Development of an empirical model to predict malaria outbreaks based on monthly case reports and climate variables in Hefei, China, 1990-2011.

Malaria remains a significant public health concern in developing countries. Drivers of malaria transmission vary across different geographical regions. Climatic variables are major risk factor in seasonal and secular patterns of P. vivax malaria transmission along Anhui province. The study aims to forecast malaria outbreaks using empirical model developed in Hefei, China. Data on the monthly numbers of notified malaria cases and climatic factors were obtained for the period of January 1st 1990 to December 31st 2011 from the Hefei CDC and Anhui Institute of Meteorological Sciences, respectively. Two logistic regression models with time series seasonal decomposition were used to explore the impact of climatic and seasonal factors on malaria outbreaks. Sensitivity and specificity statistics were used for evaluating the predictive power. The results showed that relative humidity (OR = 1.171, 95% CI = 1.090-1.257), sunshine (OR = 1.076, 95% CI = 1.043-1.110) and barometric pressure (OR = 1.051, 95% CI = 1.003-1.100) were significantly associated with malaria outbreaks after adjustment for seasonality in Hefei area. The validation analyses indicated the overall agreement of 70.42% (sensitivity: 70.52%; specificity: 70.30%). The research suggested that the empirical model developed based on disease surveillance and climatic conditions may have applications in malaria control and prevention activities.