Title
High-accuracy detection of malaria vector larval habitats using drone-based multispectral imagery
Date Issued
01 January 2019
Access level
open access
Resource Type
journal article
Publisher(s)
Public Library of Science
Abstract
Interest in larval source management (LSM) as an adjunct intervention to control and eliminate malaria transmission has recently increased mainly because long-lasting insecticidal nets (LLINs) and indoor residual spray (IRS) are ineffective against exophagic and exophilic mosquitoes. In Amazonian Peru, the identification of the most productive, positive water bodies would increase the impact of targeted mosquito control on aquatic life stages. The present study explores the use of unmanned aerial vehicles (drones) for identifying Nyssorhynchus darlingi (formerly Anopheles darlingi) breeding sites with high-resolution imagery (~0.02m/pixel) and their multispectral profile in Amazonian Peru. Our results show that high-resolution multispectral imagery can discriminate a profile of water bodies where Ny. darlingi is most likely to breed (overall accuracy 86.73%- 96.98%) with a moderate differentiation of spectral bands. This work provides proof-of-concept of the use of high-resolution images to detect malaria vector breeding sites in Amazonian Peru and such innovative methodology could be crucial for LSM malaria integrated interventions.
Volume
13
Issue
1
Language
English
OCDE Knowledge area
Medicina tropical
Scopus EID
2-s2.0-85060937775
PubMed ID
Source
PLoS Neglected Tropical Diseases
ISSN of the container
1935-2727
Sponsor(s)
This study was funded by TDR/WHO (201460655) to DG and supported in part by NIH-NIAID (U19AI089681) to JMV and NIH R01(AI110112) to JEC. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank the workers who carried out the field collections for their dedication during the surveys, and the local authorities of Salvador, Urco Miraño, Libertad and Visto Bueno for their enthusiastic support. We also thank all the people involved in the TDR-Peru project in Lima and Iquitos. We are grateful to Dirección Regional de Salud (DIRESA, Iquitos, Loreto) for collaboration and facilitating logistics in Loreto Department, and Applied Genomic Technologies Core at the Wadsworth Center, New York State Department of Health, where we performed the COI sequencing for species identification. This publication has been possible thanks to the authorization and permits N. 0424-2012-AG-DGFFS-DGEFFS from Direccion de Gestion Forestal y de Fauna Silvestre and Direccion General Forestal y de Fauna Silvestre from the Peruvian National Ministry of Agriculture.
Sources of information: Directorio de Producción Científica Scopus