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The fact that the weather conditions that enhance the outbreak of malaria are well known the predictability of this killer disease remains a challenge. RANET-Kenya, in keeping with its core activity notwithstanding, of reaching rural communities with information on weather and climate for improvement of quality of life, takes the initiative to develop malaria prediction models for application in specific zones of Kenya. This initiative, taken in collaboration with partners within the RANET (Radio Internet Project) multidisciplinary team will help operationalise the development, production and dissemination of malaria advisories to specific high-risk regions.

Malaria is a disease caused by the parasite Plasmodium. The infection is usually transmitted by the bite of an infected female Anopheles mosquito. Plasmodium falciparum is the commonest species in Kenya. It accounts for 98% of the cases and is associated with a lot of deaths if not treated. Other species which include Plasmodium malariae and Plasmodium ovale form up to 2% of the cases. Plasmodium vivax is very rare. Malarial features can vary from symptomless to mild or serious disease. Malaria is characterised clinically by chills, fever, joint pains, diarrhoea, mental confusion, nausea, vomiting, irritability, refusal to feed, and profuse sweating.

About 110m cases of malaria occur each year. More than 90m of these cases are from Sub-Saharan Africa where 1-2m die of the disease each year.

Locally, almost every Kenyan household is affected by the human suffering and financial hardship caused by malarial illness. Thirty percent of all outpatients in Kenya are due to malaria. It accounts for 19% of admissions, 5.1% of whom die from complications of the disease.

Kisii, Transmara, Nandi, Uasin Gishu, Trans Nzoia, Kericho and Bomet districts are among large areas of Kenya that are traditionally regarded as susceptible to epidemic malaria. These regions are virtually all situated at the Highlands West of the Rift Valley. Division of Malaria Control has identified six sentinel sites namely Bondo, Busia, Kirinyaga, Kisii/Gucha, Kwale and Makueni where incidence of malaria is closely monitored with defined thresholds that may signal epidemic outbreaks.

The geographical extent of malaria parasite is thought to be temperature limited, while the incidence of malaria is controlled by the length of the warm season. Climatic variability can affect mosquito vector abundance and longevity, rate of parasite development in mosquitoes and immunity and behaviour of the human population. Epidemic malaria transmission areas appear to be particularly sensitive to changes in weather conditions. These also tend to be areas lacking well co-ordinated control activities and therefore, it is here that predictions of weather changes as they relate to disease would be of particular use for malaria control planners.

In the epidemic zones, interventions are necessary only at specific points in time. A system which, indicates the best time to implement interventions, will assist control managers to make appropriate decisions on timely and effective interventions. This is where RANET Project of the Kenya Meteorological Department and collaborating health institutions come in. Predictive models for use as an early warning system for malaria in Kenya in general, and over unstable areas in particular, is urgently needed and the multidisciplinary team of RANET-Kenya is in the process of developing them.

Partnership has started within the RANET multidisciplinary team and includes KMD and Kenya Medical Research Institute (KEMRI). Other possible collaborators under the aegis of World Health Organisation (WHO) include Multilateral Initiative on Malaria (MIM), Roll Back Malaria (RBM), Health Information System (HIS) and Division of Malaria Control (DOMC).