Geographical distributions of African malaria vector sibling species and evidence for insecticide resistance

Abstract

BackgroundMany of the mosquito species responsible for malaria transmission belong to a sibling complex; a taxonomic group of morphologically identical, closely related species. Sibling species often differ in several important factors that have the potential to impact malaria control, including their geographical distribution, resistance to insecticides, biting and resting locations, and host preference. The aim of this study was to define the geographical distributions of dominant malaria vector sibling species in Africa so these distributions can be coupled with data on key factors such as insecticide resistance to aid more focussed, species-selective vector control.ResultsWithin the Anopheles gambiae species complex and the Anopheles funestus subgroup, predicted geographical distributions for Anopheles coluzzii, An. gambiae (as now defined) and An. funestus (distinct from the subgroup) have been produced for the first time. Improved predicted geographical distributions for Anopheles arabiensis, Anopheles melas and Anopheles merus have been generated based on records that were confirmed using molecular identification methods and a model that addresses issues of sampling bias and past changes to the environment. The data available for insecticide resistance has been evaluated and differences between sibling species are apparent although further analysis is required to elucidate trends in resistance.ConclusionsSibling species display important variability in their geographical distributions and the most important malaria vector sibling species in Africa have been mapped here for the first time. This will allow geographical occurrence data to be coupled with species-specific data on important factors for vector control including insecticide resistance. Species-specific data on insecticide resistance is available for the most important malaria vectors in Africa, namely An. arabiensis, An. coluzzii, An. gambiae and An. funestus. Future work to combine these data with the geographical distributions mapped here will allow more focussed and resource-efficient vector control and provide information to greatly improve and inform existing malaria transmission models.Electronic supplementary materialThe online version of this article (doi:10.1186/s12936-017-1734-y) contains supplementary material, which is available to authorized users.

Novel Wolbachia strains in Anopheles malaria vectors from Sub-Saharan Africa

“…coluzzii extends further north, and closer to the coast than An. gambiae s.s. within west Africa [49]. In our study, high malaria prevalence rates in An.…”

Mapping Trends in Insecticide Resistance Phenotypes in African Malaria Vectors

“…For example, the distribution of An. arabiensis extends further south than other species in the complex 23 and this species is known to be more plastic in its feeding behaviour, biting outdoors and feeding on cattle 33 . Thus it is possible that selection for resistance in this species lags behind other members of the complex 35, 36, 37 .…”

“…gambiae complex sample that was tested. Our analysis only includes test results that are representative of the original sample collected 8, 27 , and our predictions cannot directly represent variation in the prevalence of resistance due to variation in the composition of sibling species 23,38 . Routine identification of the composition of sibling species in tested samples, and the provision of species-specific mortality values, would improve the capacity of susceptibility test data to inform prediction of resistance.…”

“…Relationships between resistance and drivers of selection will, however, vary geographically depending on population structure 20, 21 . Genetic mechanisms of resistance also differ across mosquito species 15, 20 , and even closely-related mosquito species have different ecological niches 22, 23 , as well as different blood feeding behaviour and preferences, meaning that they are likely to experience differences in insecticide exposure 24 .…”

Analysis-ready datasets for insecticide resistance phenotype and genotype frequency in African malaria vectors

“…First, because this allows accurate calculation of the Euclidian distances between points for analyses that exploit spatial correlations in the data 15, 28 . Secondly, precise location information allows accurate matching of the data to a wide range of environmental variables, such as climatic, socio-economic and intervention variables, to exploit relationships between the biological data and these environmental variables 29,30 . The use of data linked to wider areas is a current area of research aimed at improving model predictions in circumstances where data linked to precise locations are particularly sparse 31,32 .…”