Antimicrobial resistance (AMR) threatens our modern standard of living with the potential return to a pre-antibiotic condition where deadly infections are no longer treatable. Wastewater treatment plants (WWTPs) are vital components in water sanitation infrastructure and are now also being recognized as valuable monitoring points for antibiotics, antibiotic resistant bacteria (ARB), and antibiotic resistance genes (ARGs) disposed of or excreted by human populations. Hospital waste water is of special interest as a potential focused monitoring point and in general research is needed to establish the benefits of both on-site and community-scale wastewater treatment as important barriers to the disseminators of ARGs into the environment. The research aims described herein examine these components of wastewater treatment and how they relate to AMR indicators identified through metagenomic sequencing. Through monitoring of local WWTPs, it was found that AMR indicators shifted over time and in relation to human behavior that changed due to the COVID-19 pandemic. Hospital wastewater did not measurably impact the microbiome during simulated activated sludge wastewater treatment according to broad-scale metagenomic ARG profiling; however, some clinically-relevant ARGs escaped treatment. Lastly, a study of a transect of WWTPs indicated impacts on the abundance of certain ARGs in downstream riverine receiving environments. Nonetheless, there appeared to be a number of other factors at play, and upstream and downstream resistomes tended to remain similar, calling for further research to delineate impacts of various wastewaters and treatments on ARGs in affected aquatic environments. / Doctor of Philosophy / Antimicrobial resistance (AMR) occurs when bacteria, viruses, and fungi are able to survive in the presence of antibiotics because they carry antibiotic resistance genes (ARGs) encoded in their DNA. AMR is a major public health concern as it makes it so that antibiotics are no longer effective against potentially deadly infections. Wastewater treatment plants (WWTPs) are being discovered as a hub of opportunity for monitoring potential AMR problems in a community. WWTPs receive sewage from homes and various industries. This sewage contains rich information for researchers to examine in terms of which antibiotics, bacteria, and ARGs are circulating in the community. This makes it possible to find out which antibiotics are being consumed in the community and which ARGs might be prevalent. The purpose of this research was to better understand both how WWTPs can be used as monitoring points for AMR and how they can be improved to help reduce ARGs emitted to rivers and streams where treated water is discharged. It was found that the types of ARGs prevalent in wastewater changed over time, especially during the COVID-19 pandemic as people worked from home and changed habits regarding doctors' visits, which impacted antibiotic use. Hospital sewage was studied as a useful indicator of pathogens and ARGs that are challenging a community and also the antibiotics being used. This research explored what happened to ARGs during the treatment of domestic (i.e., from people's homes) wastewater along with hospital wastewater and found that hospital wastewater introduced some ARGs that are typically found in clinical settings, but did not negatively impact the overall wastewater treatment process. Finally, the impact that WWTPs have on rivers to which treated water is discharged was explored. The results indicated that certain ARGs were elevated downstream of the WWTPs. However, when examining all ARGs together, no major shifts due to the treated wastewater were apparent.

A rural-urban divide in health status and healthcare infrastructure has been well-documented in the U.S., where populations residing in census regions classified as rural often exhibit more negative health outcomes, adverse health behaviors, and have reduced access to affordable and proximal health services, compared to their urban and peri-urban counterparts. However, it is important to note that such disparities vary based on specific rural regions and individual circumstances. Rural areas may face elevated risk factors for infectious diseases such as increased proximity to wildlife and livestock and disproportionately high reliance on private, non-federally regulated, primary drinking water sources. Chronic conditions prevalent in rural communities such as diabetes and hypertension are frequently linked with longer duration and higher severity of symptoms than in urban areas; this association suggests that the risk of exposure to infectious diseases and the likelihood of progression to serious illness and hospitalization may be elevated, although this is not universally the case across all rural settings. Alongside documented urban-rural health disparities, there also exist disparities in the nature and quality of data on health-related behaviors, outcomes, and service provision in rural areas compared to urban and peri-urban regions. In this dissertation, two key environmental matrices –drinking water and wastewater– were highlighted as vectors of information to better estimate levels of contaminant exposures and health outcomes in rural communities. First, baseline data on drinking water contaminant levels and associated health outcome data were highlighted as crucial for refining holistic exposure estimates as well as understanding drinking water related health burdens in rural communities where a larger proportion of households use private drinking water sources, such as well water, that are not federally regulated. Second, systematic sampling and testing of pathogen biomarkers in wastewater to non-invasively measure population-level health status, also known as wastewater based surveillance (WBS) and, depending on the context, wastewater based epidemiology (WBE) is not constrained by disadvantages of clinical testing, e.g., limited health-care access, long travel times to testing facilities, delay between symptom-onset and testing. Thus, expanded implementation of WBS in rural communities is proposed here as a strategy to address data disparities in clinical testing for infectious diseases. Collectively, this dissertation advances knowledge on estimated drinking water contaminant levels, exposures, and associated public health outcomes and corresponding research gaps in rural Appalachian U.S., and elucidates pathways toward best practices and considerations for public-health focused wastewater testing adoption in rural communities. For the latter, the question of whether WBS challenges unique to rural wastewater systems hinder application of WBS in small, rural communities was explored, as well as methods to advance best-practices for rural WBS. To summarize existing publicly available peer-reviewed literature on drinking water contaminants in rural Appalachian U.S., in Chapter 2, a systematic review and meta-analysis of microbial and chemical drinking water contaminants was performed. Key contaminants were identified as being elevated beyond regulatory, health-based, maximum contaminant levels in our meta-analyses from rural drinking water sources in Appalachia, including E coli, lead, arsenic, uranium. Overall, we found data on drinking water source quality under baseline conditions (i.e., rather than post anomalous contamination events such as chemical spills) in rural Appalachian U.S. was sparse relative to widespread media coverage on the issue. Epidemiologic-based research studies that collected both drinking water exposure data and paired health outcome data were also limited. As a result, although some instances of anomalously high levels of drinking water contaminants were identified in rural Appalachia from the published literature, we could not obtain a clear picture of baseline exposures to drinking water contaminants in most rural Appalachian communities, highlight need to address these knowledge gaps. In Chapter 3, to evaluate whether wastewater could serve as a reliable metric for estimating community circulation of viruses and antimicrobial resistance (AMR) markers, even when sourced from aging and low-resource sewer collection networks, a 12-month wastewater monitoring study was conducted in a small, rural sewer conveyance system with pronounced infrastructural challenges. Specifically, the field site under study was compromised with heavy inflow and infiltration (IandI). Detection rates and concentrations of viral, AMR, and human fecal markers were grouped by levels of IandI impact across the sewershed, and location-, date-, and sample- specific variables were assessed for their relative influence on viral, AMR, and human fecal marker signal using generalized linear models (GLMs). We found that while IandI likely adversely impacted the magnitude of wastewater biomarker signal to some extent throughout the sewershed, especially up-sewer at sites with more pronounced IandI, substantial diminishment of wastewater signal at WWTP influent was not observed in response to precipitation events. Thus, our data indicated that WWTP influent sampling alone can still be used to assess and track community circulation of pathogens in heavily IandI impacted systems, particularly for ubiquitously circulating viruses less prone to dilution induced decay. Delineations were also made for what circumstances up-sewer sampling may be necessary to better inform population shedding of pathogens, especially where IandI is prevalent. Various normalization strategies have been proposed to account for sources of variability for deriving population-level pathogen shedding from wastewater, including those introduced by IandI-driven dilution. Thus, in Chapter 4, we evaluated the temporal and spatial variability of viral and AMR marker signal in wastewater at different levels of IandI, both unnormalized and with the adoption of several normalization strategies. We found that normalization using physicochemical-based wastewater strength metrics (chemical oxygen demand, total suspended solids, phosphate, and ammonia) resulted in higher temporal and site-specific variability of SARS-CoV-2 and human fecal biomarker signal compared to unnormalized data, especially for viral and AMR marker signal measured in wastewater from sites with pronounced IandI. Viral wastewater signal normalized to physicochemical wastewater strength metrics and flow data also closely mirrored precipitation trends, suggesting such normalization approaches may more closely scale wastewater trends towards precipitation patterns rather than per capita signal in an IandI compromised system. We also found that in most cases, normalization did not significantly alter the relationship between wastewater trends and clinical infection trends. These findings suggest a degree of caution is warranted for some normalization approaches, especially where precipitation driven IandI is heightened. However, data and findings largely supported the utility of using human fecal markers such as crAssphage for normalizing wastewater signal to address site-specific differences in dilution levels, since viral signal scaled to this metric did not result in strong correlations between precipitation and wastewater trends, higher spatial and temporal variation was not observed, and strong correlations were observed between viral signal and viral infection trends. Finally, in chapter 5, we assessed the relationship between monthly Norovirus GII, Rotavirus, and SARS-CoV-2 wastewater trends with seasonal infection trends for each of the viruses to ascertain whether WBE could be used in a rural sewershed of this size with substantial IandI impacts to track and potentially predict population level infection trends. Though up-sewer, or near-source sampling, at sites with permanent IandI impacts did not exhibit a clear relationship with seasonal infection trends for Rotavirus, SARS-CoV-2, and Norovirus GII, WWTP influent signal and consensus signals aggregated from multiple up-sewer sites largely mirrored expected seasonal trends. Findings also suggested that for more ubiquitous viral targets, such as SARS-CoV-2, viral trends measured at WWTP influent in a small IandI impacted system may still provide a sufficiently useful measure of infection trends to inform the use of WBE (assuming appropriate normalization to sewershed population). These findings elucidate the potential utility and relative robustness of wastewater testing to ascertain community-level circulation of pathogens in small, rural sewersheds even those compromised by extensive IandI inputs. Overall, this dissertation examined drinking water and wastewater as critical metrics for assessing contaminant exposures and infectious disease trends in rural communities, particularly in the context of small, rural communities which tend to have more limited health infrastructure and lower-resource wastewater systems. Overall, findings underscore the need for baseline data on drinking water quality by identifying gaps in current knowledge and calling for further research to better understand drinking water contaminant exposure levels in rural areas. Wastewater as a non-invasive, population-level health metric was evaluated in the context of a small, rural sewer system overall, and by varying observed levels of IandI, as well as associated tradeoffs for normalization adoption. By evaluating these environmental surveillance metrics using both desk-based and field-based research study designs, findings from this dissertation offer valuable insights and practical recommendations for improving baseline drinking water quality monitoring and wastewater pathogen testing, all with the overarching goal of supporting more targeted public health interventions in rural settings. / Doctor of Philosophy / In the United States, there is a significant health and healthcare gap between rural and urban areas. Rural communities often face worse health outcomes, poorer health behaviors, and have less access to affordable and nearby healthcare services compared to their urban and peri-urban counterparts. Additionally, rural areas are exposed to higher risks for infectious diseases due to closer proximity to wildlife and livestock and proportionately lower access to regulated drinking water sources. Chronic conditions like diabetes and hypertension, which are more common in rural populations, can exacerbate the severity and duration of symptoms for infectious diseases, potentially leading to more serious illness and hospitalizations. Despite these heightened risks, data on health behaviors, outcomes, and healthcare services in rural areas is often lacking and less comprehensive compared to urban regions. This dissertation investigates two promising avenues of improving monitoring to provide information needed to better understand and address contaminant exposures and health trends in rural communities: drinking water and wastewater. Firstly, this dissertation underscores the importance of establishing baseline data on drinking water quality. This is essential for accurately estimating exposure levels and understanding the health impacts associated with elevated levels of drinking water contaminants, particularly in rural areas where a higher share of primary drinking water sources is unregulated by the federal government compared to urban areas. This study reveals significant gaps in current knowledge and highlights the need for more research to provide a clearer picture of drinking water quality in these communities. Secondly, this dissertation explores the use of wastewater as a non-invasive tool for assessing community health. This method, known as wastewater-based surveillance (WBS) or wastewater-based epidemiology (WBE), offers a way to measure population-level health trends without relying on clinical testing, which can be limited by factors such as access to healthcare and delays in testing. The dissertation evaluates how effective wastewater monitoring can be in small, rural sewer systems, even when these systems face challenges like aging infrastructure and significant inflow and infiltration (IandI) from groundwater and surface water. It examines how different normalization strategies for wastewater data can influence the reliability of this method and how wastewater testing can be adapted to account for varying levels of IandI. Overall, the dissertation provides valuable insights into the effectiveness of using drinking water and wastewater as environmental metrics for informing public health intervention strategies in rural settings. It offers justifications for improving drinking water quality monitoring and wastewater testing practices, aiming to support more targeted and effective public health interventions in rural communities. By addressing the challenges and limitations associated with these environmental monitoring strategies this research contributes to a better understanding of how to reduce health data disparities in rural areas.