Climate prediction of El Niño malaria epidemics in north-west Tanzania

Background: Malaria is a significant public health problem in Tanzania. Approximately 16 million

malaria cases are reported every year and 100,000 to 125,000 deaths occur. Although most of

Tanzania is endemic to malaria, epidemics occur in the highlands, notably in Kagera, a region that

was subject to widespread malaria epidemics in 1997 and 1998. This study examined the

relationship between climate and malaria incidence in Kagera with the aim of determining whether

seasonal forecasts may assist in predicting malaria epidemics.

Methods: A regression analysis was performed on retrospective malaria and climatic data during

each of the two annual malaria seasons to determine the climatic factors influencing malaria

incidence. The ability of the DEMETER seasonal forecasting system in predicting the climatic

anomalies associated with malaria epidemics was then assessed for each malaria season.

Results: It was found that malaria incidence is positively correlated with rainfall during the first

season (Oct-Mar) (R-squared = 0.73, p < 0.01). For the second season (Apr-Sep), high malaria

incidence was associated with increased rainfall, but also with high maximum temperature during

the first rainy season (multiple R-squared = 0.79, p < 0.01). The robustness of these statistical

models was tested by excluding the two epidemic years from the regression analysis. DEMETER

would have been unable to predict the heavy El Niño rains associated with the 1998 epidemic.

Nevertheless, this epidemic could still have been predicted using the temperature forecasts alone.

The 1997 epidemic could have been predicted from observed temperatures in the preceding

season, but the consideration of the rainfall forecasts would have improved the temperature-only

forecasts over the remaining years.

Conclusion: These results demonstrate the potential of a seasonal forecasting system in the

development of a malaria early warning system in Kagera region.