Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar
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.
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Subjects: | L73 - Maladies des animaux, U30 - Méthodes de recherche, malaria, télédétection, évaluation du risque, distribution spatiale, http://aims.fao.org/aos/agrovoc/c_34312, http://aims.fao.org/aos/agrovoc/c_6498, http://aims.fao.org/aos/agrovoc/c_37932, http://aims.fao.org/aos/agrovoc/c_36230, http://aims.fao.org/aos/agrovoc/c_4510, |
Online Access: | http://agritrop.cirad.fr/595784/ http://agritrop.cirad.fr/595784/1/remotesensing-12-01585.pdf |
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dig-cirad-fr-5957842024-01-29T02:48:18Z http://agritrop.cirad.fr/595784/ http://agritrop.cirad.fr/595784/ Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar. Rakotoarison Hobiniaina Anthonio, Rasamimalala Mampionona, Rakotondramanga Jean Marius, Ramiranirina Brune, Franchard Thierry, Kapesa Laurent, Razafindrakoto Jocelyn, Guis Hélène, Tantely Luciano Michaël, Girod Romain, Rakotoniaina Solofoarisoa, Baril Laurence, Piola Patrice, Rakotomanana Fanjasoa. 2020. Remote Sensing, 12, n.spéc. Remote Sensing for Health: from Fine-Scale Investigations towards Early-Warning Systems:1585, 22 p.https://doi.org/10.3390/rs12101585 <https://doi.org/10.3390/rs12101585> Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar Rakotoarison, Hobiniaina Anthonio Rasamimalala, Mampionona Rakotondramanga, Jean Marius Ramiranirina, Brune Franchard, Thierry Kapesa, Laurent Razafindrakoto, Jocelyn Guis, Hélène Tantely, Luciano Michaël Girod, Romain Rakotoniaina, Solofoarisoa Baril, Laurence Piola, Patrice Rakotomanana, Fanjasoa eng 2020 Remote Sensing L73 - Maladies des animaux U30 - Méthodes de recherche malaria télédétection évaluation du risque distribution spatiale http://aims.fao.org/aos/agrovoc/c_34312 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_37932 http://aims.fao.org/aos/agrovoc/c_36230 Madagascar http://aims.fao.org/aos/agrovoc/c_4510 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. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/595784/1/remotesensing-12-01585.pdf text cc_by info:eu-repo/semantics/openAccess https://creativecommons.org/licenses/by/4.0/ https://doi.org/10.3390/rs12101585 10.3390/rs12101585 info:eu-repo/semantics/altIdentifier/doi/10.3390/rs12101585 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.3390/rs12101585 |
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L73 - Maladies des animaux U30 - Méthodes de recherche malaria télédétection évaluation du risque distribution spatiale http://aims.fao.org/aos/agrovoc/c_34312 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_37932 http://aims.fao.org/aos/agrovoc/c_36230 http://aims.fao.org/aos/agrovoc/c_4510 L73 - Maladies des animaux U30 - Méthodes de recherche malaria télédétection évaluation du risque distribution spatiale http://aims.fao.org/aos/agrovoc/c_34312 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_37932 http://aims.fao.org/aos/agrovoc/c_36230 http://aims.fao.org/aos/agrovoc/c_4510 |
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L73 - Maladies des animaux U30 - Méthodes de recherche malaria télédétection évaluation du risque distribution spatiale http://aims.fao.org/aos/agrovoc/c_34312 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_37932 http://aims.fao.org/aos/agrovoc/c_36230 http://aims.fao.org/aos/agrovoc/c_4510 L73 - Maladies des animaux U30 - Méthodes de recherche malaria télédétection évaluation du risque distribution spatiale http://aims.fao.org/aos/agrovoc/c_34312 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_37932 http://aims.fao.org/aos/agrovoc/c_36230 http://aims.fao.org/aos/agrovoc/c_4510 Rakotoarison, Hobiniaina Anthonio Rasamimalala, Mampionona Rakotondramanga, Jean Marius Ramiranirina, Brune Franchard, Thierry Kapesa, Laurent Razafindrakoto, Jocelyn Guis, Hélène Tantely, Luciano Michaël Girod, Romain Rakotoniaina, Solofoarisoa Baril, Laurence Piola, Patrice Rakotomanana, Fanjasoa Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar |
description |
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. |
format |
article |
topic_facet |
L73 - Maladies des animaux U30 - Méthodes de recherche malaria télédétection évaluation du risque distribution spatiale http://aims.fao.org/aos/agrovoc/c_34312 http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_37932 http://aims.fao.org/aos/agrovoc/c_36230 http://aims.fao.org/aos/agrovoc/c_4510 |
author |
Rakotoarison, Hobiniaina Anthonio Rasamimalala, Mampionona Rakotondramanga, Jean Marius Ramiranirina, Brune Franchard, Thierry Kapesa, Laurent Razafindrakoto, Jocelyn Guis, Hélène Tantely, Luciano Michaël Girod, Romain Rakotoniaina, Solofoarisoa Baril, Laurence Piola, Patrice Rakotomanana, Fanjasoa |
author_facet |
Rakotoarison, Hobiniaina Anthonio Rasamimalala, Mampionona Rakotondramanga, Jean Marius Ramiranirina, Brune Franchard, Thierry Kapesa, Laurent Razafindrakoto, Jocelyn Guis, Hélène Tantely, Luciano Michaël Girod, Romain Rakotoniaina, Solofoarisoa Baril, Laurence Piola, Patrice Rakotomanana, Fanjasoa |
author_sort |
Rakotoarison, Hobiniaina Anthonio |
title |
Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar |
title_short |
Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar |
title_full |
Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar |
title_fullStr |
Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar |
title_full_unstemmed |
Remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the Central highlands of Madagascar |
title_sort |
remote sensing and multi-criteria evaluation for malaria risk mapping to support indoor residual spraying prioritization in the central highlands of madagascar |
url |
http://agritrop.cirad.fr/595784/ http://agritrop.cirad.fr/595784/1/remotesensing-12-01585.pdf |
work_keys_str_mv |
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