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

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.

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Publication Details

Journal
PLoS ONE
Published
2026-02-04
DOI
https://doi.org/10.1371/journal.pone.0340690
Primary Topic
Malaria Research and Control
Type
article
Field-Weighted Citation Impact
0.00
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article

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

Samuel Dadzie, Francis A. Adzei, Juhoe Kim, Masaki Umeda et al.
PLoS ONE
Malaria Research and Control
article

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

Samuel Dadzie, Francis A. Adzei, Juhoe Kim, Masaki Umeda, Godfred A. Bokpin
article en

Abstract

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.

PLoS ONEVol. 21(2)
Massachusetts Department of Public Health (US), University of Ghana (GH), Nagoya Institute of Technology (JP), Noguchi Memorial Institute for Medical Research (GH)
Openalex Percentile: Top 68%
Malaria Research and Control
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