Malaria and weather come under same umbrella
Weather forecasting models could provide early warnings of malaria epidemics.
Today's forecast predicts heavy showers and ... a chance of mosquitoes? That's the hope of scientists who have unveiled a weather forecasting computer model that can provide up to five months warning of malaria epidemics in the most vulnerable countries.
Malaria kills more than 1 million people each year, and infects a staggering 500 million people worldwide. Africa is home to about 90% of people affected by malaria, most of whom are part of a constant level of endemic cases. However, malaria epidemics can trigger a significant rise in cases and deaths at the local level, even though they account for only a small percentage of the world's total.
Because climate drives both the development of the malaria parasite, and the behaviour of the mosquitoes that carry it, weather forecasting can help to predict the likelihood of an outbreak.
In theory, an early warning of such epidemics should help governments and aid agencies to deploy anti-malarial drugs and bed nets to the regions most likely to be hit, along with strategic pesticide spraying.
"We can make better use of very limited resources to prevent outbreaks of these epidemics," said Tim Palmer, a climate modeller at the European Centre for Medium-Range Weather Forecasts in Reading, UK, and part of the research team that presents its forecasting system in this week's Nature1.
Degree of uncertainty
Previous climate models have been able to predict malaria epidemics up to one month in advance by analysing rainfall and sea surface temperatures2. In general, higher than average rainfall will lead to increased cases of malaria.
The new malaria forecast model relies on a technique known as ensemble forecasting, which combines several different climate models into one system to provide a more accurate prediction.
The team successfully used the model, developed as part of the EU-funded DEMETER project, to retrospectively predict malaria outbreaks in Botswana between 1982 and 2002.
The advantage of using ensemble forecasting is that it also delivers the uncertainty of that prediction, explains Palmer. That means that in years when strong predictions cannot be made, resources can be spread around a region more uniformly.
Catherine Dibble of the University of Maryland, College Park, who develops computer models of epidemics, agrees that this new system would allow healthcare workers to "hedge their bets" and to "get good information a lot sooner".
But Andrew Spielman, an expert in tropical diseases from Harvard University in Cambridge, Massachusetts, cautions that this model’s predictive power still needs to be tested on current epidemiological data.
Palmer now hopes that this modelling system could be used to predict outbreaks of other diseases that have climactic links, such as dengue fever, cholera and meningitis. It could also have an impact on agriculture, helping farmers to decide what types of crops to grow in the rainy season.
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- Thomson M. C, et al. Nature, 439 . 576 - 579 (2006).
- Thomson M. C, et al. Am. J. Trop. Med. Hyg., 73. 214 - 221 (2005).