Mapping malaria vector habitats in West Africa: drone imagery and deep learning analysis for targeted vector surveillance

Trujillano, F. et al. (2023) Mapping malaria vector habitats in West Africa: drone imagery and deep learning analysis for targeted vector surveillance. Remote Sensing, 15(11), 2775. (doi: 10.3390/rs15112775) (PMID:37324796) (PMCID:PMC7614662)

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Abstract

Disease control programs are needed to identify the breeding sites of mosquitoes, which transmit malaria and other diseases, in order to target interventions and identify environmental risk factors. The increasing availability of very-high-resolution drone data provides new opportunities to find and characterize these vector breeding sites. Within this study, drone images from two malaria-endemic regions in Burkina Faso and Côte d’Ivoire were assembled and labeled using open-source tools. We developed and applied a workflow using region-of-interest-based and deep learning methods to identify land cover types associated with vector breeding sites from very-high-resolution natural color imagery. Analysis methods were assessed using cross-validation and achieved maximum Dice coefficients of 0.68 and 0.75 for vegetated and non-vegetated water bodies, respectively. This classifier consistently identified the presence of other land cover types associated with the breeding sites, obtaining Dice coefficients of 0.88 for tillage and crops, 0.87 for buildings and 0.71 for roads. This study establishes a framework for developing deep learning approaches to identify vector breeding sites and highlights the need to evaluate how results will be used by control programs.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Johnson, Miss Emilia and Fornace, Dr Kimberly and Trujillano, Mrs Fedra
Authors: Trujillano, F., Jimenez Garay, G., Alatrista-Salas, H., Byrne, I., Nunez-del-Prado, M., Chan, K., Manrique, E., Johnson, E., Apollinaire, N., Kouame Kouakou, P., Oumbouke, W. A., Tiono, A. B., Guelbeogo, M. W., Lines, J., Carrasco-Escobar, G., and Fornace, K.
College/School:College of Medical Veterinary and Life Sciences > School of Biodiversity, One Health & Veterinary Medicine
Journal Name:Remote Sensing
Publisher:MDPI
ISSN:2072-4292
ISSN (Online):2072-4292
Published Online:26 May 2023
Copyright Holders:Copyright © 2023 The Authors
First Published:First published in Remote Sensing 15(11): 2775
Publisher Policy:Reproduced under a Creative Commons License
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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
310866Socio-ecological dynamics of zoonotic and vector-borne diseases in changing landscapes: implications for surveillance and controlKimberly FornaceWellcome Trust (WELLCOTR)221963/Z/20/ZInstitute of Biodiversity, Animal Health and Comparative Medicine
318118BBSRC IAA University of GlasgowGerard GrahamBiotechnology and Biological Sciences Research Council (BBSRC)BB/X511110/1III - Immunology