As the return to normality in the wake of the COVID-19 pandemic enters its early stages, the necessity for accurate, quick, and community-wide surveillance of SARS-CoV-2 has been emphasized. Wastewater-based epidemiology (WBE) has been used across the world as a tool for monitoring the pandemic, but studies of its efficacy in comparison to the best-known method for surveillance, randomly selected COVID-19 testing, has limited research. This study evaluated the trends and correlations present between SARS-CoV-2 in the effluent wastewater of a large university campus and random COVID-19 testing results published by the university. A moderately strong positive correlation was found between the random testing and WBE surveillance methods (r = 0.63), and this correlation was strengthened when accommodating for lost samples during the experiment (r = 0.74).

Diabetes affects millions of people globally and can lead to other severe health complications when undiagnosed or not properly managed. The incidence of diabetes has rapidly increased over the past several years, however, not all individuals have access to affordable or convenient healthcare. We hypothesize that wastewater-based epidemiology (WBE) has the potential to assess community health status by analyzing biomarkers indicative of human health and disease, including diabetes. Used in tandem with current methods, monitoring indicators of diabetes in community wastewater could provide a comprehensive assessment tool for disease prevalence in large and small populations. Specifically, the proposed targeted biomarker evaluated in this study to indicate population-wide diabetes prevalence was 8-hydroxy-2’- deoxyguanosine (8-OHdG). This work combines a rigorous literature review and initial laboratory studies to explore the possibility of diabetes monitoring at the community level using WBE. Here, 24-hour composite wastewater samples were collected from within two wastewater sub-catchments of Greater Tempe, AZ. Overall goals of this study were to: i) Determine the feasibility to detect endogenous markers of diabetes in community wastewater; ii) Assess the potential impact of confounding factors, such as smoking, cancer, and atherosclerosis, through a literature analysis; and iii) Evaluate the socioeconomic status and demographics of the study population. Preliminary results of the experiments suggest this methodology to be feasible, as indicated by the observation of detectable signals of 8-OHdG in community wastewater collected from the sewer infrastructure; however, future work and continued experimentation will be required to address low signal intensity and assay precision and accuracy. Thus, the work presented here provides valuable proof-of-concept data, with detailed information on the method employed and identified opportunities to further determine the relationship between 8-OHdG concentrations in municipal wastewater and diabetes prevalence at the community level.

Diabetes affects millions of people globally and can lead to other severe health complications when undiagnosed or not properly managed. The incidence of diabetes has rapidly increased over the past several years, however, not all individuals have access to affordable or convenient healthcare. We hypothesize that wastewater-based epidemiology (WBE) has the potential to assess community health status by analyzing biomarkers indicative of human health and disease, including diabetes. Used in tandem with current methods, monitoring indicators of diabetes in community wastewater could provide a comprehensive assessment tool for disease prevalence in large and small populations. Specifically, the proposed targeted biomarker evaluated in this study to indicate population-wide diabetes prevalence was 8-hydroxy-2’-deoxyguanosine (8-OHdG). This work combines a rigorous literature review and initial laboratory studies to explore the possibility of diabetes monitoring at the community level using WBE. Here, 24-hour composite wastewater samples were collected from within two wastewater sub-catchments of Greater Tempe, AZ. Overall goals of this study were to: i) Determine the feasibility to detect endogenous markers of diabetes in community wastewater; ii) Assess the potential impact of confounding factors, such as smoking, cancer, and atherosclerosis, through a literature analysis; and iii) Evaluate the socioeconomic status and demographics of the study population. Preliminary results of the experiments suggest this methodology to be feasible, as indicated by the observation of detectable signals of 8-OHdG in community wastewater collected from the sewer infrastructure; however, future work and continued experimentation will be required to address low signal intensity and assay precision and accuracy. Thus, the work presented here provides valuable proof-of-concept data, with detailed information on the method employed and identified opportunities to further determine the relationship between 8-OHdG concentrations in municipal wastewater and diabetes prevalence at the community level.

The COVID-19 pandemic caused uncertainty and changing public health recommendations across the world as our understanding of the SARS-CoV-2 virus changed. Following a preliminary assessment by the World Health Organization, non-steroidal anti-inflammatory drugs were said to worsen symptoms and should be avoided before the recommendation was subsequently revoked. There also was pain associated with infection, leading to the hypothesis that use of over-the-counter pain medication increases may correlate with increases of SARS-CoV-2 infections. Wastewater samples were collected from two communities in Tempe, AZ from December 2019 to July 2020 (n = 35) and were analyzed by liquid chromatography tandem mass spectrometry (LC-MS/MS) to identify levels of acetaminophen, ibuprofen and their metabolites, acetaminophen sulfate and carboxy-ibuprofen. Results showed 100% detection frequency of all analytes in all samples across the duration of the study. Mass loadings of acetaminophen (918.4 g day-1 +/- 354.8 g day-1) were higher than ibuprofen (182.9 g day-1 +/- 49.8 g day-1), potentially driven by flushing behaviors rather than consumption activities. However, ibuprofen was more heavily consumed than acetaminophen across all days of the study period. Comparisons to COVID-19 clinical cases data showed increased use in ibuprofen with increases in clinical cases loads, while acetaminophen showed no change, suggesting ibuprofen was the over the counter (OTC) medication of choice during the first wave of the pandemic.