ArticleMalaria journal2023
Cost and quality of operational larviciding using drones and smartphone technology.
Article in Malaria journal, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 2 of them syntheses that pooled it.
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Who cites it
17 citing papers in PubMed, 2 syntheses or guidelines pooled it, 18 citations in OpenAlex.
- The role of artificial intelligence (AI) in the elimination of malaria: a systematic literature review.Malaria journal · 2025Pooled it
- The economic burden of malaria in Africa: a systematic review of cost of illness studies.Malaria journal · 2025Pooled it
- 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
- New frontiers for unmanned aerial vehicles in planetary health research.BMC global and public health · 2026Review
- Article
- A large-scale mosquito larviciding in Tanga Region, Tanzania, reduced mosquito densities to varying degrees across malaria transmission risk strata.Scientific reports · 2025Article
- A costing analysis of an intermittent biolarviciding intervention with limited epidemiological effect in Tanga Region, Tanzania.Malaria journal · 2025Article
- Large-scale intermittent larviciding intervention and associations with key malaria epidemiological parameters in Tanga Region, Tanzania.Malaria journal · 2025Article
- Anopheles arabiensis larval habitats characterization and Anopheles species diversity in water bodies from Jozini, KwaZulu-Natal Province.Malaria journal · 2025Article
- Elevating larval source management as a key strategy for controlling malaria and other vector-borne diseases in Africa.Parasites & vectors · 2025Review
- Larviciding for malaria control and elimination in Africa.Malaria journal · 2025Review
- The impact of Bacillus thuringiensis var. israelensis (VectobacMalaria journal · 2024Article
- Considerations for first field trials of low-threshold gene drive for malaria vector control.Malaria journal · 2024Review
- 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
- Updates on traditional methods for combating malaria and emergingFrontiers in cellular and infection microbiology · 2024Review
Corrections and comments
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Authors and funding
13 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundLarval Source Management (LSM) is an important tool for malaria vector control and is recommended by WHO as a supplementary vector control measure. LSM has contributed in many successful attempts to eliminate the disease across the Globe. However, this approach is typically labour-intensive, largely due to the difficulties in locating and mapping potential malarial mosquito breeding sites. Previous studies have demonstrated the potential for drone imaging technology to map malaria vector breeding sites. However, key questions remain unanswered related to the use and cost of this technology within operational vector control.
methodsUsing Zanzibar (United Republic of Tanzania) as a demonstration site, a protocol was collaboratively designed that employs drones and smartphones for supporting operational LSM, termed the Spatial Intelligence System (SIS). SIS was evaluated over a four-month LSM programme by comparing key mapping accuracy indicators and relative costs (both mapping costs and intervention costs) against conventional ground-based methods. Additionally, malaria case incidence was compared between the SIS and conventional study areas, including an estimation of the incremental cost-effectiveness of switching from conventional to SIS larviciding.
resultsThe results demonstrate that the SIS approach is significantly more accurate than a conventional approach for mapping potential breeding sites: mean % correct per site: SIS = 60% (95% CI 32-88%, p = 0.02), conventional = 18% (95% CI - 3-39%). Whilst SIS cost more in the start-up phase, overall annualized costs were similar to the conventional approach, with a simulated cost per person protected per year of $3.69 ($0.32 to $15.12) for conventional and $3.94 ($0.342 to $16.27) for SIS larviciding. The main economic benefits were reduced labour costs associated with SIS in the pre-intervention baseline mapping of habitats. There was no difference in malaria case incidence between the three arms. Cost effectiveness analysis showed that SIS is likely to provide similar health benefits at similar costs compared to the conventional arm.
conclusionsThe use of drones and smartphones provides an improved means of mapping breeding sites for use in operational LSM. Furthermore, deploying this technology does not appear to be more costly than a conventional ground-based approach and, as such, may represent an important tool for Malaria Control Programmes that plan to implement LSM.
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