Remote Sensing and Multi-Criteria Evaluation for Malaria Risk Mapping to Support Indoor Residual Spraying Prioritization in the Central Highlands of Madagascar

Bibliographic Details
Title: Remote Sensing and Multi-Criteria Evaluation for Malaria Risk Mapping to Support Indoor Residual Spraying Prioritization in the Central Highlands of Madagascar
Authors: Hobiniaina Anthonio Rakotoarison, Mampionona Rasamimalala, Jean Marius Rakotondramanga, Brune Ramiranirina, Thierry Franchard, Laurent Kapesa, Jocelyn Razafindrakoto, Hélène Guis, Luciano Michaël Tantely, Romain Girod, Solofoarisoa Rakotoniaina, Laurence Baril, Patrice Piola, Fanjasoa Rakotomanana
Source: Remote Sensing, Vol 12, Iss 10, p 1585 (2020)
Publisher Information: MDPI AG, 2020.
Publication Year: 2020
Collection: LCC:Science
Subject Terms: remote sensing, spatial modeling, multi-criteria evaluation, malaria, Madagascar, Science
More Details: The National Malaria Control Program (NMCP) in Madagascar classifies Malagasy districts into two malaria situations: districts in the pre-elimination phase and districts in the control phase. Indoor residual spraying (IRS) is identified as the main intervention means to control malaria in the Central Highlands. However, it involves an important logistical mobilization and thus necessitates prioritization of interventions according to the magnitude of malaria risks. Our objectives were to map the malaria transmission risk and to develop a tool to support the Malagasy Ministry of Public Health (MoH) for selective IRS implementation. For the 2014–2016 period, different sources of remotely sensed data were used to update land cover information and substitute in situ climatic data. Spatial modeling was performed based on multi-criteria evaluation (MCE) to assess malaria risk. Models were mainly based on environment and climate. Three annual malaria risk maps were obtained for 2014, 2015, and 2016. Annual parasite incidence data were used to validate the results. In 2016, the validation of the model using a receiver operating characteristic (ROC) curve showed an accuracy of 0.736; 95% CI [0.669–0.803]. A free plugin for QGIS software was made available for NMCP decision makers to prioritize areas for IRS. An annual update of the model provides the basic information for decision making before each IRS campaign. In Madagascar and beyond, the availability of the free plugin for open-source software facilitates the transfer to the MoH and allows further application to other problems and contexts.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2072-4292
Relation: https://www.mdpi.com/2072-4292/12/10/1585; https://doaj.org/toc/2072-4292
DOI: 10.3390/rs12101585
Access URL: https://doaj.org/article/da3cad93d9f94483b6e507edf7140582
Accession Number: edsdoj.3cad93d9f94483b6e507edf7140582
Database: Directory of Open Access Journals
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More Details
ISSN:20724292
DOI:10.3390/rs12101585
Published in:Remote Sensing
Language:English