Microbial water quality is frequently assessed with a risk indicator approach that relies on Escherichia coli. Relying exclusively on E. coli is limiting, particularly in low-resource settings, and we argue that risk assessments could be improved by a complementary parameter, tryptophan-like fluorescence (TLF). Over two campaigns (June 2016 and March 2017) we sampled 37 water points in rural Kwale County, Kenya for TLF, E. coli and thermotolerant coliforms (total n = 1082). Using three World Health Organization defined classes (very high, high, and low/intermediate), risk indicated by TLF was not significantly different from risk indicated by E. coli (p = 0.85). However, the TLF and E. coli risk classifications did show disagreement, with TLF indicating higher risk for 14% of samples and lower risk for 13% of samples. Comparisons of duplicate/replicate results demonstrated that precision is higher for TLF (average relative percent difference of duplicates = 14%) compared to culture-based methods (average RPD of duplicates ≥ 26%). Additionally, TLF sampling is more practical because it requires less time and resources. Precision and practicality make TLF well-suited to high-frequency sampling in low resource contexts. Interpretation and interference challenges are minimised when TLF is measured in groundwaters, which typically have low dissolved organic carbon, relatively consistent temperature, negligible turbidity and pH between 5 and 8. TLF cannot be used as a proxy for E. coli on an individual sample basis, but it can add value to groundwater risk assessments by improving prioritization of sampling and by increasing understanding of spatiotemporal variability.
Across the water sector, Escherichia coli is the preferred microbial water quality indicator and current guidance upholds that it indicates recent faecal contamination. This has been challenged, however, by research demonstrating growth of E. coli in the environment. In this study, we used whole genome sequencing to investigate the links between E. coli and recent faecal contamination in drinking water. We sequenced 103 E. coli isolates sampled from 9 water supplies in rural Kitui County, Kenya, including points of collection (n = 14) and use (n = 30). Biomarkers for definitive source tracking remain elusive, so we analysed the phylogenetic grouping, multi-locus sequence types (MLSTs), allelic diversity, and virulence and antimicrobial resistance (AMR) genes of the isolates for insight into their likely source. Phylogroup B1, which is generally better adapted to water environments, is dominant in our samples (n = 69) and allelic diversity differences (z = 2.12, p = 0.03) suggest that naturalised populations may be particularly relevant at collection points with lower E. coli concentrations (<50 / 100mL). The strains that are more likely to have originated from human and/or recent faecal contamination (n = 50), were found at poorly protected collection points (4 sites) or at points of use (12 sites). We discuss the difficulty of interpreting health risk from E. coli grab samples, especially at household level, and our findings support the use of E. coli risk categories and encourage monitoring that accounts for sanitary conditions and temporal variability.
The sustainable developments goals (SDGs) introduced monitoring of drinking water quality to the international development agenda. At present, Escherichia coli are the primary measure by which we evaluate the safety of drinking water from an infectious disease perspective. Here, we propose and apply a framework to reflect on the purposes of and approaches to monitoring drinking water safety. To deliver SDG 6.1, universal access to safe drinking water, a new approach to monitoring is needed. At present, we rely heavily on single measures of E. coli contamination to meet a normative definition of safety. Achieving and sustaining universal access to safe drinking water will require monitoring that can inform decision making on whether services are managed to ensure safety and security of access.
The need to increase drinking water quality monitoring in rural sub-Saharan Africa is widely recognised. Rural water service providers (RWSPs) may be positioned to include water quality monitoring in their activities; however, it is important that water safety activities do not compromise cooperation between the RWSP, bureaucracy, and communities. Using dilemma analysis, drawing on an institutional experiment engaging 76 stakeholders, we find that conceptualising water quality versus quantity as a dichotomy delays progress on safe water. This false dichotomy makes it more difficult to deliver water safety improvements due to contrasting assumptions about the importance of quality; risks associated with not being able to act; and unclear divisions of responsibility. Monitoring water quality can be a threat to stakeholders and stakeholder cooperation; however, this may be mitigated by including supported water safety planning in the technical and institutional design of rural water projects at their conception.
Reducing disease from unsafe drinking-water is a key environmental health objective in rural Sub-Saharan Africa, where water management is largely community-based. The effectiveness of environmental health risk reporting to motivate sustained behaviour change is contested but as efforts to increase rural drinking-water monitoring proceed, it is timely to ask how water quality information feedback can improve water safety management. Using cross-sectional (1457 households) and longitudinal (167 participants) surveys, semi-structured interviews (73 participants), and water quality monitoring (79 sites), we assess water safety perceptions and evaluate an information intervention through which Escherichia coli monitoring results were shared with water managers over a 1.5-year period in rural Kitui County, Kenya. We integrate the extended parallel process model and the precaution adoption process model to frame risk information processing and stages of behaviour change. We highlight that responses to risk communications are determined by the specificity, framing, and repetition of messaging and the self-efficacy of information recipients. Poverty threatscapes and gender norms hinder behaviour change, particularly at the household-level; however, test results can motivate supply-level managers to implement hazard control measures—with effectiveness and sustainability dependent on infrastructure, training, and ongoing resourcing. Our results have implications for rural development efforts and environmental risk reporting in low-income settings.
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