Detection of SARS-CoV-2 variant Mu, Beta, Gamma, Lambda, Delta, Alpha, and Omicron in wastewater settled solids using mutation-specific assays is associated with regional detection of variants in clinical samples

Changes in the circulation of SARS-CoV-2 variants of concern (VOCs) may require changes in public health response to the COVID-19 pandemic, as they have the potential to evade vaccines and pharmaceutical interventions and may be more transmissive relative to other SARS-CoV-2 variants. As such, it is essential to track and prevent their spread in susceptible communities.We developed digital RT-PCR assays for mutations characteristic of VOCs and used them to quantify those mutations in wastewater settled solids samples collected from a publicly owned treatment works (POTW) during different phases of the COVID-19 pandemic. Wastewater concentrations of single mutations characteristic to each VOC, normalized by the concentration of a conserved SARS-CoV-2 N gene, correlate to regional estimates of the proportion of clinical infections caused by each VOC. These results suggest targeted RT-PCR assays can be used to detect variants circulating in communities and inform public health response to the pandemic. ImportanceWastewater represents a pooled biological sample of the contributing community and thus a resource of assessing community health. Here we show that emergence, spread, and disappearance of SARS-CoV-2 infections caused by variants of concern are reflected in the presence of variant genomic RNA in wastewater settled solids. This work highlights an important public health use case for wastewater.

High frequency, high throughput quantification of SARS-CoV-2 RNA in wastewater settled solids at eight publicly owned treatment works in Northern California shows strong association with COVID-19 incidence

A number of recent retrospective studies have demonstrated that SARS-CoV-2 RNA concentrations in wastewater are associated with COVID-19 cases in the corresponding sewersheds. Implementing high-resolution, prospective efforts across multiple plants depends on sensitive measurements that are representative of COVID-19 cases, scalable for high throughput analysis, and comparable across laboratories. We conducted a prospective study across eight publicly owned treatment works (POTWs). A focus on SARS-CoV-2 RNA in solids enabled us to scale-up our measurements with a commercial lab partner. Samples were collected daily and results were posted to a website within 24-hours. SARS-CoV-2 RNA in daily samples correlated to incidence COVID-19 cases in the sewersheds; a 1 log10 increase in SARS-CoV-2 RNA in settled solids corresponds to a 0.58 log10 (4X) increase in sewershed incidence rate. SARS-CoV-2 RNA signals measured with the commercial laboratory partner were comparable across plants and to measurements conducted in a university laboratory when normalized by pepper mild mottle virus PMMoV RNA. Results suggest that SARS-CoV-2 RNA should be detectable in settled solids for COVID-19 incidence rates > 1/100,000 (range 0.8 - 2.3 cases per 100,000). These sensitive, representative, scalable, and comparable methods will be valuable for future efforts to scale-up wastewater-based epidemiology. ImportanceAccess to reliable, rapid monitoring data is critical to guide response to an infectious disease outbreak. For pathogens that are shed in feces or urine, monitoring wastewater can provide a cost-effective snapshot of transmission in an entire community via a single sample. In order for a method to be useful for ongoing COVID-19 monitoring, it should be sensitive for detection of low concentrations of SARS-CoV-2, representative of incidence rates in the community, scalable to generate data quickly, and comparable across laboratories. This paper presents a method utilizing wastewater solids to meet these goals, producing measurements of SARS-CoV-2 RNA strongly associated with COVID-19 cases in the sewershed of a publicly owned treatment work. Results, provided within 24 hrs, can be used to detect incidence rates as low as approximately 1/100,000 cases and can be normalized for comparison across locations generating data using different methods.

Effect of storage conditions on SARS-CoV-2 RNA quantification in wastewater solids

SARS-CoV-2 RNA in wastewater settled solids is associated with COVID-19 incidence in sewersheds and therefore, there is a strong interest in using these measurements to augment traditional disease surveillance methods. A wastewater surveillance program should provide rapid turn around for sample measurements (ideally within 24 hours), but storage of samples is necessary for a variety of reasons including biobanking. Here we investigate how storage of wastewater solids at 4{degrees}C, -20{degrees}C, and -80{degrees}C affects measured concentrations of SARS-CoV-2 RNA. We find that short term (7-8 d) storage of raw solids at 4{degrees}C has little effect on measured concentrations of SARS-CoV-2 RNA, whereas longer term storage at 4{degrees}C (35-122 d) or freezing reduces measurements by 60%, on average. We show that normalizing SARS-CoV-2 RNA concentrations by concentrations of pepper mild mottle virus (PMMoV) RNA, an endogenous wastewater virus, can correct for changes during storage as storage can have a similar effect on PMMoV RNA as on SARS-CoV-2 RNA. The reductions in SARS-CoV-2 RNA in solids during freeze thaws is less than those reported for the same target in liquid influent by several authors.

Wastewater-based estimation of the effective reproductive number of SARS-CoV-2

BackgroundThe effective reproductive number, Re, is a critical indicator to monitor disease dynamics, inform regional and national policies, and estimate the effectiveness of interventions. It describes the average number of new infections caused by a single infectious person through time. To date, Re estimates are based on clinical data such as observed cases, hospitalizations, and/or deaths. These estimates are temporarily biased when clinical testing or reporting strategies change. ObjectivesWe show that the dynamics of SARS-CoV-2 RNA in wastewater can be used to estimate Re in near real-time, independent of clinical data and without the associated biases. MethodsWe collected longitudinal measurements of SARS-CoV-2 RNA in wastewater in Zurich, CH, and San Jose (CA), USA. We combined this data with information on the temporal dynamics of shedding (the shedding load distribution) to estimate a time series proportional to the daily COVID-19 infection incidence. We estimated a wastewater-based Re from this incidence. ResultsThe method to estimate Re from wastewater works robustly on data from two different countries and two wastewater matrices. The resulting estimates are as similar to the Re estimates from case report data as Re estimates based on observed cases, hospitalizations, and deaths are among each other. We further provide details on the effect of sampling frequency and the shedding load distribution on the ability to infer Re. DiscussionTo our knowledge, this is the first time Re has been estimated from wastewater. This method provides a low cost, rapid, and independent way to inform SARS-CoV-2 monitoring during the ongoing pandemic and is applicable to future wastewater-based epidemiology targeting other pathogens.