IMPORTANCE The reopening of colleges and universities in the US during the coronavirus disease 2019 (COVID-19) pandemic is a significant public health challenge. The development of accessible and practical approaches for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) detection in the college population is paramount for deploying recurrent surveillance testing as an essential strategy for virus detection, containment, and mitigation. OBJECTIVE To determine the prevalence of SARS-CoV-2 in asymptomatic participants in a university community by using CREST (Cas13-based, rugged, equitable, scalable testing), a CRISPRbased test developed for accessible and large-scale viral screening. DESIGN, SETTING, AND PARTICIPANTS For this cohort study, a total of 1808 asymptomatic participants were screened for SARS-CoV-2 using a CRISPR-based assay and a point-of-reference reverse transcriptase-quantitative polymerase chain reaction (RT-qPCR) test. Viral prevalence in self

Background: The progress of the COVID-19 pandemic profoundly impacts the health of communities around the world, with unique impacts on colleges and universities. Transmission of SARS-CoV-2 by asymptomatic people is thought to be the underlying cause of a large proportion of new infections. However, the local prevalence of asymptomatic and pre-symptomatic carriers of SARS-CoV-2 is influenced by local public health restrictions and the community setting. Objectives: This study has three main objectives. First, we looked to establish the prevalence of asymptomatic SARS-CoV-2 infection on a university campus in California. Second, we sought to assess the changes in viral prevalence associated with the shifting community conditions related to non-pharmaceutical interventions (NPIs). Third, we aimed to compare the performance of CRISPR- and PCR-based assays for large-scale virus surveillance sampling in COVID-19 asymptomatic persons. Methods: We enrolled 1,808 asymptomatic persons for self-collection of oropharyngeal (OP) samples to undergo SARS-CoV-2 testing. We compared viral prevalence in samples obtained in two time periods: May 28th-June 11th; June 23rd-July 2nd. We detected viral genomes in these samples using two assays: CREST, a CRISPR-based method recently developed at UCSB, and the RT-qPCR test recommended by US Centers for Disease Control and Prevention (CDC). Results: Of the 1,808 participants, 1,805 were affiliates of the University of California, Santa Barbara, and 1,306 were students. None of the tests performed on the 732 samples collected between late May to early June were positive. In contrast, tests performed on the 1076 samples collected between late June to early July, revealed nine positive cases. This change in prevalence met statistical significance, p = 0.013. One sample was positive by RT-qPCR at the threshold of detection, but negative by both CREST and CLIA-confirmation testing. With this single exception, there was perfect concordance in both positive and negative results obtained by RT-qPCR and CREST. The estimated prevalence of the virus, calculated using the confirmed cases, was 0.74%. The average age of our sample population was 28.33 (18-75) years, and the average age of the positive cases was 21.7 years (19-30). Conclusions: Our study revealed that there were no COVID-19 cases in our study population in May/June. Using the same methods, we demonstrated a substantial shift in prevalence approximately one month later, which coincided with changes in community restrictions and public interactions. This increase in prevalence, in a young and asymptomatic population which would not have otherwise accessed COVID-19 testing, indicated the leading wave of a local outbreak, and coincided with rising case counts in the surrounding county and the state of California. Our results substantiate that large, population-level asymptomatic screening using self-collection may be a feasible and instructive aspect of the public health approach within large campus communities, and the almost perfect concordance between CRISPR- and PCR-based assays indicate expanded options for surveillance testing

The emergence of the SARS-CoV-2 Omicron variant in 2021 is associated with a global surge of cases in late 2021 and early 2022. Identifying the introduction of novel SARS-CoV-2 variants to a population is imperative to inform decisions by clinicians and public health officials. Here, we describe a quantitative reverse transcription PCR-based assay (RT-qPCR) targeting unique mutations in the Omicron BA.1/BA1.1 and BA.2 viral genomes. This assay accurately and precisely detect the presence of these Omicron variants in patient samples in less than four hours. Using this assay, we tested 270 clinical samples and detected the introduction of Omicron BA.1/BA1.1 and BA.2 in the Santa Barbara County (SBC) population in December 2021 and February 2022, respectively. Identifying Omicron variants using this RT-qPCR assay showed complete concordance with whole viral genome sequencing; both assays indicated that Omicron was the dominant variant in SB County. Our data substantiate that RT-qPCR-based virus detection assays offer a fast and inexpensive alternative to NGS for virus variant-specific detection approach, which allows streamlining the detection of Omicron variants in patient samples.

The COVID-19 pandemic has taken a devastating human toll worldwide. The development of impactful guidelines and measures for controlling the COVID-19 pandemic requires continuous and widespread testing of suspected cases and their contacts through accurate, accessible, and reliable methods for SARS-CoV-2 detection. Here we describe a CRISPR-Cas13-based method for the detection of SARS-CoV-2. The assay is called CREST (Cas13-based, rugged, equitable, scalable testing), and is specific, sensitive, and highly accessible. As such, CREST may provide a low-cost and dependable alternative for SARS-CoV-2 surveillance.

The recent emergence of the SARS-CoV-2 Omicron variant is associated with a dramatic surge of cases around the globe in late 2021 and early 2022. The numerous mutations in this variant, particularly in the Spike protein, enhance its transmission, increase immune evasion, and limit treatment with monoclonal antibodies. Identifying a community's introduction to a novel SARS-CoV-2 variant with new clinical features related to treatment options and infection control needs is imperative to inform decisions by clinicians and public health officials, and traditional sequencing techniques often take weeks to result. Here, we describe a quantitative reverse transcription PCR assay (RT-qPCR) to accurately and precisely detect the presence of the Omicron sublineages BA.1/BA1.1 and BA.2 viral RNA from patient samples in less than four hours. The assay uses primers targeting the BA.1/BA1.1 unique mutations N211del, L212I, and L214 insertion EPE in the Spike protein gene, and the BA.2 specific mutations T19I and L24/P25/P26 deletion in the Spike protein gene. Using this assay, we detected 169 cases of Omicron, 164 BA.1/BA1.1 and 5 BA.2, from 270 residual SARS-CoV-2 positive samples collected for diagnostic purposes from Santa Barbara County (SBC) between December 2021 to February 2022. The RT-qPCR results show concordance with whole viral genome sequencing. Our observations indicate that Omicron was the dominant variant in SB County and is likely responsible for the surge of cases in the area during the sampling period. Using this inexpensive and accurate test, the rapid detection of Omicron in patient samples allowed clinicians to modify treatment strategies and public health officers to enhance contact tracing strategies. This RT-qPCR assay offers an alternative to current variant-specific detection approaches, provides a template for the fast design of similar assays, and allows the rapid, accurate, and inexpensive detection of Omicron variants in patient samples. It can also be readily adapted to new variants as they emerge in the future.