Bayesian conditional autoregressive models to assess spatial patterns of diarrhoea risk among children under the age of 5 years in Mbour, Senegal

Submitted: 12 October 2019
Accepted: 21 October 2019
Published: 6 November 2019
Abstract Views: 1281
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APPENDIX: 190
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Diarrhoeal diseases remain a major public health problem, causing more than half a million child deaths every year, particularly in low- and middle-income countries (LMICs). Despite existing knowledge on the aetiologies and causes of diarrhoeal diseases, relatively little is known about its spatial patterns in LMICs, including Senegal. In the present study, data from a cross-sectional survey carried out in 2016 were analysed to describe the spatial pattern of diarrhoeal prevalence in children under the age of 5 years in the secondary city of Mbour in the south-western part of Senegal. Bayesian conditional autoregressive (CAR) models with spatially varying coefficients were employed to determine the effect of sociodemographic, economic and climate parameters on diarrhoeal prevalence. We observed substantial spatial heterogeneities in diarrhoea prevalence. Risk maps, stratified by age group, showed that diarrhoeal prevalence was higher in children aged 25-59 months compared to their younger counterparts with the highest risk observed in the north and south peripheral neighbourhoods, especially in Grand Mbour, Médine, Liberté and Zone Sonatel. The posterior relative risk estimate obtained from the Bayesian CAR model indicated that a unit increase in the proportion of people with untreated stored drinking water was associated with a 29% higher risk of diarrhoea. A unit increase in rainfall was also associated with an increase in diarrhoea risk. Our findings suggest that public health officials should integrate disease mapping and cluster analyses and consider the varying effects of sociodemographic factors in developing and implementing areaspecific interventions for reducing diarrhoea.

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Supporting Agencies

This study was supported by funding from the Swiss Government, through the Swiss Government Excellence Scholarships for Foreign Scholars (ESKAS scholarship) and the Swiss African- Research Cooperation (SARECO) programme. ASS is grateful to Knud Højgaards Fond for supporting the Research Platform for Disease Ecology, Climate and Health and thank the Danish National Research Foundation for its support of the Center for Macroecology, Evolution and Climate (grant no. DNRF96).

How to Cite

Thiam, S., Cissé, G., Stensgaard, A.-S., Niang-Diène, A., Utzinger, J., & Vounatsou, P. (2019). Bayesian conditional autoregressive models to assess spatial patterns of diarrhoea risk among children under the age of 5 years in Mbour, Senegal. Geospatial Health, 14(2). https://doi.org/10.4081/gh.2019.823

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