Spatial risk distribution and determinants of E. coli contamination in household drinking water: a case study of Bangladesh

Int J Environ Health Res. 2020 Jun;30(3):268-283. doi: 10.1080/09603123.2019.1593328. Epub 2019 Mar 29.

Abstract

The Escherichia coli (E. coli) contamination in the household (HH) drinking water is often a public health concern. Very few studies explore the associated factors and spatial risk modeling together for E. coli contamination in Bangladesh, this research gap motivates to explore this fact further by utilizing Bangladesh Multiple Indicator Cluster Survey (MICS) 2012-13 data. A Bayesian spatial ordered logit model was used to examine the associated factors and spatial risks of the E. coli contamination. The results show that 62% of HH water samples were contaminated with E. coli. After controlling for different factors, a high level of E. coli contamination was observed among HHs who had access to non-improved water sources. Moreover, no significant rural-urban difference was observed. The spatial prediction of the high-risk contamination was prominent in districts like Dhaka and Bandarban. The study findings can provide insights into the planning of policy activities in Bangladesh.

Keywords: Bayesian spatial model; E. coli contamination; spatial risk.

MeSH terms

  • Bangladesh
  • Bayes Theorem
  • Drinking Water / microbiology*
  • Environmental Monitoring
  • Escherichia coli / isolation & purification*
  • Risk Assessment
  • Spatial Analysis

Substances

  • Drinking Water