Assessing the risk of acute gastrointestinal illness attributable to three enteric pathogens from contaminated private water wells in Ontario

An investigation of microbial groundwater contamination seasonality and extreme weather event interruptions using "big data", time-series analyses, and unsupervised machine learning

Temporal studies of groundwater potability have historically focused on E. coli detection rates, with non-E. coli coliforms (NEC) and microbial concentrations remaining understudied by comparison. Additionally, "big data" (i.e., large, diverse datasets that grow over time) have yet to be employed for assessing the effects of high return-period extreme weather events on groundwater quality. The current investigation employed ≈1.1 million Ontarian private well samples collected between 2010 and 2021, seeking to address these knowledge gaps via applying time-series decomposition, interrupted time-series analysis (ITSA), and unsupervised machine learning to five microbial contamination parameters: E. coli and NEC concentrations (CFU/100 mL) and detection rates (%), and the calculated NEC:E. coli ratio. Time-series decompositions revealed E. coli concentrations and the NEC:E. coli ratio as complementary metrics, with concurrent interpretation of their seasonal signals indicating that localized contamination mechanisms dominate during winter months. ITSA findings highlighted the importance of hydrogeological time lags: for example, a significant E. coli detection rate increase (2.4% vs 1.8%, p = 0.02) was identified 12 weeks after the May 2017 flood event. Unsupervised machine learning spatially classified annual contamination cycles across Ontarian subregions (n = 27), with the highest inter-cluster variability identified among E. coli detection rates and the lowest among NEC detection rates and the NEC:E. coli ratio. Given the spatiotemporal consistency identified for NEC and the NEC:E. coli ratio, associated interpretations and recommendations are likely transferable across large, heterogeneous regions. The presented study may serve as a methodological blueprint for future temporal investigations employing "big" groundwater quality data.

Human health risk from groundwater consumption: A case study in the Apaaso-Tafo Community in the Bono East Region of Ghana

Water is a nutrient for life and a resource for human development, and therefore towns and cities often build treatment systems to provide wholesome water for consumption, bathing, washing, etc. For rural communities where centralised water treatment plants are lacking, groundwater (GW) is often the resource of choice due to its relatively low pathogenic loading and turbidity. However, GW is highly susceptible to contamination from anthropogenic activities. In the Bono East region of Ghana, 94 % of solid waste and 89 % of wastewater are disposed of on the roadside without treatment, posing a contamination risk to water resources. Despite the potential for GW contamination in the region, few researchers have assessed GW quality, and none has evaluated the human infectious risk from GW consumption. In this case study, GW quality in the Apaaso-Tafo community in the region was assessed and the infectious health risks posed to consumers were evaluated. Twenty GW samples were collected from ten boreholes. The concentrations of metals (Ca2+, Mg2+ and Fe) were determined using atomic absorption spectroscopy, bacteria (total and faecal coliform) using Multiple Tube Fermentation and Membrane Filter Techniques, and physicochemical qualities using electrometric, titrimetric, argentometric and spectrophotometric methods. The water quality indices (WQI) and the infection probability from drinking the GW were computed. The WQI showed that most (80 %) GW samples are within acceptable limits. Except for the pH, temperature, turbidity and total coliform bacteria, all parameters met the WHO standards. 40 % of the boreholes contained 50 to 500 cfu/100 mL of coliform bacteria and posed daily infection risks between 1 and 7.63 %. It is recommended that standpipes on boreholes be fitted with membrane or nano filters capable of removing bacteria and viruses to reduce infection risk. The authorities should also monitor GW quality regularly and respond to changes in quality with the appropriate intervention such as issuing 'boil-before-drinking' notices to consumers or encouraging parents to provide bottled and sachet water for their young children. Future research with an increased number of communities, sample size and sampling frequency should also be conducted to enhance the generalisability of these findings.

Evaluating the effectiveness of community-informed resource dissemination at increasing knowledge and testing rates among private well water owners in a statewide population

BACKGROUND

Threats to groundwater quality pose health risks to private well owners. Knowledge gaps are the main reason for low testing rates. Yet, few studies have examined the extent to which community-informed resource distribution increases knowledge and promotes private well testing.

OBJECTIVES

Evaluate the effectiveness of resource dissemination in promoting increased knowledge and private well testing.

METHODS

Community-informed resources were developed that included 6 domains: regulation, testing recommendations, local resources, rationale for testing, state and federal resources, and mitigation actions. They were disseminated to n = 1423 Survey of the Health of Wisconsin participants. Participants completed evaluations at the time of dissemination and one year later. Logistic regression models examined knowledge and behavior changes because of the resource sheet by demographics.

RESULTS

About 50% of respondents reported increased knowledge on most domains of the resource sheet; 80% reported increased knowledge on at least one domain. About 13% tested their well in the last year because of the resource sheet. Because of the resource sheet, seeking out information in the last year was 2.47 (95% CI: 1.04-5.87) times higher among those ≥65 years of age after adjustment, and private well testing was 5.46 (95% CI: 2.15-13.9) times higher among households with ≥$100,000 annual income.

DISCUSSION

Direct information distribution to private well owners can benefit many rural residents and promote well testing. Findings from this study highlight outreach disparities to private well owners. Future work should identify unique barriers and motivators to testing, and preferred communication media, among low-income and younger private well-owners.

The use of E. coli phylogrouping and microbial source tracking (non-species specific, human-specific, bovine-specific bacteroidales markers) to elucidate hydro(geo)logical contamination mechanisms in southeastern Ontario, Canada

In Ontario, monitoring, maintenance, and treatment of private drinking systems (e.g. wells) are the responsibility of the well owner. Fecal contamination of drinking water threatens public health, particularly in rural communities which are often fully reliant on unregulated private groundwater as a primary drinking water source. Private well users face a higher risk of acute gastrointestinal illness compared to those served by municipally operated systems (Murphy et al., 2016). Accordingly, the current study sought to characterize the fecal indicator, E. coli, isolated from southeastern Ontario private groundwater wells, including phylogroups and host source. Results were examined in the context of antecedent climate and local hydrogeological setting to elucidate likely contaminant sources and pathways. A total of 737 E. coli isolates from 260 private wells were assigned to phylogroups using the Clermont PCR phylotyping method, with likely host source determined using host-specific Bacteroidales 16S rRNA RT qPCR assays. Multivariate models were developed for the main E. coli phylogroups (A, B1, B2, and D) and all microbial source tracking markers. Models were coupled for interpretation where possible, based on associations between phylogroups and MST markers. Preferential subsurface flow, and to a lesser degree, overland flow, were likely mechanisms of contamination across all models. Distinct temporal associations were found based on the fecal source. Multiple models were developed and will be discussed, in an attempt to elucidate source-specific contamination mechanisms, in support of risk assessment and appropriate protective actions.

Development of a "big data" groundwater microbial contamination index and spatial comparisons with enteric infection rates in southern Ontario

Big data have become increasingly important for policymakers and scientists but have yet to be employed for the development of spatially specific groundwater contamination indices or protecting human and environmental health. The current study sought to develop a series of indices via analyses of three variables: Non-E. coli coliform (NEC) concentration, E. coli concentration, and the calculated NEC:E. coli concentration ratio. A large microbial water quality dataset comprising 1,104,094 samples collected from 292,638 Ontarian wells between 2010 and 2021 was used. Getis-Ord Gi* (Gi*), Local Moran's I (LMI), and space-time scanning were employed for index development based on identified cluster recurrence. Gi* and LMI identify hot and cold spots, i.e., spatially proximal subregions with similarly high or low contamination magnitudes. Indices were statistically compared with mapped well density and age-adjusted enteric infection rates (i.e., campylobacteriosis, cryptosporidiosis, giardiasis, verotoxigenic E. coli (VTEC) enteritis) at a subregional (N = 298) resolution for evaluation and final index selection. Findings suggest that index development via Gi* represented the most efficacious approach. Developed Gi* indices exhibited no correlation with well density, implying that indices are not biased by rural population density. Gi* indices exhibited positive correlations with mapped infection rates, and were particularly associated with higher bacterial (Campylobacter, VTEC) infection rates among younger sub-populations (p < 0.05). Conversely, no association was found between developed indices and giardiasis rates, an infection not typically associated with private groundwater contamination. Findings suggest that a notable proportion of bacterial infections are associated with groundwater and that the developed Gi* index represents an appropriate spatiotemporal reflection of long-term groundwater quality. Bacterial infection correlations with the NEC:E. coli ratio index (p < 0.001) were markedly different compared to correlations with the E. coli index, implying that the ratio may supplement E. coli monitoring as a groundwater assessment metric capable of elucidating contamination mechanisms. This study may serve as a methodological blueprint for the development of big data-based groundwater contamination indices across the globe.

Private groundwater contamination and risk management: A comparative scoping review of similarities, drivers and challenges across two socio-economically developed regions

Consolidation of multi-domain risk management research is essential for strategies facilitating the concerted government (educational) and population-level (behavioural) actions required to reduce microbial private groundwater contamination. However, few studies to date have synthesised this literature or sought to ascertain the causal generality and extent of supply contamination and preventive responses. In light of the Republic of Ireland (ROI) and Ontario's high reliance and research focus on private wells and consequent utility for empirical comparison, a scoping review of pertinent literature (1990-2022) from both regions was undertaken. The SPICE (Setting, Perspective, Intervention, Comparison, Evaluation) method was employed to inform literature searches, with Scopus and Web of Science selected as primary databases for article identification. The review identified 65 relevant articles (Ontario = 34, ROI = 31), with those investigating well user actions (n = 22) and groundwater quality (n = 28) the most frequent. A markedly higher pooled proportion of private supplies in the ROI exhibited microbial contamination (38.3 % vs. 4.1 %), despite interregional similarities in contamination drivers (e.g., weather, physical supply characteristics). While Ontarian well users demonstrated higher rates of historical (≥ 1) and annual well testing (90.6 % vs. 71.1 %; 39.1 % vs. 8.6 %) and higher rates of historical well treatment (42.3 % vs. 24.3 %), interregional levels of general supply knowledge were analogous (70.7 % vs. 71.0 %). Financial cost, organoleptic properties and residence on property during supply construction emerged as predictors of cognition and behaviour in both regions. Review findings suggest broad interregional similarities in drivers of supply contamination and individual-level risk mitigation, indicating that divergence in contamination rates may be attributable to policy discrepancies - particularly well testing incentivisation. The paucity of identified intervention-oriented studies further highlights the importance of renewed research and policy agendas for improved, targeted well user outreach and incentivised, convenience-based services promoting routine supply maintenance.

Targeted amplicon sequencing facilitated a novel risk assessment framework for assessing the prevalence of broad spectrum bacterial and coronavirus diseases

How to effectively leverage wastewater data to estimate the risk of various infectious diseases remains a great challenge. To address this issue, we conducted continuous wastewater surveillance in Dalian city during the summer-autumn seasons of 2022, targeting coronavirus and bacterial diseases. The surveillance included daily sampling at a wastewater treatment plant (WWTP) and weekly sampling in three sewersheds. Targeting the bacteria's 16S rRNA gene and the coronavirus's RNA-dependent RNA polymerase (RdRp) gene, we first employed RT-PCR and amplicon sequencing techniques to analyze the presence and phylogenetic relationship of detected coronavirus and bacterial pathogens. Next, qPCR was used to quantify the abundances of detected coronavirus and bacterial species. Based on the daily shedding dynamics of SARS-CoV-2, a novel model was developed to predict daily new cases. Based on the medium shedding density of 12 pathogens, two thresholds of sewage pathogen load (indicating 0.1 % and 1 % infection rates) were proposed. Our PanCoV RT-PCR detected coronavirus on 12th August and from 26th August to 12th September 2022. Targeted amplicon sequencing further identified human coronavirus OC43 (hCoV-OC43) on 12th August and the SARS-CoV-2 Omicron variant since 26th August in samples from WWTPs and sewersheds. Phylogenetic analysis revealed that hCoV-OC43 from this study belonged to genotype K and suggested a close relationship between the amplified coronavirus sequences from wastewater and clinical samples in a local COVID-19 outbreak on 26th August. Amplicon sequencing targeting the bacterial 16S rRNA gene also revealed the presence of several bacterial pathogens. Finally, we assessed the microbial risk of specific pathogens in sewersheds and identified a number of pathogens that reached high (>1 % prevalence) and medium risk levels (>0.1 % prevalence) at sewershed B. Our findings underline wastewater surveillance as a valuable early warning system for coronavirus and other waterborne bacterial diseases, complementing public health response measures.