Abstract
BackgroundMalaria epidemics remain a significant public health issue in the East African highlands. The aim of this study was to monitor temporal variations in vector densities in relation to changes in meteorological factors and malaria incidence at four highland sites in Kenya and Uganda and to evaluate the implications of these relationships for epidemic prediction and control.MethodsMosquitoes were collected weekly over a period of 47 months while meteorological variables and morbidity data were monitored concurrently. Mixed-effects Poisson regression was used to study the temporal associations of meteorological variables to vector densities and of the latter to incidence rates of Plasmodium falciparum.ResultsAnopheles gambiae s.s. was the predominant vector followed by Anopheles arabiensis. Anopheles funestus was also found in low densities. Vector densities remained low even during periods of malaria outbreaks. Average temperature in previous month and rainfall in previous two months had a quadratic and linear relationship with An. gambiae s.s. density, respectively. A significant statistical interaction was also observed between average temperature and rainfall in the previous month. Increases in densities of this vector in previous two months showed a linear relationship with increased malaria incidence.ConclusionAlthough epidemics in highlands often appear to follow abnormal weather patterns, interactions between meteorological, entomological and morbidity variables are complex and need to be modelled mathematically to better elucidate the system. This study showed that routine entomological surveillance is not feasible for epidemic monitoring or prediction in areas with low endemicity. However, information on unusual increases in temperature and rainfall should be used to initiate rapid vector surveys to assess transmission risk.
Highlights
Malaria epidemics remain a significant public health issue in the East African highlands
Past highland malaria epidemics have been shown to occur within defined altitudinal limits [9] and have often been linked causally to climatic anomalies [10,11], scientific knowledge of interactions between climate, vectors and disease has not yet reached a stage where it can directly contribute to the design of early warning systems
Climatic factors and morbidity clear differences exist in terms of average climate conditions (Table 1), temporal weather patterns were broadly consistent across the four sites (Figure 2)
Summary
Malaria epidemics remain a significant public health issue in the East African highlands. There is a well-recognized need to develop malaria early warning and detection systems in order to avert or reduce the negative impacts of epidemics in highland areas [2,3]. For such systems to be effective, the lead times they provide must be sufficient to allow for increased surveillance, planning of prevention and control measures and targeting of specific areas [4]. Researchers have attempted to build early warning models based on observed or predicted climate anomalies [5,6,7,8] This approach has shown some promise in certain epidemiological settings [7], but progress in developing climatebased models of malaria incidence in highland areas has been very limited. Vector density has been proposed as a suitable indicator of epidemic risk [12], but its practical use within routine monitoring systems has not been evaluated
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