Quantitative analysis of SARS-CoV-2 RNA from wastewater solids in communities with low COVID-19 incidence and prevalence.

Wastewater-based epidemiology may be useful for informing public health response to viral diseases like COVID-19 caused by SARS-CoV-2. We quantified SARS-CoV-2 RNA in wastewater influent and primary settled solids in two wastewater treatment plants to inform the preanalytical and analytical approaches and to assess whether influent or solids harbored more viral targets. The primary settled solids samples resulted in higher SARS-CoV-2 detection frequencies than the corresponding influent samples. Likewise, SARS-CoV-2 RNA was more readily detected in solids using one-step digital droplet (dd)RT-PCR than with two-step RT-QPCR and two-step ddRT-PCR, likely owing to reduced inhibition with the one-step ddRT-PCR assay. We subsequently analyzed a longitudinal time series of 89 settled solids samples from a single plant for SARS-CoV-2 RNA as well as coronavirus recovery (bovine coronavirus) and fecal strength (pepper mild mottle virus) controls. SARS-CoV-2 RNA targets N1 and N2 concentrations correlated positively and significantly with COVID-19 clinically confirmed case counts in the sewershed. Together, the results demonstrate that measuring SARS-CoV-2 RNA concentrations in settled solids may be a more sensitive approach than measuring SARS-CoV-2 in influent.

SARS-CoV-2 RNA in Wastewater Settled Solids Is Associated with COVID-19 Cases in a Large Urban Sewershed.

Viral genome sequencing has guided our understanding of the spread and extent of genetic diversity of SARS-CoV-2 during the COVID-19 pandemic. SARS-CoV-2 viral genomes are usually sequenced from nasopharyngeal swabs of individual patients to track viral spread. Recently, RT-qPCR of municipal wastewater has been used to quantify the abundance of SARS-CoV-2 in several regions globally. However, metatranscriptomic sequencing of wastewater can be used to profile the viral genetic diversity across infected communities. Here, we sequenced RNA directly from sewage collected by municipal utility districts in the San Francisco Bay Area to generate complete and nearly complete SARS-CoV-2 genomes. The major consensus SARS-CoV-2 genotypes detected in the sewage were identical to clinical genomes from the region. Using a pipeline for single nucleotide variant calling in a metagenomic context, we characterized minor SARS-CoV-2 alleles in the wastewater and detected viral genotypes which were also found within clinical genomes throughout California. Observed wastewater variants were more similar to local California patient-derived genotypes than they were to those from other regions within the United States or globally. Additional variants detected in wastewater have only been identified in genomes from patients sampled outside California, indicating that wastewater sequencing can provide evidence for recent introductions of viral lineages before they are detected by local clinical sequencing. These results demonstrate that epidemiological surveillance through wastewater sequencing can aid in tracking exact viral strains in an epidemic context.

/pdf/genome-sequencing-of-sewage-detects-regionally-prevalent-59jr9k5lux.pdf

Genome Sequencing of Sewage Detects Regionally Prevalent SARS-CoV-2 Variants.

https://digital.csic.es/bitstream/10261/239339/1/preprints202104.0481.v1.pdf

Minimizing errors in RT-PCR detection and quantification of SARS-CoV-2 RNA for wastewater surveillance

Wastewater surveillance for SARS-CoV-2 provides an approach for assessing the infection burden across a sewer service area. For these data to be useful for public health, measurement variability and the relationship to case data need to be established. We determined SARS-CoV-2 RNA concentrations in the influent of 12 wastewater treatment plants from August 2020 to January 2021. Technical replicates for N1 gene concentrations showed a relative standard deviation of 24%, suggesting it is possible to track relatively small (similar to 30%) changes in SARS-CoV-2 concentrations over time. COVID-19 cases were correlated significantly (rho >= 0.70) to wastewater SARS-CoV-2 RNA concentrations across large and small service areas, with weaker relationships (rho >= 0.59) in two communities. SARS-CoV-2 concentrations normalized to per capita slightly improved correlations to COVID-19 incidence, but normalizing to a spiked recovery control (BCoV) or a fecal marker (PMMoV or HF183) reduced correlations for a number of plants. Daily sampling demonstrated that a minimum of two samples collected per week were needed to maintain accuracy in trend analysis. The differences in the strength of SARS-CoV-2 relationships to COVID-19 incidence and the effect of normalization on these data among communities demonstrate that rigorous validation should be performed at individual sites where wastewater surveillance programs are implemented.

Evaluation of Sampling, Analysis, and Normalization Methods for SARS-CoV-2 Concentrations in Wastewater to Assess COVID-19 Burdens in Wisconsin Communities

COVID-19 surveillance in Southeastern Virginia using wastewater-based epidemiology.

The ongoing COVID-19 pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) requires a significant, coordinated public health response. Assessing case density and spread of infection is critical and relies largely on clinical testing data. However, clinical testing suffers from known limitations, including test availability and a bias towards enumerating only symptomatic individuals. Wastewater-based epidemiology (WBE) has gained widespread support as a potential complement to clinical testing for assessing COVID-19 infections at the community scale. The efficacy of WBE hinges on the ability to accurately characterize SARS-CoV-2 concentrations in wastewater. To date, a variety of sampling schemes have been used without consensus around the appropriateness of grab or composite sampling. Here we address a key WBE knowledge gap by examining the variability of SARS-CoV-2 concentrations in wastewater grab samples collected every 2 hours for 72 hours compared with corresponding 24-hour flow-weighted composite samples. Results show relatively low variability (mean for all assays = 741 copies 100 mL-1, standard deviation = 508 copies 100 mL-1) for grab sample concentrations, and good agreement between most grab samples and their respective composite (mean deviation from composite = 159 copies 100 mL-1). When SARS-CoV-2 concentrations are used to calculate viral load, the discrepancy between grabs (log10 difference = 12.0) or a grab and its associated composite (log10 difference = 11.8) are amplified. A similar effect is seen when estimating carrier prevalence in a catchment population with median estimates based on grabs ranging 62-1853 carriers. Findings suggest that grab samples may be sufficient to characterize SARS-CoV-2 concentrations, but additional calculations using these data may be sensitive to grab sample variability and warrant the use of flow-weighted composite sampling. These data inform future WBE work by helping determine the most appropriate sampling scheme and facilitate sharing of datasets between studies via consistent methodology.

/pdf/wastewater-sars-cov-2-concentration-and-loading-variability-1xwuvk8pf0.pdf

Wastewater SARS-CoV-2 Concentration and Loading Variability from Grab and 24-Hour Composite Samples

Collection system investigation microbial source tracking (CSI-MST): Applying molecular markers to identify sewer infrastructure failures.

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COVID-19 surveillance in Southeastern Virginia using wastewater-based epidemiology.

Wastewater SARS-CoV-2 Concentration and Loading Variability from Grab and 24-Hour Composite Samples

Collection system investigation microbial source tracking (CSI-MST): Applying molecular markers to identify sewer infrastructure failures.