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Geographic coincidence of increased malaria transmission hazard and vulnerability occurring at the periphery of two Tanzanian villages

Tanya L Russell123*, Dickson W Lwetoijera12, Bart GJ Knols4, Willem Takken5, Gerry F Killeen12 and Louise A Kelly-Hope6

Author Affiliations

1 Ifakara Health Institute, Environmental Sciences Thematic Group, Ifakara, Tanzania

2 Liverpool School of Tropical Medicine, Vector Group, Pembroke Place, Liverpool, UK

3 Faculty of Medicine, Health and Molecular Sciences, James Cook University, Cairns, Australia

4 In2Care BV, Costerweg 5, Wageningen, 6702 AA, The Netherlands

5 Laboratory of Entomology, Wageningen University and Research Centre, Wageningen, The Netherlands

6 Liverpool School of Tropical Medicine, Centre for Neglected Tropical Diseases, Pembroke Place, Liverpool, UK

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Malaria Journal 2013, 12:24  doi:10.1186/1475-2875-12-24

Published: 18 January 2013



The goal of malaria elimination necessitates an improved understanding of any fine-scale geographic variations in transmission risk so that complementary vector control tools can be integrated into current vector control programmes as supplementary measures that are spatially targeted to maximize impact upon residual transmission. This study examines the distribution of host-seeking malaria vectors at households within two villages in rural Tanzania.


Host-seeking mosquitoes were sampled from 72 randomly selected households in two villages on a monthly basis throughout 2008 using CDC light-traps placed beside occupied nets. Spatial autocorrelation in the dataset was examined using the Moran’s I statistic and the location of any clusters was identified using the Getis-Ord Gi* statistic. Statistical associations between the household characteristics and clusters of mosquitoes were assessed using a generalized linear model for each species.


For both Anopheles gambiae sensu lato and Anopheles funestus, the density of host-seeking females was spatially autocorrelated, or clustered. For both species, houses with low densities were clustered in the semi-urban village centre while houses with high densities were clustered in the periphery of the villages. Clusters of houses with low or high densities of An. gambiae s.l. were influenced by the number of residents in nearby houses. The occurrence of high-density clusters of An. gambiae s.l. was associated with lower elevations while An. funestus was also associated with higher elevations. Distance from the village centre was also positively correlated with the number of household occupants and having houses constructed with open eaves.


The results of the current study highlight that complementary vector control tools could be most effectively targeted to the periphery of villages where the households potentially have a higher hazard (mosquito densities) and vulnerability (open eaves and larger households) to malaria infection.