Predicting daily COVID-19 case rates from SARS-CoV-2 RNA concentrations across a diversity of wastewater catchments.

We assessed the relationship between municipality COVID-19 case rates and SARS-CoV-2 concentrations in the primary sludge of corresponding wastewater treatment facilities. Over 1700 daily primary sludge samples were collected from six wastewater treatment facilities with catchments serving 18 cities and towns in the State of Connecticut, USA. Samples were analyzed for SARS-CoV-2 RNA concentrations during a 10 month time period that overlapped with October 2020 and winter/spring 2021 COVID-19 outbreaks in each municipality. We fit lagged regression models to estimate reported case rates in the six municipalities from SARS-CoV-2 RNA concentrations collected daily from corresponding wastewater treatment facilities. Results demonstrate the ability of SARS-CoV-2 RNA concentrations in primary sludge to estimate COVID-19 reported case rates across treatment facilities and wastewater catchments, with coverage probabilities ranging from 0.94 to 0.96. Lags of 0 to 1 days resulted in the greatest predictive power for the model. Leave-one-out cross validation suggests that the model can be broadly applied to wastewater catchments that range in more than one order of magnitude in population served. The close relationship between case rates and SARS-CoV-2 concentrations demonstrates the utility of using primary sludge samples for monitoring COVID-19 outbreak dynamics. Estimating case rates from wastewater data can be useful in locations with limited testing availability, testing disparities, or delays in individual COVID-19 testing programs.

SalivaDirect: A simplified and flexible platform to enhance SARS-CoV-2 testing capacity.

BACKGROUND: Scaling SARS-CoV-2 testing to meet demands of safe reopenings continues to be plagued by assay costs and supply chain shortages. In response, we developed SalivaDirect, which received Emergency Use Authorization (EUA) from the U.S. Food and Drug Administration (FDA). METHODS: We simplified our saliva-based diagnostic test by (1) not requiring collection tubes with preservatives, (2) replacing nucleic acid extraction with a simple enzymatic and heating step, and (3) testing specimens with a dualplex qRT-PCR assay. Moreover, we validated SalivaDirect with reagents and instruments from multiple vendors to minimize supply chain issues. FINDINGS: From our hospital cohort, we show a high positive agreement (94%) between saliva tested with SalivaDirect and nasopharyngeal swabs tested with a commercial qRT-PCR kit. In partnership with the National Basketball Association (NBA) and National Basketball Players Association (NBPA), we tested 3,779 saliva specimens from healthy individuals and detected low rates of invalid (0.3%) and false-positive (<0.05%) results. CONCLUSIONS: We demonstrate that saliva is a valid alternative to swabs for SARS-CoV-2 screening and that SalivaDirect can make large-scale testing more accessible and affordable. Uniquely, we can designate other laboratories to use our sensitive, flexible, and simplified platform under our EUA (https://publichealth.yale.edu/salivadirect/). FUNDING: This study was funded by the NBA and NBPA (N.D.G.), the Huffman Family Donor Advised Fund (N.D.G.), a Fast Grant from Emergent Ventures at the Mercatus Center at George Mason University (N.D.G.), the Yale Institute for Global Health (N.D.G.), and the Beatrice Kleinberg Neuwirth Fund (A.I.K.). C.B.F.V. is supported by NWO Rubicon 019.181EN.004.

Increased SARS-CoV-2 Testing Capacity with Pooled Saliva Samples.

We analyzed feasibility of pooling saliva samples for severe acute respiratory syndrome coronavirus 2 testing and found that sensitivity decreased according to pool size: 5 samples/pool, 7.4% reduction; 10 samples/pool, 11.1%; and 20 samples/pool, 14.8%. When virus prevalence is >2.6%, pools of 5 require fewer tests; when <0.6%, pools of 20 support screening strategies.

Measurement of SARS-CoV-2 RNA in wastewater tracks community infection dynamics.

We measured severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA concentrations in primary sewage sludge in the New Haven, Connecticut, USA, metropolitan area during the Coronavirus Disease 2019 (COVID-19) outbreak in Spring 2020. SARS-CoV-2 RNA was detected throughout the more than 10-week study and, when adjusted for time lags, tracked the rise and fall of cases seen in SARS-CoV-2 clinical test results and local COVID-19 hospital admissions. Relative to these indicators, SARS-CoV-2 RNA concentrations in sludge were 0-2 d ahead of SARS-CoV-2 positive test results by date of specimen collection, 0-2 d ahead of the percentage of positive tests by date of specimen collection, 1-4 d ahead of local hospital admissions and 6-8 d ahead of SARS-CoV-2 positive test results by reporting date. Our data show the utility of viral RNA monitoring in municipal wastewater for SARS-CoV-2 infection surveillance at a population-wide level. In communities facing a delay between specimen collection and the reporting of test results, immediate wastewater results can provide considerable advance notice of infection dynamics.

Detection of SARS-CoV-2 RNA by multiplex RT-qPCR.

The current quantitative reverse transcription PCR (RT-qPCR) assay recommended for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing in the United States requires analysis of 3 genomic targets per sample: 2 viral and 1 host. To simplify testing and reduce the volume of required reagents, we devised a multiplex RT-qPCR assay to detect SARS-CoV-2 in a single reaction. We used existing N1, N2, and RP primer and probe sets by the Centers for Disease Control and Prevention, but substituted fluorophores to allow multiplexing of the assay. The cycle threshold (Ct) values of our multiplex RT-qPCR were comparable to those obtained by the single assay adapted for research purposes. Low copy numbers (≥500 copies/reaction) of SARS-CoV-2 RNA were consistently detected by the multiplex RT-qPCR. Our novel multiplex RT-qPCR improves upon current single diagnostics by saving reagents, costs, time, and labor.