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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2017
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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. |
format | Online Article Text |
id | pubmed-5683539 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
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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