Work

Field evaluation of drone and AI assisted larval source management in Ghana

Year: 2026

Type: article

Abstract: BACKGROUND: Malaria remains a major public health burden in sub-Saharan Africa. In Ghana, in particular, larval source management (LSM) is increasingly recognized as a complementary vector control strategy. This study evaluates a field-adapted LSM approach that integrates drone-based mapping and artificial intelligence (AI)-driven site prioritization to enhance operational efficiency and reduce resource use. METHODS: The intervention replaces conventional manual scouting with aerial mapping conducted one day prior to larvicide application. An AI model analyzes geospatial and morphological features of water bodies to identify high-risk larval habitats. Site coordinates are transmitted to field teams via mobile devices for targeted treatment. A comparative field trial was conducted in eight administrative sub-districts within Ghana's Eastern Region. Four sub-districts implemented the drone- and AI-assisted approach, while four served as controls using standard LSM procedures. A mixed-methods evaluation was employed, incorporating quantitative metrics and qualitative field insights. RESULTS: Drone-assisted mapping led to more than a threefold increase in the number of identified breeding sites. AI-based targeting reduced larvicide consumption by over 60%. The combined technologies lowered worker requirements by approximately 50%. Despite these reductions, malaria case trends in the intervention sub-districts remained comparable to those in the control sub-districts. The study's limitations include its restriction to the dry season and below-average rainfall, which may have influenced mosquito abundance and transmission. CONCLUSIONS: Drone- and AI-assisted LSM demonstrated substantial resource savings without compromising vector control outcomes. Further longitudinal evaluation across transmission seasons is warranted to assess sustained effectiveness and inform national policy.

Source: PLoS ONE

DOI: 10.1371/journal.pone.0340690

Authors: Godfred A. Bokpin, Francis A. Adzei, Samuel Dadzie, Masaki Umeda, Juhoe Kim

Institutions: University of Ghana, Harvard University, Noguchi Memorial Institute for Medical Research

Language: English

Topic: Malaria Research and Control

Subfield: Public Health, Environmental and Occupational Health

Field: Medicine

Domain: Health Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure

Open Access status: gold

Estimated APC paid: $2,382