Understanding common population markers for SARS-CoV-2 RNA normalization in wastewater - A review.

Wastewater monitoring and epidemiology have seen renewed interest during the recent COVID-19 pandemic. As a result, there is an increasing need to normalize wastewater-derived viral loads in local populations. Chemical tracers, both exogenous and endogenous compounds, have proven to be more stable and reliable for normalization than biological indicators. However, differing instrumentation and extraction methods can make it difficult to compare results. This review examines current extraction and quantification methods for ten common population indicators: creatinine, coprostanol, nicotine, cotinine, sucralose, acesulfame, androstenedione 5-hydroindoleacetic acid (5-HIAA), caffeine, and 1,7-dimethyluric acid. Some wastewater parameters such as ammonia, total nitrogen, total phosphorus, and daily flowrate were also evaluated. The analytical methods included direct injection, dilute and shoot, liquid/liquid, and solid phase extraction (SPE). Creatine, acesulfame, nicotine, 5-HIAA and androstenedione have been analysed by direct injection into LC-MS; however, most authors prefer to include SPE steps to avoid matrix effects. Both LC-MS and GC-MS have been successfully used to quantify coprostanol in wastewater, and the other selected indicators have been quantified successfully with LC-MS. Acidification to stabilize the sample before freezing to maintain the integrity of samples has been reported to be beneficial. However, there are arguments both for and against working at acidic pHs. Wastewater parameters mentioned earlier are quick and easy to quantify, but the data does not always represent the human population effectively. A preference for population indicators originating solely from humans is apparent. This review summarises methods employed for chemical indicators in wastewater, provides a basis for choosing an appropriate extraction and analysis method, and highlights the utility of accurate chemical tracer data for wastewater-based epidemiology.

Surveillance of SARS-CoV-2 in nine neighborhood sewersheds in Detroit Tri-County area, United States: Assessing per capita SARS-CoV-2 estimations and COVID-19 incidence.

Wastewater-based epidemiology (WBE) has been suggested as a useful tool to predict the emergence and investigate the extent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In this study, we screened appropriate population biomarkers for wastewater SARS-CoV-2 normalization and compared the normalized SARS-CoV-2 values across locations with different demographic characteristics in southeastern Michigan. Wastewater samples were collected between December 2020 and October 2021 from nine neighborhood sewersheds in the Detroit Tri-County area. Using reverse transcriptase droplet digital polymerase chain reaction (RT-ddPCR), concentrations of N1 and N2 genes in the studied sites were quantified, with N1 values ranging from 1.92 × 102 genomic copies/L to 6.87 × 103 gc/L and N2 values ranging from 1.91 × 102 gc/L to 6.45 × 103 gc/L. The strongest correlations were observed with between cumulative COVID-19 cases per capita (referred as COVID-19 incidences thereafter), and SARS-CoV-2 concentrations normalized by total Kjeldahl nitrogen (TKN), creatinine, 5-hydroxyindoleacetic acid (5-HIAA) and xanthine when correlating the per capita SARS-CoV-2 and COVID-19 incidences. When SARS-CoV-2 concentrations in wastewater were normalized and compared with COVID-19 incidences, the differences between neighborhoods of varying demographics were reduced as compared to differences observed when comparing non-normalized SARS-CoV-2 with COVID-19 cases. This indicates when studying the disease burden in communities of different demographics, accurate per capita estimation is of great importance. The study suggests that monitoring selected water quality parameters or biomarkers, along with RNA concentrations in wastewater, will allow adequate data normalization for spatial comparisons, especially in areas where detailed sanitary sewage flows and contributing populations in the catchment areas are not available. This opens the possibility of using WBE to assess community infections in rural areas or the developing world where the contributing population of a sample could be unknown.

Biomarkers selection for population normalization in SARS-CoV-2 wastewater-based epidemiology.

Wastewater-based epidemiology (WBE) has been one of the most cost-effective approaches to track the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) levels in the communities since the coronavirus disease 2019 (COVID-19) outbreak in 2020. Normalizing SARS-CoV-2 concentrations by the population biomarkers in wastewater is critical for interpreting the viral loads, comparing the epidemiological trends among the sewersheds, and identifying the vulnerable communities. In this study, five population biomarkers, pepper mild mottle virus (PMMoV), creatinine (CRE), 5-hydroxyindoleacetic acid (5-HIAA), caffeine (CAF) and its metabolite paraxanthine (PARA) were investigated and validated for their utility in normalizing the SARS-CoV-2 loads through two normalizing approaches using the data from 64 wastewater treatment plants (WWTPs) in Missouri. Their utility in assessing the real-time population contributing to the wastewater was also evaluated. The best performing candidate was further tested for its capacity for improving correlation between normalized SARS-CoV-2 loads and the clinical cases reported in the City of Columbia, Missouri, a university town with a constantly fluctuating population. Our results showed that, except CRE, the direct and indirect normalization approaches using biomarkers allow accounting for the changes in wastewater dilution and differences in relative human waste input over time regardless flow volume and population of the given WWTP. Among selected biomarkers, PARA is the most reliable population biomarker in determining the SARS-CoV-2 load per capita due to its high accuracy, low variability, and high temporal consistency to reflect the change in population dynamics and dilution in wastewater. It also demonstrated its excellent utility for real-time assessment of the population contributing to the wastewater. In addition, the viral loads normalized by the PARA-estimated population significantly improved the correlation (rho=0.5878, p < 0.05) between SARS-CoV-2 load per capita and case numbers per capita. This chemical biomarker complements the current normalization scheme recommended by CDC and helps us understand the size, distribution, and dynamics of local populations for forecasting the prevalence of SARS-CoV2 within each sewershed.