Climate forecasts could help control disease outbreaks
of late , there has been much interest to understand the relationship between health and the El Nio phenomenon or the periodic warming of the Pacific waters. The catastrophic weather associated with El Nio - heavy rainfall, flooding or drought - can trigger severe disease outbreaks, notably malaria, cholera and diarrhoea. This is what happened in otherwise dry Wajir district of Kenya in early 1998. Peru also experienced the same after the 1982-83 event.
Now, scientists are keen to apply the rapidly-advancing science of seasonal forecasting to predict the occurrence of diseases. It is hoped that the health sector will be able to make good use of this information in health service planning ( Tiempo , No 33, September 1999).
Several mechanisms can explain the association between weather and disease, but the primary relationship is between rainfall and mosquitoes.Mosquito vectors transmit many diseases, such as malaria, and heavy rainfall normally increases their population and triggers an epidemic. However, it is important to understand the ecology of the local vector species in order to attempt some measure of control.
Vector-borne diseases occur in unprotected populations, which lack sufficient immunity and/or effective public health measures. It can be a serious problem especially in arid regions. Strong correlations have been found between annual rainfall, the number of rainy days and incidence of malaria in most districts of Rajasthan and Gujarat. A high incidence of malaria and excessive rainfall have been reported in the years following El Nio and during La Nina, which is the cooling of the Pacific waters after the El Nio phenomenon.
Because of the disease outbreaks associated with El Nio or La Nina effects, seasonal and annual climate forecasts may be of great importance in mitigating future epidemics, especially since it is now possible to predict the onset and progress of El Nio months ahead.
A pilot study concerned with the application of seasonal forecasting for malaria control was undertaken in the Southern Africa Development Community region in 1998 by the World Health Organisation ( who ). This approach utilises a consolidated forecast - an amalgamation of different models with regional expertise. The preliminary results were encouraging and, possibly for the first time, the meteorological department, agriculture and health delegates discussed their requirements at the same table. If the technology is to be applied in Africa, more work will have to be done is assessing the regions and seasons where the forecast models work. And once people are confident with the performance of such data, they can begin to actively assimilate it into their own activities and control programmes.
Probability forecasts of rainfall amounts have been used by the who sub-regional malaria control office in Harare, Zimbabwe during 1998-99. Such information was regarded as "very useful" in the coordination of malaria control activities. In the same way, many other countries around the world could benefit from early warning and epidemic preparedness. This could go a long way in controlling malaria as well as other diseases the world over.
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