Malaria morbidity among school children living in two areas of contrasting transmission in western Kenya.

Research in malaria-endemic areas is usually focused on malaria during early childhood. Less is known about malaria among older school age children. The incidence of clinical attacks of malaria was monitored, using active case detection in primary schools, in two areas of western Kenya that differ in the intensity of transmission. Clinical malaria was more common in schools in the Nandi highlands, with a six-fold higher incidence of malaria attacks during the malaria epidemic in 2002, compared with school children living in a holoendemic area with intense perennial transmission during the same period. The high incidence coupled with the high parasite densities among cases is compatible with a low level of protective immunity in the highlands. The malaria incidence among school children exposed to intense year-round transmission (26 per 100 school children per year) was consistent with reports from other holoendemic areas. Taken together with other published studies, the data suggest that malaria morbidity among school age children increases as transmission intensity decreases. The implications for malaria control are discussed

Current status of insecticide resistance among malaria vectors in Kenya

Abstract Background Insecticide resistance has emerged as one of the major challenges facing National Malaria Control Programmes in Africa. A well-coordinated national database on insecticide resistance (IRBase) can facilitate the development of effective strategies for managing insecticide resistance and sustaining the effectiveness of chemical-based vector control measures. The aim of this study was to assemble a database on the current status of insecticide resistance among malaria vectors in Kenya. Methods Data was obtained from published literature through PubMed, HINARI and Google Scholar searches and unpublished literature from government reports, research institutions reports and malaria control programme reports. Each data source was assigned a unique identification code and entered into Microsoft Excel 2010 datasheets. Base maps on the distribution of insecticide resistance and resistance mechanisms among malaria vectors in Kenya were generated using ArcGIS Desktop 10.1 (ESRI, Redlands, CA, USA). Results Insecticide resistance status among the major malaria vectors in Kenya was reported in all the four classes of insecticides including pyrethroids, carbamates, organochlorines and organophosphates. Resistance to pyrethroids has been detected in Anopheles gambiae (s.s.), An. arabiensis and An. funestus (s.s.) while resistance to carbamates was limited to An. gambiae (s.s.) and An. arabiensis. Resistance to the organochlorine was reported in An. gambiae (s.s.) and An. funestus (s.s.) while resistance to organophosphates was reported in An. gambiae (s.l.) only. The mechanisms of insecticide resistance among malaria vectors reported include the kdr mutations (L 1014S and L 1014F) and elevated activity in carboxylesterase, glutathione S-transferases (GST) and monooxygenases. The kdr mutations L 1014S and L 1014F were detected in An. gambiae (s.s.) and An. arabiensis populations. Elevated activity of monooxygenases has been detected in both An. arabiensis and An. gambiae (s.s.) populations while the elevated activity of carboxylesterase and GST has been detected only in An. arabiensis populations. Conclusions The geographical maps show the distribution of insecticide resistance and resistance mechanisms among malaria vectors in Kenya. The database generated will provide a guide to intervention policies and programmes in the fight against malaria

Additional file 1: Figure S1. of Current status of insecticide resistance among malaria vectors in Kenya

Malaria vectors susceptibility status against permethrin. Figure S2. Malaria vectors susceptibility status against deltamethrin. Figure S3. Malaria vectors susceptibility status against lambda-cyhalothrin. Figure S4. Malaria vectors susceptibility status against alpha-cypermethrin. Figure S5. Malaria vectors susceptibility status against etofenprox. Figure S6. Malaria vectors susceptibility status against DDT. Figure S7. Malaria vectors susceptibility status against fenitrothion. Figure S8. Malaria vectors susceptibility status against malathion. Figure S9. Malaria vectors susceptibility status against bendiocarb. Figure S10. Malaria vectors susceptibility status against propoxur. (TIFF 9751 kb