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Mapping multiple components of malaria risk for improved targeting of elimination interventions

There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National ma...

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Autores principales: Cohen, Justin M., Le Menach, Arnaud, Pothin, Emilie, Eisele, Thomas P., Gething, Peter W., Eckhoff, Philip A., Moonen, Bruno, Schapira, Allan, Smith, David L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5683539/
https://www.ncbi.nlm.nih.gov/pubmed/29132357
http://dx.doi.org/10.1186/s12936-017-2106-3
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author Cohen, Justin M.
Le Menach, Arnaud
Pothin, Emilie
Eisele, Thomas P.
Gething, Peter W.
Eckhoff, Philip A.
Moonen, Bruno
Schapira, Allan
Smith, David L.
author_facet Cohen, Justin M.
Le Menach, Arnaud
Pothin, Emilie
Eisele, Thomas P.
Gething, Peter W.
Eckhoff, Philip A.
Moonen, Bruno
Schapira, Allan
Smith, David L.
author_sort Cohen, Justin M.
collection PubMed
description There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National malaria programmes typically make operational decisions about where to implement vector control and surveillance activities based upon simple categorizations of annual parasite incidence. With technological advances, an enormous opportunity exists to better target specific malaria interventions to the places where they will have greatest impact by mapping and evaluating metrics related to a variety of risk components, each of which describes a different facet of the transmission cycle. Here, these components and their implications for operational decision-making are reviewed. For each component, related mappable malaria metrics are also described which may be measured and evaluated by malaria programmes seeking to better understand the determinants of malaria risk. Implementing tailored programmes based on knowledge of the heterogeneous distribution of the drivers of malaria transmission rather than only consideration of traditional metrics such as case incidence has the potential to result in substantial improvements in decision-making. As programmes improve their ability to prioritize their available tools to the places where evidence suggests they will be most effective, elimination aspirations may become increasingly feasible.
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spelling pubmed-56835392017-11-20 Mapping multiple components of malaria risk for improved targeting of elimination interventions Cohen, Justin M. Le Menach, Arnaud Pothin, Emilie Eisele, Thomas P. Gething, Peter W. Eckhoff, Philip A. Moonen, Bruno Schapira, Allan Smith, David L. Malar J Review There is a long history of considering the constituent components of malaria risk and the malaria transmission cycle via the use of mathematical models, yet strategic planning in endemic countries tends not to take full advantage of available disease intelligence to tailor interventions. National malaria programmes typically make operational decisions about where to implement vector control and surveillance activities based upon simple categorizations of annual parasite incidence. With technological advances, an enormous opportunity exists to better target specific malaria interventions to the places where they will have greatest impact by mapping and evaluating metrics related to a variety of risk components, each of which describes a different facet of the transmission cycle. Here, these components and their implications for operational decision-making are reviewed. For each component, related mappable malaria metrics are also described which may be measured and evaluated by malaria programmes seeking to better understand the determinants of malaria risk. Implementing tailored programmes based on knowledge of the heterogeneous distribution of the drivers of malaria transmission rather than only consideration of traditional metrics such as case incidence has the potential to result in substantial improvements in decision-making. As programmes improve their ability to prioritize their available tools to the places where evidence suggests they will be most effective, elimination aspirations may become increasingly feasible. BioMed Central 2017-11-13 /pmc/articles/PMC5683539/ /pubmed/29132357 http://dx.doi.org/10.1186/s12936-017-2106-3 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Review
Cohen, Justin M.
Le Menach, Arnaud
Pothin, Emilie
Eisele, Thomas P.
Gething, Peter W.
Eckhoff, Philip A.
Moonen, Bruno
Schapira, Allan
Smith, David L.
Mapping multiple components of malaria risk for improved targeting of elimination interventions
title Mapping multiple components of malaria risk for improved targeting of elimination interventions
title_full Mapping multiple components of malaria risk for improved targeting of elimination interventions
title_fullStr Mapping multiple components of malaria risk for improved targeting of elimination interventions
title_full_unstemmed Mapping multiple components of malaria risk for improved targeting of elimination interventions
title_short Mapping multiple components of malaria risk for improved targeting of elimination interventions
title_sort mapping multiple components of malaria risk for improved targeting of elimination interventions
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5683539/
https://www.ncbi.nlm.nih.gov/pubmed/29132357
http://dx.doi.org/10.1186/s12936-017-2106-3
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