ArticleParasites & vectors2017
Using low-cost drones to map malaria vector habitats.
Article in Parasites & vectors, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 34 papers.
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Who cites it
34 citing papers in PubMed.
- Deep learning identifies water bodies from low-cost drone images for mosquito larval habitat mapping.Scientific reports · 2026Article
- High-resolution automated mapping of potential Aedes larval container habitats using drone imagery and supervised machine learning in Dar es Salaam, Tanzania.PLoS neglected tropical diseases · 2026Article
- EnhancingRemote sensing applications : society and environment · 2026Article
- Article
- New frontiers for unmanned aerial vehicles in planetary health research.BMC global and public health · 2026Review
- Article
- How technologies are driving digital innovation in mosquito surveillance systems: a global scoping review over the past decade.BMJ public health · 2026Article
- Comparison of unmanned aerial vehicle imaging to ground truth walkthroughs for identifying and classifying trash sites serving as potential Aedes aegypti breeding grounds.Parasites & vectors · 2025Article
- Larviciding for malaria control and elimination in Africa.Malaria journal · 2025Review
- The impact of Bacillus thuringiensis var. israelensis (VectobacMalaria journal · 2024Article
- Using image segmentation models to analyse high-resolution earth observation data: new tools to monitor disease risks in changing environments.International journal of health geographics · 2024Article
- Geospatial modelling of dry season habitats of the malaria vector, Anopheles funestus, in south-eastern Tanzania.Parasites & vectors · 2024Article
- Updates on traditional methods for combating malaria and emergingFrontiers in cellular and infection microbiology · 2024Review
- Cost and quality of operational larviciding using drones and smartphone technology.Malaria journal · 2023Article
- Sterilized Anopheles funestus can autodisseminate sufficient pyriproxyfen to the breeding habitat under semi-field settings.Malaria journal · 2023Article
- Mapping Malaria Vector Habitats in West Africa: Drone Imagery and Deep Learning Analysis for Targeted Vector Surveillance.Remote sensing · 2023Article
- Digitally managed larviciding as a cost-effective intervention for urban malaria: operational lessons from a pilot in São Tomé and Príncipe guided by the Zzapp system.Malaria journal · 2023Article
- Unmanned aerial vehicles for surveillance and control of vectors of malaria and other vector-borne diseases.Malaria journal · 2023Review
- The use of drones for mosquito surveillance and control.Parasites & vectors · 2022Review
- Smartphone-Based Multiplexed Biosensing Tools for Health Monitoring.Biosensors · 2022Review
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere 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.
resultsWith flying times of less than 30 min for each site, high-resolution (7 cm) georeferenced images were successfully generated for each of the seven sites, covering areas up to 30 ha. 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).
conclusionThe 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.
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