Using low-cost drones to map malaria vector habitats

Abstract Background There is a growing awareness that if we are to achieve the ambitious goal of malaria elimination, we must compliment indoor-based vector control interventions (such as bednets and indoor spraying) with outdoor-based interventions such as larval source management (LSM). The effectiveness of LSM is limited by our capacity to identify and map mosquito aquatic habitats. This study provides a proof of concept for the use of a low-cost (< $1000) drone (DJI Phantom) for mapping water bodies in seven sites across Zanzibar including natural water bodies, irrigated and non-irrigated rice paddies, peri-urban and urban locations. Results With flying times of less than 30\ua0min for each site, high-resolution (7\ua0cm) georeferenced images were successfully generated for each of the seven sites, covering areas up to 30\ua0ha. Water bodies were readily identifiable in the imagery, as well as ancillary information for planning LSM activities (access routes to water bodies by road and foot) and public health management (e.g. identification of drinking water sources, mapping individual households and the nature of their construction). Conclusion The drone-based surveys carried out in this study provide a low-cost and flexible solution to mapping water bodies for operational dissemination of LSM initiatives in mosquito vector-borne disease elimination campaigns. Generated orthomosaics can also be used to provide vital information for other public health planning activities

Climate suitability for European ticks:Assessing species distribution models against null models and projection under AR5 climate

BACKGROUND: There is increasing evidence that the geographic distribution of tick species is changing. Whilst correlative Species Distribution Models (SDMs) have been used to predict areas that are potentially suitable for ticks, models have often been assessed without due consideration for spatial patterns in the data that may inflate the influence of predictor variables on species distributions. This study used null models to rigorously evaluate the role of climate and the potential for climate change to affect future climate suitability for eight European tick species, including several important disease vectors. METHODS: We undertook a comparative assessment of the performance of Maxent and Mahalanobis Distance SDMs based on observed data against those of null models based on null species distributions or null climate data. This enabled the identification of species whose distributions demonstrate a significant association with climate variables. Latest generation (AR5) climate projections were subsequently used to project future climate suitability under four Representative Concentration Pathways (RCPs). RESULTS: Seven out of eight tick species exhibited strong climatic signals within their observed distributions. Future projections intimate varying degrees of northward shift in climate suitability for these tick species, with the greatest shifts forecasted under the most extreme RCPs. Despite the high performance measure obtained for the observed model of Hyalomma lusitanicum, it did not perform significantly better than null models; this may result from the effects of non-climatic factors on its distribution. CONCLUSIONS: By comparing observed SDMs with null models, our results allow confidence that we have identified climate signals in tick distributions that are not simply a consequence of spatial patterns in the data. Observed climate-driven SDMs for seven out of eight species performed significantly better than null models, demonstrating the vulnerability of these tick species to the effects of climate change in the future. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13071-015-1046-4) contains supplementary material, which is available to authorized users

Automatic Detection of Open and Vegetated Water Bodies Using Sentinel 1 to Map African Malaria Vector Mosquito Breeding Habitats

Providing timely and accurate maps of surface water is valuable for mapping malaria risk and targeting disease control interventions. Radar satellite remote sensing has the potential to provide this information but current approaches are not suitable for mapping African malarial mosquito aquatic habitats that tend to be highly dynamic, often with emergent vegetation. We present a novel approach for mapping both open and vegetated water bodies using serial Sentinel-1 imagery for Western Zambia. This region is dominated by the seasonally inundated Upper Zambezi floodplain that suffers from a number of public health challenges. The approach uses open source segmentation and machine learning (extra trees classifier), applied to training data that are automatically derived using freely available ancillary data. Refinement is implemented through a consensus approach and Otsu thresholding to eliminate false positives due to dry flat sandy areas. The results indicate a high degree of accuracy (mean overall accuracy 92% st dev 3.6) providing a tractable solution for operationally mapping water bodies in similar large river floodplain unforested environments. For the period studied, 70% of the total water extent mapped was attributed to vegetated water, highlighting the importance of mapping both open and vegetated water bodies for surface water mapping

Geographically extensive larval surveys reveal an unexpected scarcity of primary vector mosquitoes in a region of persistent malaria transmission in western Zambia

Background The Barotse floodplains of the upper Zambezi River and its tributaries are a highly dynamic environment, with seasonal flooding and transhumance presenting a shifting mosaic of potential larval habitat and human and livestock bloodmeals for malaria vector mosquitoes. However, limited entomological surveillance has been undertaken to characterise the vector community in these floodplains and their environs. Such information is necessary as, despite substantial deployment of insecticide-treated nets (ITNs) and indoor residual spraying (IRS) against Anopheles vectors, malaria transmission persists across Barotseland in Zambia’s Western Province. Methods Geographically extensive larval surveys were undertaken in two health districts along 102 km of transects, at fine spatial resolution, during a dry season and following the peak of the successive wet season. Larvae were sampled within typical Anopheles flight range of human settlements and identified through genetic sequencing of cytochrome c oxidase I and internal transcribed spacer 2 regions of mitochondrial and nuclear DNA. This facilitated detailed comparison of taxon-specific abundance patterns between ecological zones differentiated by hydrological controls. Results An unexpected paucity of primary vectors was revealed, with An. gambiae s.l. and An. funestus representing <2% of 995 sequenced anophelines. Potential secondary vectors predominated in the vector community, primarily An. coustani group species and An squamosus. Whilst the distribution of An. gambiae s.l. in the study area was highly clustered, secondary vector species were ubiquitous across the landscape in both dry and wet seasons, with some taxon-specific relationships between abundance and ecological zones by season. Conclusions The diversity of candidate vector species and their high relative abundance observed across diverse hydro-ecosystems indicates a highly adaptable transmission system, resilient to environmental variation and, potentially, interventions that target only part of the vector community. Larval survey results imply that residual transmission of malaria in Barotseland is being mediated predominantly by secondary vector species, whose known tendencies for crepuscular and outdoor biting renders them largely insensitive to prevalent vector control methods