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Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia
BACKGROUND: Malaria, a parasitic infection, is a life-threatening disease in South Sumatra Province, Indonesia. This study aimed to investigate the spatial association between malaria occurrence and environmental risk factors. METHODS: The number of confirmed malaria cases was analysed for the year...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819714/ https://www.ncbi.nlm.nih.gov/pubmed/29463239 http://dx.doi.org/10.1186/s12936-018-2230-8 |
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author | Hasyim, Hamzah Nursafingi, Afi Haque, Ubydul Montag, Doreen Groneberg, David A. Dhimal, Meghnath Kuch, Ulrich Müller, Ruth |
author_facet | Hasyim, Hamzah Nursafingi, Afi Haque, Ubydul Montag, Doreen Groneberg, David A. Dhimal, Meghnath Kuch, Ulrich Müller, Ruth |
author_sort | Hasyim, Hamzah |
collection | PubMed |
description | BACKGROUND: Malaria, a parasitic infection, is a life-threatening disease in South Sumatra Province, Indonesia. This study aimed to investigate the spatial association between malaria occurrence and environmental risk factors. METHODS: The number of confirmed malaria cases was analysed for the year 2013 from the routine reporting of the Provincial Health Office of South Sumatra. The cases were spread over 436 out of 1613 villages. Six potential ecological predictors of malaria cases were analysed in the different regions using ordinary least square (OLS) and geographically weighted regression (GWR). The global pattern and spatial variability of associations between malaria cases and the selected potential ecological predictors was explored. RESULTS: The importance of different environmental and geographic parameters for malaria was shown at global and village-level in South Sumatra, Indonesia. The independent variables altitude, distance from forest, and rainfall in global OLS were significantly associated with malaria cases. However, as shown by GWR model and in line with recent reviews, the relationship between malaria and environmental factors in South Sumatra strongly varied spatially in different regions. CONCLUSIONS: A more in-depth understanding of local ecological factors influencing malaria disease as shown in present study may not only be useful for developing sustainable regional malaria control programmes, but can also benefit malaria elimination efforts at village level. |
format | Online Article Text |
id | pubmed-5819714 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-58197142018-02-26 Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia Hasyim, Hamzah Nursafingi, Afi Haque, Ubydul Montag, Doreen Groneberg, David A. Dhimal, Meghnath Kuch, Ulrich Müller, Ruth Malar J Research BACKGROUND: Malaria, a parasitic infection, is a life-threatening disease in South Sumatra Province, Indonesia. This study aimed to investigate the spatial association between malaria occurrence and environmental risk factors. METHODS: The number of confirmed malaria cases was analysed for the year 2013 from the routine reporting of the Provincial Health Office of South Sumatra. The cases were spread over 436 out of 1613 villages. Six potential ecological predictors of malaria cases were analysed in the different regions using ordinary least square (OLS) and geographically weighted regression (GWR). The global pattern and spatial variability of associations between malaria cases and the selected potential ecological predictors was explored. RESULTS: The importance of different environmental and geographic parameters for malaria was shown at global and village-level in South Sumatra, Indonesia. The independent variables altitude, distance from forest, and rainfall in global OLS were significantly associated with malaria cases. However, as shown by GWR model and in line with recent reviews, the relationship between malaria and environmental factors in South Sumatra strongly varied spatially in different regions. CONCLUSIONS: A more in-depth understanding of local ecological factors influencing malaria disease as shown in present study may not only be useful for developing sustainable regional malaria control programmes, but can also benefit malaria elimination efforts at village level. BioMed Central 2018-02-20 /pmc/articles/PMC5819714/ /pubmed/29463239 http://dx.doi.org/10.1186/s12936-018-2230-8 Text en © The Author(s) 2018 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 | Research Hasyim, Hamzah Nursafingi, Afi Haque, Ubydul Montag, Doreen Groneberg, David A. Dhimal, Meghnath Kuch, Ulrich Müller, Ruth Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia |
title | Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia |
title_full | Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia |
title_fullStr | Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia |
title_full_unstemmed | Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia |
title_short | Spatial modelling of malaria cases associated with environmental factors in South Sumatra, Indonesia |
title_sort | spatial modelling of malaria cases associated with environmental factors in south sumatra, indonesia |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5819714/ https://www.ncbi.nlm.nih.gov/pubmed/29463239 http://dx.doi.org/10.1186/s12936-018-2230-8 |
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