Journal of water and health最新文献

Chronic kidney disease of unknown etiology (CKDu) disproportionately affects men in agricultural regions; few studies parse exposures among affected and unaffected women. We conducted a case-control study among women in Sri Lanka, identifying 15 cases, who experienced progressive kidney disease in a prospective study in a CKDu-endemic region. We selected age-matched controls from the same endemic and neighboring non-endemic region. We then assessed differences in self-reported exposures, and analyzed water samples for inorganic and organic chemicals. Women who reported heat exhaustion (OR = 19.3; p = 0.017) and pesticide handling (OR = 12.6; p = 0.011) were more likely cases. Women who used natural fertilizer in home gardens were more likely controls (OR = 0.05; p = 0.008). Cases' water had higher fluoride, sulfate, calcium, and vanadium, and more often contained pesticides at >1 ppb, particularly diazinon, compared with controls from endemic and non-endemic regions. Our study supports prior data linking heat exposure to CKDu and identifies differences in home gardening, pesticide use, and water content among CKDu-affected women.

This study assessed the health risks associated with groundwater contamination by metals and metalloids in the Tabalaopa-Aldama aquifer, located in the arid region of northern Mexico. A total of 40 drinking water wells were sampled and analyzed for elements including arsenic, aluminum, uranium, iron, nickel, and zinc. The results revealed that a significant proportion of the wells exceeded national and international permissible limits for these contaminants. To evaluate the potential impact on public health, three complementary indices were applied: the health risk index, the hazard quotient, and the water quality index. The integrated analysis demonstrated high consistency among the indices, particularly highlighting arsenic, iron, and nickel as critical contaminants. Multivariate statistical techniques further identified key patterns and groupings, revealing that contaminant levels are influenced by geological and hydrological factors such as well depth and flow rate. The integration of the results from these indices through multivariate statistical methods - specifically Principal Component Analysis (PCA) and cluster analysis - provided a valuable assessment of the concordance and divergences between the indices. This allowed for more robust identification of high-risk areas and contributed to better-informed decision-making for targeted water quality management and public health protection.

Hospital wastewater is often a reservoir for multidrug-resistant organisms and clinically significant pathogens such as MRSA. In this cross-sectional study, 90 Staphylococcus aureus isolates recovered from hospital wastewater were comprehensively characterized. The analysis included antimicrobial susceptibility testing, assessment of biofilm formation, spa typing, and PCR-based detection of a wide panel of antibiotic resistance genes as well as key virulence factors. Our results showed that 43.3, 36.7, and 20% of isolates were classified as strong, intermediate, and weak biofilm-forming strains, respectively. Our data indicated that the resistance profile of aac (6')-Ie/aph (2″), msr(A) (8.9%) was the most prevalent pattern. Spa typing revealed that the 90 isolates belonged to 11 particular spa types, including t747 (16.7%), t790 (14.4%), t10795 (13.3%), t005 (11.1%), t044 (7.8%), t030 (7.8%), t037 (7.8%), t008 (6.7%), t421 (5.6%), t860 (4.4%), and t388 (4.4%). All of the VISA and VRSA strains belonged to SCCmec IV/t790 isolates. Among the 39 strong biofilm producers, the majority (28.2%) belonged to SCCmec IV/t790. The mupirocin-resistant strain belonged to the SCCmec IV/t790 (41.2%), SCCmec III/t037 (17.6%), SCCmec IV/t008 (17.6%), SCCmec III/t030 (11.8%), and SCCmec IV/t044 (11.8%) isolates. These findings highlight the value of wastewater surveillance for tracking antimicrobial resistance and guiding public health interventions.

This study aimed to assess the annual disease burden associated with exposure to antimicrobial resistance (AMR) among farmers through the use of irrigation water contaminated with AMR. The probability of infection, the conventional metric in quantitative microbial risk assessment (QMRA), does not capture disease burdens caused by AMR, such as prolonged treatment and more severe illness. To address this, disability-adjusted life years (DALYs) were applied to estimate additional disease burdens due to AMR for diarrhea caused by Escherichia coli and impetigo caused by Staphylococcus aureus. Lake water used for irrigation was contaminated with sulfamethoxazole/trimethoprim (ST)- and tetracycline (TC)-resistant E. coli, linked to fecal pollution from livestock-related facilities, and amoxicillin (AMX)-resistant E. coli, which was widespread across the lake basin. QMRA revealed that the probabilities of infection from both E. coli and S. aureus exceeded the commonly accepted risk of 10^-4. DALY-based estimates showed that AMR increased the annual disease burden by up to 4.2% compared with a non-AMR scenario, and potentially up to +100% under a high-AMR condition. These findings demonstrate that DALYs effectively quantify AMR-related health burdens associated with irrigation water containing directly or indirectly reused wastewater and support decision-making for AMR risk mitigation.

This study demonstrates the use of wastewater monitoring for opioids and other high-risk substances on a university campus, intended to inform public health surveillance and response efforts for youth and transitional age youth. Over a 14-week campaign, we collected 54 grab samples from three campus manholes, including one that isolated flows from a student housing complex, and analyzed them for 24 parent compounds and metabolites using LC-MS/MS. Heroin and its metabolite 6-acetylmorphine were among several opioid-related detections, illustrating how campus wastewater monitoring can capture actionable use events for targeted public health interventions. Fentanyl, norfentanyl, and xylazine were consistently below their method reporting limits across all 54 samples, consistent with recent declines in national overdose and wastewater datasets. The highest detection frequencies were associated with methamphetamine (22-50%), amphetamine (39-83%), and a THC metabolite (50-100%). This study also highlights the implications of sample type (grab vs. composite) and day of week for wastewater-based epidemiology (WBE). Considering that the use of opioid-related WBE as an actionable public health surveillance tool is still relatively new, additional case studies are needed to explore the potential of this emerging tool and increase confidence in deploying public health interventions in response to wastewater data.

Dialysis water quality is critical to patient safety, particularly in relation to bacterial endotoxins, which can pose major health hazards. Environmental variables, such as seasonal flocculation, may influence endotoxin levels in treated water. The purpose of this study was to evaluate the seasonal fluctuation in endotoxin concentrations in dialysis water across a number of hospital-based dialysis centers. Over 12 months, water samples were collected monthly from various places and tested for endotoxin levels using the Limulus Amebocyte Lysate (LAL) assay. The findings demonstrated considerable seasonal changes, with almost 55.5% of the samples surpassing the international threshold of 0.03 EU/mL. Peaks were seen during the warmer months (July-August 2025 and February-March 2025), whereas lower levels were more typical in the winter (November-December 2024). These findings highlight the requirement for seasonally adjusted monitoring and control strategies to maintain water quality and ensure patient safety in dialysis settings.

Silver ions (Ag⁺) are effective antimicrobial agents, but the quantitative role of microbial cell characteristics in governing Ag⁺ reactivity has remained unclear. This study aimed to quantitatively investigate how microbial cell characteristics influence their susceptibility to Ag⁺. Escherichia coli (Gram-negative), Micrococcus luteus (Gram-positive), Aspergillus brasiliensis (fungi), and Candida maltosa (yeast) were exposed to Ag⁺ dosing of 0.05-0.2 mg-Ag/L for 0-60 min. Then, the intrinsic quenching model was applied to the experimental results to quantify species-specific rate constant (k L min^-1 mg^-1), adsorption rate constant (β min^-1), and dilution coefficient (n dimensionless), linking cell features to observe the inactivation kinetics. Free-ion dosing achieved 99.8% disinfection of E. coli and ≥ 88.5% reduction of fungal species within 15 min at just 0.1 mg-Ag/L. E. coli exhibited the fastest Ag⁺ uptake and the highest inactivation rate (k₁₅ min^-1), followed by C. maltosa, A. brasiliensis, and M. luteus, reflecting increasing diffusion barriers. While the previous qualitative studies have clarified the basic mechanisms of Ag⁺ interaction with cells, we extended those insights to the quantitative assessment. By fitting the intrinsic quenching model to the experimental data, we derived species-specific parameters that translate cell characteristics into quantitative metrics, providing a practical basis for optimizing Ag⁺ dosing across microbes.

Wastewater surveillance (WWS) at healthcare facilities is a nascent field with knowledge gaps in the feasibility of conducting such surveillance at this specialized facility type, and for how to best implement and interpret wastewater (WW) data. WWS was piloted at skilled nursing facilities, including conducting tracer studies, optimization of a low-flow strainer for autosampler WW collection, and preliminary testing of a WW access survey. An expanded WW access survey with collaboration from additional partners was distributed to 16 post-acute/long-term care facilities. The lessons learned obtained through the pilot 'use cases' demonstrated minimal clogging and consistent collection of WW using a low-flow strainer (±0.36 L) and tracer studies highlighted the importance to confirm facility effluent source with an average visual dye detection between 1.5 and 2.5 min from the toilet flush. The expanded WW access survey assessed the feasibility of WWS regarding physical onsite manhole access, safety aspects, effluent flow, and other factors, where 75% (12 of 16) of surveyed facilities demonstrated feasibility. Healthcare facility-level WWS includes specialized methodological approaches prior to implementation to achieve the intended public health impact. These considerations support the continued overall goal of detecting emerging biological public health threats at healthcare facilities using WWS.

Wastewater-based epidemiology (WBE) is a powerful tool for tracking chemical and biological markers and for the analysis of population-level health trends. This study adopted a robust multi-stakeholder approach (bringing together key representatives from local administration, health centres, social organizations, water utilities, and academia) to conduct wastewater monitoring using the quadruple helix model, with the aim to enhance stakeholder engagement and improve population health assessments. The substances of abuse of greatest interest to stakeholders, such as cocaine, caffeine, and nicotine consumed in the Barcelona Metropolitan Area (North-East Spain), were evaluated to monitor lifestyle habits. Additionally, the prevalence of enterovirus genogroups (EVs), also selected by stakeholders, was assessed as an indicator of infectious agents. Findings were correlated with socioeconomic variables to gain insight into territorial disparities. This study proposes an innovative pathway for WBE by integrating social science to contextualise wastewater-derived data, thereby streamlining the interpretation of findings to inform decision-making.

Conventional water quality indices (WQIs), such as the Canadian Council of Ministers of the Environment Water Quality Index (CCME-WQI), typically assign equal weights to all parameters - a practice that may obscure the health relevance of pollutants with chronic toxicity. This study proposes a health risk-weighted variant of the CCME-WQI that integrates multivariate statistical analysis and toxicological criteria to enhance public health responsiveness. Using long-term monitoring data from the Dajia River Basin in Taichung, Taiwan (2003-2024), 30 physical and chemical parameters were analyzed using principal component analysis and factor analysis to reduce redundancy and identify key indicators. Ten core parameters were selected based on statistical contribution and health risk thresholds, including hazard quotient (HQ > 1), cancer risk (CR > 10^-4), and IARC classifications. Risk-based weights were assigned accordingly. Seasonal validation showed strong agreement between the optimized and original CCME-WQI models (RMSE = 7.72; p = 0.610), while improving sensitivity to high-risk contaminants such as arsenic, lead, and cadmium, particularly for children. The proposed framework offers a scalable and resource-efficient tool, making it suitable for both centralized and decentralized water quality management contexts, while supporting health-informed monitoring and contributing to Sustainable Development Goal 6.