Human Health Risks Associated with Recreational Waters: Preliminary Approach of Integrating Quantitative Microbial Risk Assessment with Microbial Source Tracking

Unraveling urban hydro-environmental response to climate change and MCDA-based area prioritization in a data-scarce developing city

Climate change leads to more frequent and intense heavy rainfall events, posing significant challenges for urban stormwater management, particularly in rapidly urbanizing cities of developing countries with constrained infrastructure. However, the quantitative assessment of urban stormwater, encompassing both its volume and quality, in these regions is impeded due to the scarcity of observational data and resulting limited understanding of drainage system dynamics. This study aims to elucidate the present and projected states of urban flooding, with a specific emphasis on fecal and organic contamination caused by combined sewer overflow (CSO). Leveraging a hydrological model incorporating physical and biochemical processes validated against invaluable observational data, we undertake simulations to estimate discharge, flood volume, and concentrations of suspended solids (SS), Escherichia coli (E. coli), and chemical oxygen demand (COD) within the drainage channel network of Phnom Penh City, Cambodia. Alterations in flood volumes, and pollutant concentrations and loads in overflow under two representative concentration pathways (RCPs 4.5 and 8.5) for extreme rainfall events are projected. Furthermore, we employ a multi-criteria decision analysis (MCDA) framework to evaluate flood risk, incorporating diverse indicators encompassing physical, social, and ecological dimensions. Our results demonstrate the exacerbating effects of climate change on flood volumes, expansion of flooded areas, prolonged durations of inundation, elevated vulnerability index, and heightened susceptibility to pollutant contamination under both scenarios, underscoring increased risks of flooding and fecal contamination. Spatial analysis identifies specific zones exhibiting heightened vulnerability to flooding and climate change, suggesting priority zones for investment in flood mitigation measures. These findings provide crucial insights for urban planning and stormwater management in regions with limited drainage infrastructure, offering essential guidance for decision-making in locales facing similar challenges.

Integrating microbial source tracking with quantitative microbial risk assessment to evaluate site specific risk based thresholds at two South Florida beaches

Quantitative microbial risk assessment (QMRA) can be used to evaluate health risks associated with recreational beach use. This study developed a site-specific risk assessment using a novel approach that combined quantitative PCR-based measurement of microbial source tracking (MST) genetic markers (human, dog, and gull fecal bacteria) with a QMRA analysis of potential pathogen risk. Water samples (n = 24) from two recreational beaches were collected and analyzed for MST markers as part of a broader Beach Exposure And Child Health Study that examined child behavior interactions with the beach environment. We report here the measurements of fecal bacteria MST markers in the environmental DNA extracts of those samples and a QMRA analysis of potential health risks utilizing the results from the MST measurements in the water samples. Human-specific Bacteroides was enumerated by the HF183 Taqman qPCR assay, gull-specific Catellicoccus was enumerated by the Gull2 qPCR assay, and dog-specific Bacteroides was enumerated by the DogBact qPCR assay. Derived reference pathogen doses, calculated from the MST marker concentrations detected in recreational waters, were used to estimate the risk of gastrointestinal illness for both children and adults. Dose-response equations were used to estimate the probability of the risk of infection (Pinf) per a swimming exposure event. Based on the QMRA simulations presented in this study, the GI risk from swimming or playing in water containing a mixture of human and non-human fecal sources appear to be primarily driven by the human fecal source. However, the estimated median GI health risk for both beaches never exceeded the U.S. EPA risk threshold of 32 illnesses per 1,000 recreation events. Our research suggests that utilizing QMRA together with MST can further extend our understanding of potential recreational bather risk by identifying the source contributing the greatest risk in a particular location, therefore informing beach management responses and decision-making.

Viral Metagenomics as a Tool to Track Sources of Fecal Contamination: A One Health Approach

The One Health framework recognizes that human, animal, and environmental health are linked and highly interdependent. Fecal contamination of water, soil, foodstuff, and air may impact many aspects of One Health, and culture, PCR-based, and sequencing methods are utilized in the detection of fecal contamination to determine source, load, and risk to inform targeted mitigation strategies. Viruses, particularly, have been considered as fecal contamination indicators given the narrow host range many exhibit and their association with other biological contaminants. Culture- and molecular-based methods are considered the gold-standards for virus detection and for determining specific sources of fecal contamination via viral indicators. However, viral metagenomics is also being considered as a tool for tracking sources of fecal contamination. In the present review, studies tracking potential sources of fecal contamination in freshwaters, marine waters, foodstuff, soil, and air using viral metagenomics are discussed to highlight the potential of viral metagenomics for optimizing fecal source tracking. Limitations of the use of viral metagenomics to track fecal contamination sources, including sample processing, nucleic acid recovery, sequencing depth, and bioinformatics are also discussed. Finally, the present review discusses the potential of viral metagenomics as part of the toolbox of methods in a One Health approach.

Mobility and risk assessment of heavy metals in benthic sediments using contamination factors, positive matrix factorisation (PMF) receptor model, and human health risk assessment

Metal pollution in benthic sediments was fractionated and modelled to quantify the risk of anthropogenic activities on river ecosystems. In this study, the individual contamination factor (ICF) and the global contamination factor (GCF) were used to measure the contamination levels in the sediments. On the other hand, the mobility factor (MF) was used to quantify the mobility of heavy metals in benthic river sediments. The factors used to assess pollution in benthic sediments employ bioavailable fractions of heavy metals, which have a greater chance of release into aquatic sediments and hence are more dangerous to the environment. Heavy metal mobility (MF) is highest in the post-monsoon season for Zn, Pb, Cu, and Co; Fe in winter; Mn in pre-monsoon; and Cd in monsoon. This means that heavy metals accumulate in benthic sediments during the post-monsoon season when river flows are less turbulent. ICF and GCF data show that pollution levels are higher post-monsoon than the rest season levels. Sediment samples were further subjected to the positive matrix factorization (PMF) model, which identified four factors that explained the variation in the study: factor 1 is concerned with anthropogenic Cu, Cd, and Co pollution, while factors 2, 3, and 4 are concerned with Fe, Mn, and Zn pollution. Finally, the total cancer risk (TCR) and hazard index (HI) are employed to quantify the risk to human health from accidental ingestion and dermal exposure. According to the risk outcomes from probabilistic and deterministic approaches, river exposure is dangerous to human health, with dermal absorption being the most significant concern of the exposure paths.

Detangling Seasonal Relationships of Fecal Contamination Sources and Correlates with Indicators in Michigan Watersheds

Despite the widely acknowledged public health impacts of surface water fecal contamination, there is limited understanding of seasonal effects on (i) fate and transport processes and (ii) the mechanisms by which they contribute to water quality impairment. Quantifying relationships between land use, chemical parameters, and fecal bacterial concentrations in watersheds can help guide the monitoring and control of microbial water quality and explain seasonal differences. The goals of this study were to (i) identify seasonal differences in Escherichia coli and Bacteroides thetaiotaomicron concentrations, (ii) evaluate environmental drivers influencing microbial contamination during baseflow, snowmelt, and summer rain seasons, and (iii) relate seasonal changes in B. thetaiotaomicron to anticipated gastrointestinal infection risks. Water chemistry data collected during three hydroclimatic seasons from 64 Michigan watersheds were analyzed using seasonal linear regression models with candidate variables including crop and land use proportions, prior precipitation, chemical parameters, and variables related to both wastewater treatment and septic usage. Adaptive least absolute shrinkage and selection operator (LASSO) linear regression with bootstrapping was used to select explanatory variables and estimate coefficients. Regardless of season, wastewater treatment plant and septic system usage were consistently selected in all primary models for B. thetaiotaomicron and E. coli. Chemistry and precipitation-related variable selection depended upon season and organism. These results suggest a link between human pollution (e.g., septic systems) and microbial water quality that is dependent on flow regime.

IMPORTANCE In this study, a data set of 64 Michigan watersheds was utilized to gain insights into fecal contamination sources, drivers, and chemical correlates across seasons for general E. coli and human-specific fecal indicators. Results reaffirmed a link between human-specific sources (e.g., septic systems) and microbial water quality. While the importance of human sources of fecal contamination and fate and transport variables (e.g., precipitation) remain important across seasons, this study provides evidence that fate and transport mechanisms vary with seasonal hydrologic condition and microorganism source. This study contributes to a body of research that informs prioritization of fecal contamination source control and surveillance strategy development to reduce the public health burden of surface water fecal contamination.

Human Health Risk Assessment for Exposure to Potentially Toxic Elements in Polluted Rivers in the Ecuadorian Amazon

Anthropogenic activities performed in the Ecuadorian Amazon have released potentially toxic elements (PTEs) into the rivers, causing severe environmental pollution and increasing the risk of exposure to the residents of the surrounding areas. This study aims to carry out a human health risk assessment using deterministic and probabilistic methods to estimate the hazard index (HI) and total cancer risk (TCR) related to multi-pathway human exposure to PTEs in polluted rivers. Concentrations of Al, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in surface water and sediment samples from rivers on the Ecuadorian Amazon were considered to assess the potential adverse human health effects. As a result, deterministic and probabilistic estimations of cancer and non-cancer risk through exposure to surface waters and sediments were above the safety limit. A sensitivity analysis identified the concentration of PTEs and the exposure duration (ED) as the two most important variables for probabilistic health risk assessment. The highest risk for receptors was related to exposure to polluted sediments through incidental ingestion and dermal contact routes. According to the deterministic estimation, the human health risk through ingestion of water was above the threshold in specific locations. This study reveals the potential health risk to which the population is exposed. This information can be used as a baseline to develop public strategies to reduce anthropogenic pollution and exposure to PTEs in Ecuadorian Amazon rivers.

Uneven genotypic diversity of Escherichia coli in fecal sources limits the performance of a library-dependent method of microbial source tracking on the southwestern French Atlantic coast

To develop a library-dependent method of tracking fecal sources of contamination of beaches on the Atlantic coast of southwestern France, a library of 6368 Escherichia coli isolates was constructed from samples of feces, from 40 known human or animal sources collected in the vicinity of Arcachon Bay in 2010, and in French Basque Country, Landes, and Béarn, between 2017 and 2018. Different schemes of source identification were tested: use of the complete or filtered reference library; characterization of the isolates by genotypic or proteomic profiling based on ERIC-PCR or MALDI-TOF mass spectrometry, respectively; isolate by isolate assignment using either classifiers based on the Pearson similarity or SVM (support vector machine). With the exception of one source identification scheme, which was discarded since it used self-assignment, all tested schemes resulted in low rates of correct classification (<35%) and significant rates of incorrect classification (>15%). The heterogeneous coverage of E. coli genotypic diversity between sources and the uneven distribution of E. coli genotypes in the library likely explain the difficulties encountered in identifying the sources of fecal contamination. Shannon diversity index of sources ranged from 0 for several wildlife species sampled once to 3.03 for sewage treatment plant effluents sampled on various occasions, showing discrepancies between sources. The uneven genotypic composition of the library was attested by the value of the Pielou index (0.54), the high proportion of nondiscriminatory genotypes (>91% of the isolates), and the very low proportion of discriminatory genotypes (<3%). Since efforts made to constitute such a library are not affordable for routine analyses, the results question the relevance of developing such a method for identifying sources of fecal contamination on such a coastline.