SummaryThe aim of this study was to assess the accuracy of different methods of forecasting malaria incidence from historical morbidity patterns in areas with unstable transmission. We tested five methods using incidence data reported from health facilities in 20 areas in central and north-western Ethiopia. The accuracy of each method was determined by calculating errors resulting from the difference between observed incidence and corresponding forecasts obtained for prediction intervals of up to 12 months. Simple seasonal adjustment methods outperformed a statistically more advanced autoregressive integrated moving average method. In particular, a seasonal adjustment method that uses mean deviation of the last three observations from expected seasonal values consistently produced the best forecasts. Using 3 years' observation to generate forecasts with this method gave lower errors than shorter or longer periods. Incidence during the rainy months of June-August was the most predictable with this method. Forecasts for the normally dry months, particularly December-February, were less accurate. The study shows the limitations of forecasting incidence from historical morbidity patterns alone, and indicates the need for improved epidemic early warning by incorporating external predictors such as meteorological factors.keywords malaria, Ethiopia, epidemic early warning system, forecasting, time series analysis correspondence T. A. Abeku, Disease Control and Vector
Background: Malaria transmission in Ethiopia is unstable and seasonal, with the majority of the country's population living in malaria-prone areas. Results from DHS 2005 indicate that the coverage of key malaria interventions was low. The government of Ethiopia has set the national goal of full population coverage with a mean of 2 long-lasting insecticidal nets (LLINs) per household through distribution of about 20 million LLIN by the end of 2007. The aim of this study was to generate baseline information on malaria parasite prevalence and coverage of key malaria control interventions in Oromia and SNNPR and to relate the prevalence survey findings to routine surveillance data just before further mass distribution of LLINs.
Summaryobjective To determine whether the Koka water reservoir in the Rift Valley of Ethiopia contributes to the malaria burden in its vicinity.methods Frequency of malaria diagnosis in fever clinics was correlated with distance of residence from the margin of the Koka reservoir. Annual as well as seasonal malaria case rates were determined in cohorts residing < 3, 3-6 and 6-9 km from the reservoir. Plasmodium falciparum risk was compared with that of Plasmodium vivax. A multiple variable regression model was used to explore associations between malaria case rates and proximity to the reservoir, controlling for other suspected influences on malaria transmission.results Malaria case rates among people living within 3 km of the reservoir are about 1.5 times as great as for those living between 3 and 6 km from the reservoir and 2.3 times as great for those living 6-9 km from the reservoir. Proximity to the reservoir is associated with greater malaria case rates in periods of more intense transmission. Plasmodium falciparum is most prevalent in communities located close to the reservoir and P. vivax in more distant villages. The presence of the reservoir, coupled with inter-annual climatic variations, explains more than half of the region's variability in malaria case rates.conclusion Large water impoundments are likely to exacerbate malaria transmission in malariaendemic parts of sub-Saharan Africa.keywords malaria risk, large dam, impounded water, Ethiopia, Africa
The status of insecticide susceptibility of Anopheles arabiensis populations was monitored in northern and southern Ethiopia using one-to three-day-old mosquitoes reared from larval collections. Anopheles gambiae complex mosquitoes, identified by PCR as An. arabiensis, were exposed to diagnostic concentrations of DDT, malathion, fenitrothion, bendiocarb, propoxur and deltamethrin according to the standard WHO procedure. A heterogeneous and focal distribution of resistance phenotypes was observed in surveyed districts of the country. In Tach Armacho in northern Ethiopia, only resistance to DDT was detected. In the other two northern sites, An. arabiensis populations were susceptible to fenitrothion, resistant to malathion, propoxur and DDT and showed low levels of survival when exposed to bendiocarb requiring further investigations. In three areas of southern Ethiopia, An. arabiensis was susceptible to bendiocarb, propoxur and malathion, with low levels of survival on fenitrothion needing further confirmation. These samples were resistant to DDT and deltamethrin. Analyses for the knockdown resistant (kdr) mutations showed only the L1014F mutation was present with frequencies ranging from 68 to 100 %. The need for routine monitoring and surveillance as part of an insecticide resistance management programme is highlighted.
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