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Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands
INTRODUCTION: Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies. METHODS AND FINDINGS: A conceptu...
Autores principales: | , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2009
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2778131/ https://www.ncbi.nlm.nih.gov/pubmed/19946627 http://dx.doi.org/10.1371/journal.pone.0008022 |
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author | Protopopoff, Natacha Van Bortel, Wim Speybroeck, Niko Van Geertruyden, Jean-Pierre Baza, Dismas D'Alessandro, Umberto Coosemans, Marc |
author_facet | Protopopoff, Natacha Van Bortel, Wim Speybroeck, Niko Van Geertruyden, Jean-Pierre Baza, Dismas D'Alessandro, Umberto Coosemans, Marc |
author_sort | Protopopoff, Natacha |
collection | PubMed |
description | INTRODUCTION: Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies. METHODS AND FINDINGS: A conceptual model of potential malaria risk factors in the highlands was built based on the available literature. Furthermore, the relative importance of these factors on malaria can be estimated through “classification and regression trees”, an unexploited statistical method in the malaria field. This CART method was used to analyse the malaria risk factors in the Burundi highlands. The results showed that Anopheles density was the best predictor for high malaria prevalence. Then lower rainfall, no vector control, higher minimum temperature and houses near breeding sites were associated by order of importance to higher Anopheles density. CONCLUSIONS: In Burundi highlands monitoring Anopheles densities when rainfall is low may be able to predict epidemics. The conceptual model combined with the CART analysis is a decision support tool that could provide an important contribution toward the prevention and control of malaria by identifying major risk factors. |
format | Text |
id | pubmed-2778131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-27781312009-11-26 Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands Protopopoff, Natacha Van Bortel, Wim Speybroeck, Niko Van Geertruyden, Jean-Pierre Baza, Dismas D'Alessandro, Umberto Coosemans, Marc PLoS One Research Article INTRODUCTION: Malaria is re-emerging in most of the African highlands exposing the non immune population to deadly epidemics. A better understanding of the factors impacting transmission in the highlands is crucial to improve well targeted malaria control strategies. METHODS AND FINDINGS: A conceptual model of potential malaria risk factors in the highlands was built based on the available literature. Furthermore, the relative importance of these factors on malaria can be estimated through “classification and regression trees”, an unexploited statistical method in the malaria field. This CART method was used to analyse the malaria risk factors in the Burundi highlands. The results showed that Anopheles density was the best predictor for high malaria prevalence. Then lower rainfall, no vector control, higher minimum temperature and houses near breeding sites were associated by order of importance to higher Anopheles density. CONCLUSIONS: In Burundi highlands monitoring Anopheles densities when rainfall is low may be able to predict epidemics. The conceptual model combined with the CART analysis is a decision support tool that could provide an important contribution toward the prevention and control of malaria by identifying major risk factors. Public Library of Science 2009-11-25 /pmc/articles/PMC2778131/ /pubmed/19946627 http://dx.doi.org/10.1371/journal.pone.0008022 Text en Protopopoff et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Protopopoff, Natacha Van Bortel, Wim Speybroeck, Niko Van Geertruyden, Jean-Pierre Baza, Dismas D'Alessandro, Umberto Coosemans, Marc Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands |
title | Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands |
title_full | Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands |
title_fullStr | Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands |
title_full_unstemmed | Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands |
title_short | Ranking Malaria Risk Factors to Guide Malaria Control Efforts in African Highlands |
title_sort | ranking malaria risk factors to guide malaria control efforts in african highlands |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2778131/ https://www.ncbi.nlm.nih.gov/pubmed/19946627 http://dx.doi.org/10.1371/journal.pone.0008022 |
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