A cohort study measuring SARS-CoV-2 seroconversion and serial viral testing in university students.

BACKGROUND: To improve understanding of the antibody response to SARS-CoV-2 infection, we examined seroprevalence, incidence of infection, and seroconversion among a cohort of young adults living on university campuses during the fall of 2020. METHODS: At the beginning (semester start) and end (semester end) of an 11-week period, serum collected from 107 students was tested using the qualitative Abbott Architect SARS-CoV-2 IgG and AdviseDx SARS-CoV-2 IgG II assays. Results were matched to interim weekly surveillance viral testing and symptom data. RESULTS: With the SARS-CoV-2 IgG assay, 15 (14.0%) students were seropositive at semester start; 29 (27.1%) students were seropositive at semester end; 10 (9.3%) were seropositive at both times. With the AdviseDx SARS-CoV-2 IgG II assay, 17 (16.3%) students were seropositive at semester start, 37 (35.6%) were seropositive at semester end, and 16 (15.3%) were seropositive at both times. Overall, 23 students (21.5%) had positive viral tests during the semester. Infection was identified by serial testing in a large majority of individuals who seroconverted using both assays. Those seropositive at semester end more frequently reported symptomatic infections (56.5%) than asymptomatic infections (30.4%). CONCLUSION: Differences between antibody targets were observed, with more declines in antibody index values below the threshold of positivity with the anti-nucleocapsid assay compared to the anti-spike assay. Serology testing, combined with serial viral testing, can detect seroconversions, and help understand the potential correlates of protection provided by antibodies to SARS-CoV-2.

Efficacy of vaccination and previous infection against the Omicron BA.1 variant in Syrian hamsters.

The emergence of the SARS-CoV-2 Omicron (B.1.1.529) variant with a surprising number of spike mutations raises concerns about reduced sensitivity of this virus to antibody neutralization and subsequent vaccine breakthrough infections. Here, we infect Moderna mRNA-vaccinated or previously infected hamsters with the Omicron BA.1 variant. While the Moderna mRNA vaccine reduces viral loads in the respiratory tissues upon challenge with an early S-614G isolate, the vaccine efficacy is not as pronounced after infection with the Omicron variant. Previous infection with the early SARS-CoV-2 isolate prevents replication after rechallenge with either virus in the lungs of previously infected hamsters, but the Omicron variant replicates efficiently in nasal turbinate tissue. These results experimentally demonstrate in an animal model that the antigenic changes in the Omicron variant are responsible for vaccine breakthrough and re-infection.

SARS-CoV-2 Omicron virus causes attenuated disease in mice and hamsters.

The recent emergence of B.1.1.529, the Omicron variant1,2, has raised concerns of escape from protection by vaccines and therapeutic antibodies. A key test for potential countermeasures against B.1.1.529 is their activity in preclinical rodent models of respiratory tract disease. Here, using the collaborative network of the SARS-CoV-2 Assessment of Viral Evolution (SAVE) programme of the National Institute of Allergy and Infectious Diseases (NIAID), we evaluated the ability of several B.1.1.529 isolates to cause infection and disease in immunocompetent and human ACE2 (hACE2)-expressing mice and hamsters. Despite modelling data indicating that B.1.1.529 spike can bind more avidly to mouse ACE2 (refs. 3,4), we observed less infection by B.1.1.529 in 129, C57BL/6, BALB/c and K18-hACE2 transgenic mice than by previous SARS-CoV-2 variants, with limited weight loss and lower viral burden in the upper and lower respiratory tracts. In wild-type and hACE2 transgenic hamsters, lung infection, clinical disease and pathology with B.1.1.529 were also milder than with historical isolates or other SARS-CoV-2 variants of concern. Overall, experiments from the SAVE/NIAID network with several B.1.1.529 isolates demonstrate attenuated lung disease in rodents, which parallels preliminary human clinical data.

Interventions to Disrupt Coronavirus Disease Transmission at a University, Wisconsin, USA, August-October 2020.

University settings have demonstrated potential for coronavirus disease (COVID-19) outbreaks; they combine congregate living, substantial social activity, and a young population predisposed to mild illness. Using genomic and epidemiologic data, we describe a COVID-19 outbreak at the University of Wisconsin-Madison, Madison, Wisconsin, USA. During August-October 2020, a total of 3,485 students, including 856/6,162 students living in dormitories, tested positive. Case counts began rising during move-in week, August 25-31, 2020, then rose rapidly during September 1-11, 2020. The university initiated multiple prevention efforts, including quarantining 2 dormitories; a subsequent decline in cases was observed. Genomic surveillance of cases from Dane County, in which the university is located, did not find evidence of transmission from a large cluster of cases in the 2 quarantined dorms during the outbreak. Coordinated implementation of prevention measures can reduce COVID-19 spread in university settings and may limit spillover to the surrounding community.

Assessing the dilution effect of specimen pooling on the sensitivity of SARS-CoV-2 PCR tests.

The SARS-CoV-2 pandemic has led to an unprecedented demand for diagnostic tests. Many studies have modeled the efficiency gains of specimen pooling, but few have systematically evaluated the dilution effect of pooling on the sensitivity of tests. Using the frequency distribution of cycle threshold (Ct ) values of our first 838 SARS-CoV-2 positive specimens, we modeled 100 specimens on the same frequency distribution. Given this distribution, we then tested dilutions of 1:5, 1:10, and 1:50 to find the percentage of specimens positive at each Ct value with each pool size. Using the frequency distribution and the percentage of specimens positive at each Ct value, we estimate that pools of 5 lead to 93% sensitivity, pools of 10 lead to 91% sensitivity, and pools of 50 lead to 81% sensitivity. Pools of 5 and 10 lead to some specimens with Ct values of ≥32 becoming negative, while pools of 50 lead to some specimens with Ct values of ≥28 becoming negative. These sensitivity estimates can inform laboratories seeking to implement pooling approaches as they seek to balance test efficiency with sensitivity.