Bayesian modelling of the effect of climate on malaria in Burundi
Abstract Background In Burundi, malaria is a major public health issue in terms of both morbidity and mortality with around 2.5 million clinical cases and more than 15,000 deaths each year. It is the single main cause of mortality in pregnant women and children below five years of age. Due to the se...
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ftdoajarticles:oai:doaj.org/article:e76e5cc312a54a93a904b4e39bd1fba5 2023-05-15T15:18:33+02:00 Bayesian modelling of the effect of climate on malaria in Burundi Gebhardt Albrecht Nkurunziza Hermenegilde Pilz Jürgen 2010-04-01T00:00:00Z https://doi.org/10.1186/1475-2875-9-114 https://doaj.org/article/e76e5cc312a54a93a904b4e39bd1fba5 EN eng BMC http://www.malariajournal.com/content/9/1/114 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-9-114 1475-2875 https://doaj.org/article/e76e5cc312a54a93a904b4e39bd1fba5 Malaria Journal, Vol 9, Iss 1, p 114 (2010) Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 article 2010 ftdoajarticles https://doi.org/10.1186/1475-2875-9-114 2022-12-31T08:34:38Z Abstract Background In Burundi, malaria is a major public health issue in terms of both morbidity and mortality with around 2.5 million clinical cases and more than 15,000 deaths each year. It is the single main cause of mortality in pregnant women and children below five years of age. Due to the severe health and economic cost of malaria, there is still a growing need for methods that will help to understand the influencing factors. Several studies have been done on the subject yielding different results as which factors are most responsible for the increase in malaria. The purpose of this study has been to undertake a spatial/longitudinal statistical analysis to identify important climatic variables that influence malaria incidences in Burundi. Methods This paper investigates the effects of climate on malaria in Burundi. For the period 1996-2007, real monthly data on both malaria epidemiology and climate in the area of Burundi are described and analysed. From this analysis, a mathematical model is derived and proposed to assess which variables significantly influence malaria incidences in Burundi. The proposed modelling is based on both generalized linear models (GLM) and generalized additive mixed models (GAMM). The modelling is fully Bayesian and inference is carried out by Markov Chain Monte Carlo (MCMC) techniques. Results The results obtained from the proposed models are discussed and it is found that malaria incidence in a given month in Burundi is strongly positively associated with the minimum temperature of the previous month. In contrast, it is found that rainfall and maximum temperature in a given month have a possible negative effect on malaria incidence of the same month. Conclusions This study has exploited available real monthly data on malaria and climate over 12 years in Burundi to derive and propose a regression modelling to assess climatic factors that are associated with monthly malaria incidence. The results obtained from the proposed models suggest a strong positive association between ... Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic Malaria Journal 9 1 |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
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Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 Gebhardt Albrecht Nkurunziza Hermenegilde Pilz Jürgen Bayesian modelling of the effect of climate on malaria in Burundi |
topic_facet |
Arctic medicine. Tropical medicine RC955-962 Infectious and parasitic diseases RC109-216 |
description |
Abstract Background In Burundi, malaria is a major public health issue in terms of both morbidity and mortality with around 2.5 million clinical cases and more than 15,000 deaths each year. It is the single main cause of mortality in pregnant women and children below five years of age. Due to the severe health and economic cost of malaria, there is still a growing need for methods that will help to understand the influencing factors. Several studies have been done on the subject yielding different results as which factors are most responsible for the increase in malaria. The purpose of this study has been to undertake a spatial/longitudinal statistical analysis to identify important climatic variables that influence malaria incidences in Burundi. Methods This paper investigates the effects of climate on malaria in Burundi. For the period 1996-2007, real monthly data on both malaria epidemiology and climate in the area of Burundi are described and analysed. From this analysis, a mathematical model is derived and proposed to assess which variables significantly influence malaria incidences in Burundi. The proposed modelling is based on both generalized linear models (GLM) and generalized additive mixed models (GAMM). The modelling is fully Bayesian and inference is carried out by Markov Chain Monte Carlo (MCMC) techniques. Results The results obtained from the proposed models are discussed and it is found that malaria incidence in a given month in Burundi is strongly positively associated with the minimum temperature of the previous month. In contrast, it is found that rainfall and maximum temperature in a given month have a possible negative effect on malaria incidence of the same month. Conclusions This study has exploited available real monthly data on malaria and climate over 12 years in Burundi to derive and propose a regression modelling to assess climatic factors that are associated with monthly malaria incidence. The results obtained from the proposed models suggest a strong positive association between ... |
format |
Article in Journal/Newspaper |
author |
Gebhardt Albrecht Nkurunziza Hermenegilde Pilz Jürgen |
author_facet |
Gebhardt Albrecht Nkurunziza Hermenegilde Pilz Jürgen |
author_sort |
Gebhardt Albrecht |
title |
Bayesian modelling of the effect of climate on malaria in Burundi |
title_short |
Bayesian modelling of the effect of climate on malaria in Burundi |
title_full |
Bayesian modelling of the effect of climate on malaria in Burundi |
title_fullStr |
Bayesian modelling of the effect of climate on malaria in Burundi |
title_full_unstemmed |
Bayesian modelling of the effect of climate on malaria in Burundi |
title_sort |
bayesian modelling of the effect of climate on malaria in burundi |
publisher |
BMC |
publishDate |
2010 |
url |
https://doi.org/10.1186/1475-2875-9-114 https://doaj.org/article/e76e5cc312a54a93a904b4e39bd1fba5 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
Malaria Journal, Vol 9, Iss 1, p 114 (2010) |
op_relation |
http://www.malariajournal.com/content/9/1/114 https://doaj.org/toc/1475-2875 doi:10.1186/1475-2875-9-114 1475-2875 https://doaj.org/article/e76e5cc312a54a93a904b4e39bd1fba5 |
op_doi |
https://doi.org/10.1186/1475-2875-9-114 |
container_title |
Malaria Journal |
container_volume |
9 |
container_issue |
1 |
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1766348747790352384 |