Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013

Abstract Background To describe spatiotemporal patterns of diarrhoea in Bhutan, and quantify the association between climatic factors and the distribution and dynamics of the disease. Methods Nationwide data on diarrhoea were obtained for 2003 to 2013 from the Health Information and Management Syste...

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Main Authors: Kinley Wangdi, Archie CA Clements
Format: Article
Language:English
Published: BMC 2017-07-01
Series:BMC Infectious Diseases
Subjects:
Online Access:http://link.springer.com/article/10.1186/s12879-017-2611-6
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spelling doaj-82478ab85d6d4ab1bc7cfc51201636142020-11-25T01:38:37ZengBMCBMC Infectious Diseases1471-23342017-07-011711910.1186/s12879-017-2611-6Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013Kinley Wangdi0Archie CA Clements1Department of Global Health, Research School of Population Health, College of Medicine, Environment and Biology, The Australian National UniversityDepartment of Global Health, Research School of Population Health, College of Medicine, Environment and Biology, The Australian National UniversityAbstract Background To describe spatiotemporal patterns of diarrhoea in Bhutan, and quantify the association between climatic factors and the distribution and dynamics of the disease. Methods Nationwide data on diarrhoea were obtained for 2003 to 2013 from the Health Information and Management System (HIMS), Ministry of Health, Bhutan. Climatic variables were obtained from the Department of Hydro Met Services, Ministry of Economic Affairs, Bhutan. Seasonal trend decomposition was used to examine secular trends and seasonal patterns of diarrhoea. A Bayesian conditional autoregressive (CAR) model was used to quantify the relationship between monthly diarrhoea, maximum temperature, rainfall, age and gender. Results The monthly average diarrhoea incidence was highly seasonal. Diarrhoea incidence increased by 0.6% (95% CrI: 0.5–0.6%) for every degree increase in maximum temperature; and 5% (95 Cr I: 4.9–5.1%) for a 1 mm increase in rainfall. Children aged <5 years were found to be 74.2% (95% CrI: 74.1–74.4) more likely to experience diarrhoea than children and adults aged ≥5 years and females were 4.9% (95% CrI: 4.4–5.3%) less likely to suffer from diarrhoea as compared to males. Significant residual spatial clustering was found after accounting for climate and demographic variables. Conclusions Diarrhoea incidence was highly seasonal, with positive associations with maximum temperature and rainfall and negative associations with age and being female. This calls for public health actions to reduce future risks of climate change with great consideration of local climatic conditions. In addition, protection of <5 years children should be prioritize through provision of rotavirus vaccination, safe and clean drinking water, and proper latrines.http://link.springer.com/article/10.1186/s12879-017-2611-6Time series analysisSpatial analysisBayesian analysisDiarrhoeaBhutan
collection DOAJ
language English
format Article
sources DOAJ
author Kinley Wangdi
Archie CA Clements
spellingShingle Kinley Wangdi
Archie CA Clements
Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013
BMC Infectious Diseases
Time series analysis
Spatial analysis
Bayesian analysis
Diarrhoea
Bhutan
author_facet Kinley Wangdi
Archie CA Clements
author_sort Kinley Wangdi
title Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013
title_short Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013
title_full Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013
title_fullStr Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013
title_full_unstemmed Spatial and temporal patterns of diarrhoea in Bhutan 2003–2013
title_sort spatial and temporal patterns of diarrhoea in bhutan 2003–2013
publisher BMC
series BMC Infectious Diseases
issn 1471-2334
publishDate 2017-07-01
description Abstract Background To describe spatiotemporal patterns of diarrhoea in Bhutan, and quantify the association between climatic factors and the distribution and dynamics of the disease. Methods Nationwide data on diarrhoea were obtained for 2003 to 2013 from the Health Information and Management System (HIMS), Ministry of Health, Bhutan. Climatic variables were obtained from the Department of Hydro Met Services, Ministry of Economic Affairs, Bhutan. Seasonal trend decomposition was used to examine secular trends and seasonal patterns of diarrhoea. A Bayesian conditional autoregressive (CAR) model was used to quantify the relationship between monthly diarrhoea, maximum temperature, rainfall, age and gender. Results The monthly average diarrhoea incidence was highly seasonal. Diarrhoea incidence increased by 0.6% (95% CrI: 0.5–0.6%) for every degree increase in maximum temperature; and 5% (95 Cr I: 4.9–5.1%) for a 1 mm increase in rainfall. Children aged <5 years were found to be 74.2% (95% CrI: 74.1–74.4) more likely to experience diarrhoea than children and adults aged ≥5 years and females were 4.9% (95% CrI: 4.4–5.3%) less likely to suffer from diarrhoea as compared to males. Significant residual spatial clustering was found after accounting for climate and demographic variables. Conclusions Diarrhoea incidence was highly seasonal, with positive associations with maximum temperature and rainfall and negative associations with age and being female. This calls for public health actions to reduce future risks of climate change with great consideration of local climatic conditions. In addition, protection of <5 years children should be prioritize through provision of rotavirus vaccination, safe and clean drinking water, and proper latrines.
topic Time series analysis
Spatial analysis
Bayesian analysis
Diarrhoea
Bhutan
url http://link.springer.com/article/10.1186/s12879-017-2611-6
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