Members of the Anopheles gambiae complex are major malaria vectors in Africa. We tested the hypothesis that the range and relative abundance of the two major vectors in the complex, An. gambiae sensu stricto and An. arabiensis, could be defined by climate. Climate was characterized at mosquito survey sites by extracting data for each location from climate surfaces using a Geographical Information System. Annual precipitation, together with annual and wet season temperature, defined the ranges of both vectors and were used to map suitable climate zones. Using data from West Africa, we found that where the species were sympatric, An. gambiae s.s. predominated in saturated environments, and An. arabiensis was more common in sites subject to desiccation (r2 = 0.875, p < 0.001). We used the nonlinear equation that best described this relationship to map habitat suitability across Africa. This simple model predicted accurately the relative abundance of both vectors in Tanzania (rs = 0.745, p = 0.002), where species composition is highly variable. The combined maps of species' range and relative abundance showed very good agreement with published maps. This technique represents a new approach to mapping the distribution of malaria vectors over large areas and may facilitate species-specific vector control activities.

Dispersal is an ecological phenomenon which is of fundamental importance to population biology. While dispersal behaviour of many orders of winged insects has received a great deal of attention, the dispersal characteristics of odonates have been poorly documented. We used capture-mark-recapture techniques to study dispersal behaviour of seven species of odonates breeding on a network of 11 small ponds in Cheshire, U.K. The ponds ranged in size from 615 to 1300 m(2) and varied from 30 to 860 m apart. We found surprisingly high rates of dispersal between ponds, with 10-47% per species of recaptured individuals moving from their natal pond. The mean probability of dispersal differed significantly among species but the relationship between the probability of dispersal and distance moved consistently followed a simple negative exponential curve for all species. Most individuals stayed at their natal pond, but a few moved long distances. Neither the age at which an individual was marked (teneral vs sexually mature) nor its sex significantly affected its tendency to disperse. The negative exponential relationship suggests that dispersal should be relatively easy to incorporate in more complex models of odonate spatio-temporal dynamics. To our knowledge, this is the first large-scale, multi-species study to assess dispersal behaviour of odonates by direct observation.Peer reviewe

We investigated local-scale variation in malaria transmission and infection in children within a continuous landscape by retrospective spatial analysis of entomological and clinical data collected during 1988 and 1989 in The Gambia, West Africa. Parasite prevalence was negatively correlated with vector abundance and exposure to malaria parasites in 10 villages where entomological surveillance had been carried out. Variation in bednet use did not explain this finding. Mosquito-breeding habitat was retrospectively mapped using 20-m spatial resolution multispectral SPOT satellite imagery from 1988. From these data we estimated by linear regression the risk of exposure to malaria parasites in 26 villages where clinical surveys of children had been made. As exposure increased, so did parasite prevalence; but at higher levels of exposure, parasite prevalence declined. Our findings demonstrate marked differences in exposure to malaria in villages over distances of less than 2 km from mosquito breeding sites and suggest that there are also large differences in immunity between neighbouring settlements.

We investigated whether the risk of infection with malaria parasites was related to topography in the Usambara Mountains, Tanzania. Clinical surveys were carried out in seven villages, situated at altitudes from 300 m to 1650 m. Each village was mapped and incorporated into a Digital Terrain Model. Univariate analysis showed that the risk of splenomegaly declined with increasing altitude and with decreasing potential for water to accumulate. Logistic regression showed that altitude alone could correctly predict 73% of households where an occupant had an enlarged spleen or not. The inclusion of land where water is likely to accumulate within 400 m of each household increased the accuracy of the overall model slightly to 76%, but significantly improved predictions between 1000 m and 1200 m, where malaria is unstable, and likely to be epidemic. This novel approach illustrates how topography could help identify local areas prone to epidemics in the African highlands.

Lymphatic filariasis remains a major public health problem in Africa and is 1 of the World Health Organization's 6 diseases targeted for global eradication. However, no detailed maps of the geographical distribution of this disease exist, making it difficult to target control activities and quantify the population at risk. We hypothesized that the distribution lymphatic filariasis is governed by climate. The climate at sites in Africa where surveys for lymphatic filariasis had taken place was characterized using computerized climate surfaces. Logistic regression analysis of the climate variables predicted with 76% accuracy whether sites had microfilaraemic patients or not. We used the logistic equation in a geographical information system to map risk of lymphatic filariasis infection across Africa, which compared favourably with expert opinion. Further validation with a quasi-independent data set showed that the model predicted correctly 88% of infected sites. A similar procedure was used to map risk of microfilaraemia in Egypt, where the dominant vector species differs from those in sub-Saharan Africa. By overlaying risk maps on a 1990 population grid, and adjusting for recent population increases, we estimate that around 420 million people will be exposed to this infection in Africa in the year 2000. This approach could be used to produce a sampling frame, based on estimated risk of microfilaraemia, for conducting filariasis surveys in countries that lack accurate distribution maps and thus save on costs.