Coronavirus disease 2019 (COVID-19) is an infectious disease that is mainly spread through aerosolized droplets containing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and is excreted in feces by infected individuals. Sewage surveillance has been applied widely to obtain data on the prevalence of COVID-19 in whole communities. We used SARS-CoV-2 gene targets N1, N2, and E to determine the prevalence of COVID-19 at both municipal and building levels. Frequency analysis of wastewater testing indicated that single markers detected only 85% or less of samples that were detected as positive for SARS-CoV-2 with the three markers combined, indicating the necessity of pairing markers to lower the false-negative rate. The best pair of markers in both municipal and building level monitoring was N1 and N2, which correctly identified 98% of positive samples detected with the three markers combined. The degradation rates of all three targets were assessed at two different temperatures (25 and 35 °C) as a possible explanation for observed differences between markers in frequency. Results indicated that all three RNA targets degrade at nearly the same rate, indicating that differences in degradation rate are not responsible for the observed differences in marker frequency.

The polymerase chain reaction (PCR) is a molecular biology tool with diverse applications in the aquatic sciences. Classical PCR is a nonquantitative method that can be used to detect target DNA sequences that are characteristic of particular microbial taxa but cannot determine their concentrations in water samples. Various quantitative forms of PCR have been developed to remove this limitation. Of these, the two that currently are used most widely are real-time quantitative PCR (qPCR) and droplet digital PCR (ddPCR). Several outlines of the mathematical and statistical basis of these methods for estimating target sequence concentrations are available in the literature, but we are aware of no thorough and rigorous derivation of the theoretical underpinnings of either. The purpose of this review is to provide such derivations, and to identify and compare the main strengths and weaknesses of the two methods. We find that both estimation methods are sound, provided careful attention is paid to specific details that differ between the two. With qPCR, it is especially important to reduce any significant PCR inhibition by sample constituents and to properly fit the standard curve to heteroskedastic calibration data. With ddPCR, it is important to ensure that the value of the mean droplet volume used in calculating concentrations is correct for the particular combination of droplet generator and master mix used. The advantages of qPCR include lower instrument and per-sample costs, a shorter turnaround time for obtaining results, a higher upper limit of quantification, and a wider dynamic range. The advantages of ddPCR include freedom from dependence on a standard curve, an inherently lower sensitivity to PCR inhibitors, a lower limit of quantification, a simpler theoretical basis, and simpler data analysis. We suggest qPCR often will be preferable in laboratory studies where investigators have significant control over the range of target sequence concentrations in samples, concentrations are sufficiently high so proper calibration does not require standards with concentrations low enough to exhibit exaggerated variability in the threshold cycle, and no significant inhibition is present, or more generally, in studies where funding levels do not permit the higher cost of instrumentation and supplies required by ddPCR or where the shorter turnaround time for qPCR is essential. If sufficient funds are available, ddPCR often will be preferable when the ability to quantify low concentrations is important, especially if inhibitors are likely to be present at concentrations that are problematic for qPCR.

Fecal contamination is a common cause of impairment of surface waters. In monitoring studies, it is usually assessed by measuring concentrations of fecal indicator bacteria such as Escherichia coli (E. coli), a common monitoring target in freshwater systems. In this study, we assess the advantages and disadvantages of two common and previously validated methods for monitoring E. coli concentrations at freshwater beaches: Colilert-18^®, with a turnaround time of ca. 18 h, and real-time quantitative PCR (qPCR), with a turnaround time of ca. 3–4 h. Based on data comprising 3081 pairs of Colilert-18 and qPCR estimates of E. coli concentrations in split samples from Michigan’s annual beach monitoring program in 2019 and 2020, we found that qPCR monitoring detected a high percentage of exceedances of the state’s water quality standard for E. coli contamination that went undetected on the day of sampling with Colilert-18 monitoring because qPCR concentration estimates were available on the day of sampling but Colilert-18 estimates were not. However, Colilert-18 data were more useful than qPCR data for the statistical comparison of contamination levels at different beaches, probably in part because Colilert-18 data showed a much lower percentage of concentration estimates outside the method’s range of quantification.

Globally, water resources used for recreation and drinking water are threatened by fecal pollution. These pollutants can cause gastrointestinal illness and environmental degradation. Additionally, most sources of fecal pollution are non-point sources stemming from multiple species. Identifying these sources is vital to categorizing the exposure risk from contact and improving remediation efforts. A common technique to provide species-specific information for fecal source identification is microbial source tracking (MST). MST quantifies DNA of host or host-associated microorganisms through polymerase chain reaction (PCR) technologies such as quantitative PCR (qPCR) or droplet digital PCR (ddPCR). MST techniques have been implemented globally and are used for routine monitoring. In the United States (US), the US Environmental Protection Agency has provided several approved standard PCR methods for MST and other recreational water quality applications. These methods have specified quality controls including sample processing controls (SPC) and assessments for sample inhibition. A standard SPC used in EPA methods involves spiking samples with salmon testes DNA (nominally originating from Chum Salmon, Oncorhynchus keta and quantifying them using Sketa22, a genus specific TaqMan^TM assay). This quality control (QC) behaves similarly to the microbial species being monitored. MST testing in Fall 2022 indicated elevated Sketa22 recoveries and re-analysis of samples indicated the detection of external Salmonidae DNA on both qPCR and ddPCR platforms. Our research was designed to identify the cause of this interference. Results indicate that the primer probe set may react with wild Salmonidae DNA. Analyzing the Sketa22 sequence using BLAST indicated matches with many species of Salmonidae present in the sampled stream system. Consequently, further research is required to identify the effectiveness of Sketa22 as a QC when native and migratory Salmonidae are present. General recommendations are provided to account for excess ambient Salmonidae DNA.