Monitoring Drinking Water Quality in Nationally Representative Household Surveys in Low- and Middle-Income Countries: Cross-Sectional Analysis of 27 Multiple Indicator Cluster Surveys 2014–2020

Abstract

Background: The 2030 Sustainable Development Goals (SDGs) set an ambitious new benchmark for safely managed drinking water services (SMDWs), but many countries lack national data on the availability and quality of drinking water. Objectives: We quantified the availability and microbiological quality of drinking water, monitored SMDWs, and examined risk factors for Escherichia coli ( E. coli ) contamination in 27 low-and middle-income countries (LMICs). Methods: A new water quality module for household surveys was implemented in 27 Multiple Indicator Cluster Surveys. Teams used portable equipment to measure E. coli at the point of collection (PoC, ) and at the point of use (PoU, ) and asked respondents about the availability and accessibility of drinking water. Households were classified as having SMDW services if they used an improved water source that was free of E. coli contamination at PoC, accessible on premises, and available when needed. Compliance with individual SMDW criteria was also assessed. Modified Poisson regression was used to explore household and community risk factors for E. coli contamination. Results: E. coli was commonly detected at the PoC (range 16–90%) and was more likely at the PoU (range 19–99%). On average, 84% of households used an improved drinking water source, and 31% met all of the SMDW criteria. E. coli contamination was the primary reason SMDW criteria were not met (15 of 27 countries). The prevalence of E. coli in PoC samples was lower among households using improved water sources [ ; 95% confidence interval (CI): 0.64, 0.85] but not for households with water accessible on premises ( ; 95% CI: 0.94, 1.05) or available when needed ( ; 95% CI: 0.88, 1.02). E. coli contamination of PoU samples was less common for households in the richest vs. poorest wealth quintile ( ; 95% CI: 0.55, 0.88) and in communities with high ( ) improved sanitation coverage ( ; 95% CI: 0.90, 0.97). Livestock ownership ( ; 95% CI: 1.04, 1.13), rural vs. urban residence ( ; 95% CI: 1.04, 1.16), and wet vs. dry season sampling ( ; 95% CI: 1.01, 1.15) were positively associated with contamination at the PoU. Discussion: Cross-sectional water quality data can be collected in household surveys and can be used to assess inequalities in service levels, to track the SDG indicator of SMDWs, and to examine risk factors for contamination. There is an urgent need for better risk management to reduce widespread exposure to fecal contamination through drinking water services in LMICs. ...

Effectiveness of interventions to improve drinking water, sanitation, and handwashing with soap on risk of diarrhoeal disease in children in low-income and middle-income settings: a systematic review and meta-analysis

“… 80 Studies in Ethiopia and Egypt have provided evidence for a higher risk of diarrhoea among individuals with an intermittent piped water supply than among those with a continuous piped supply. 81 , 82 Third, and related to the previous hypothesis, storage of drinking water is associated with considerable risk of recontamination 83 and most of the piped water interventions on premises included in this analysis reported continuing household water storage. 35 , 84 , 85 , 86 , 87 , 88 , 89…”

Global potential for harvesting drinking water from air using solar energy

“…We report regression results of R 2 = 0.87 and a standard error of 3.67, indicating a bias which overreports SMDW share and a probable underestimate of people living without SMDW in our study. This discrepancy comes from JMP calculations of SMDW that rely on the minimum value of multiple drinking water service criteria (free from contamination, available when needed and accessible on premise) rather than considering whether individual households meet all criteria for SMDW 55 .…”

Invited Perspective: Beyond National Water Quality Surveys: Improving Water Quality Surveillance to Achieve Safe Drinking Water for All (Sustainable Development Goal 6.1)

“…https://doi.org/10.1289/EHP10064 Refers to https://doi.org/10.1289/EHP8459 Escherichia coli (E. coli) contamination is the primary reason safely managed drinking water criteria have not been met globally. This is a key finding of the new paper from the Joint Monitoring Program team (Bain et al 2021). The paper presents an analysis of the wealth of data from implementation of the United Nations International Children's Fund (UNICEF) Multiple Indicator Cluster Survey (MICS) water quality module in 27 low-and middle-income countries, including nationally representative samples of fecal contamination (E. coli) in drinking water at the point of collection (PoC) and the point of use (PoU).…”

“…MICS water quality data are able to elucidate the situation in individual countries and, through the analysis by Bain et al (2021), at an aggregate level. However, MICS water quality surveys do not provide the data that water managers need to inform improvements in water safety in order to achieve the United Nations Sustainable Development Goal (SDG) 6.1 (https://unstats.un.org/sdgs/report/ 2021/goal-06/).…”

“…Analysis of progress across the two data sets exemplifies one of the limitations of these data sets-the impact of weather during sampling on results. Bain et al (2021) have explored this issue in their analysis, identifying a link between season and PoU water quality, but in-country comparisons better illustrate the impact. In Bangladesh, despite progress across all areas of water access, sanitation, and hygiene, the measured water quality results did not show similar improvements, with very minor gains at the PoC and a large deterioration at the PoU (Bangladesh Bureau of Statistics and UNICEF Bangladesh 2021).…”