected from eight sites in Kenya, Tanzania and Uganda for the period 1995-2009. Temperature and rainfall data for the period 1960-2009 were collected from meteorological stations closest to the source of the malaria data. Process-based models were constructed for computing the risk of an epidemic in two general highland ecosystems using temperature and rainfall data. The sensitivity, specificity and positive predictive power were used to validate the models.ResultsDepending on the availability and quality of the malaria and meteorological data, the models indicated good functionality at all sites. Only two sites in Kenya had data that met the criteria for the full validation of the models. The additive model was found most suited for the poorly drained U-shaped valley ecosystems while the multiplicative model was most suited for the well-drained V-shaped valley ecosystem. The +18°C model was adaptable to any of the ecosystems and was designed for conditions where climatology data were not available. The additive model scored 100% for sensitivity, specificity and positive predictive power. The multiplicative model had a sensitivity of 75% specificity of 99% and a positive predictive power of 86%.ConclusionsThe additive and multiplicative models were validated and were shown to be robust and with high climate-based, early epidemic predictive power. They are designed for use in the common, well- and poorly drained valley ecosystems in the highlands of East Africa.Electronic supplementary materialThe online version of this article (doi:10.1186/1475-2875-13-329) contains supplementary material, which is available to authorized users.
Highlights
Malaria epidemics remain a serious threat to human populations living in the highlands of East Africa where transmission is unstable and climate sensitive
Epidemic threshold An epidemic was defined as a 100% or a twofold or greater increase in confirmed malaria cases above the long term mean
Medical facilities are overwhelmed by number of cases during an epidemic and this can lead to high mortality
Summary
Malaria epidemics remain a serious threat to human populations living in the highlands of East Africa where transmission is unstable and climate sensitive. The validated models would be of great use in the early detection and prevention of malaria epidemics. In the highlands of East Africa, climate and weather are major drivers of malaria transmission [2]. Climate change and variability can cause local temperatures to shift above the 18°C threshold creating suitable malaria transmission conditions. Events such as the 1997–8 El Niño that caused severe epidemics in the East African highlands was associated with 4°C anomalies in the mean monthly maximum temperatures [9], which would have driven the 18°C mean temperature to 22°C. Concurrent with heavy rainfall, this event caused server malaria epidemics in the East African highlands [10]
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