The model uses predictions of climate variability to indicate the level of risk of an epidemic up to five months in advance of the peak malaria season ?the earliest point at which predictions have ever been made. The model will assist doctors and health care providers in preventing and controlling the disease.
Malaria is one of the world's deadliest diseases, killing more than one million people every year, as well as infecting a further 500 million worldwide. The mosquito-borne illness is endemic in several regions globally, but is most acute in Africa, home to an estimated 90 per cent of all cases.
Dr Andy Morse from the Department of Geography and colleagues from the European Centre for Medium Range Weather Forecasting; Columbia University, New York and the Ministry of Health in Botswana, based their early-warning model on population vulnerability, rainfall and health surveillance data and then used forthcoming season forecasts for rainfall to predict unusual changes in the seasonal pattern of disease in Botswana. The team based their study on Botswana as its climate makes it susceptible to malaria epidemics.
Dr Morse said: "The risk of an epidemic in tropical countries such as Botswana increases dramatically shortly after a season of good rainfall ?when the heat and humidity allow mosquito populations to thrive. By using a number of climate models, we were able to compose weather predictions for such countries, which could then be used to calculate the severity of an epidemic, months before its occurrence."
The team created a prediction system using seven, state-of-the-art, global climate models which produce weather forecasts up to six months in advance. The system allows researchers to assess the probable effect of weather conditions on a malaria epidemic.
The team's research is published in the latest issue of Nature.