Genomic Epidemiology of Severe Acute Respiratory Syndrome Coronavirus 2 Transmission Among University Students in Western Pennsylvania.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) control on college campuses is challenging given communal living and student social dynamics. Understanding SARS-CoV-2 transmission among college students is important for the development of optimal control strategies. METHODS: SARS-CoV-2 nasal swab samples were collected from University of Pittsburgh students for symptomatic testing and asymptomatic surveillance from August 2020 through April 2021 from 3 campuses. Whole-genome sequencing (WGS) was performed on 308 samples, and contact tracing information collected from students was used to identify transmission clusters. RESULTS: We identified 31 Pangolin lineages of SARS-CoV-2, the majority belonging to B.1.1.7 (Alpha) and B.1.2 lineages. Contact tracing identified 142 students (46%) clustering with each other; WGS identified 53 putative transmission clusters involving 216 students (70%). WGS identified transmissions that were missed by contact tracing. However, 84 cases (27%) could not be linked by either WGS or contact tracing. Clusters were most frequently linked to students residing in the same dormitory, off-campus roommates, friends, or athletic activities. CONCLUSIONS: The majority of SARS-CoV-2-positive samples clustered by WGS, indicating significant transmission across campuses. The combination of WGS and contact tracing maximized the identification of SARS-CoV-2 transmission on campus. WGS can be used as a strategy to mitigate, and further prevent transmission among students.

SARS-CoV-2 control on a large urban college campus without mass testing.

OBJECTIVE: A small percentage of universities and colleges conducted mass SARS-CoV-2 testing. However, universal testing is resource-intensive, strains national testing capacity, and false negative tests can encourage unsafe behaviors. PARTICIPANTS: A large urban university campus. METHODS: Virus control centered on three pillars: mitigation, containment, and communication, with testing of symptomatic and a random subset of asymptomatic students. RESULTS: Random surveillance testing demonstrated a prevalence among asymptomatic students of 0.4% throughout the term. There were two surges in cases that were contained by enhanced mitigation and communication combined with targeted testing. Cumulative cases totaled 445 for the term, most resulting from unsafe undergraduate student behavior and among students living off-campus. A case rate of 232/10,000 undergraduates equaled or surpassed several peer institutions that conducted mass testing. CONCLUSIONS: An emphasis on behavioral mitigation and communication can control virus transmission on a large urban campus combined with a limited and targeted testing strategy.

Genomic characterization of SARS-CoV-2 from vaccine breakthrough cases in Allegheny County, Pennsylvania.

We performed whole genome sequencing on SARS-CoV-2 from 59 vaccinated individuals from southwest Pennsylvania who tested positive between February and September, 2021. A comparison of mutations among vaccine breakthrough cases to a time-matched control group identified potential adaptive responses of SARS-CoV-2 to vaccination.

Predictive model for severe COVID-19 using SARS-CoV-2 whole-genome sequencing and electronic health record data, March 2020-May 2021.

OBJECTIVE: We used SARS-CoV-2 whole-genome sequencing (WGS) and electronic health record (EHR) data to investigate the associations between viral genomes and clinical characteristics and severe outcomes among hospitalized COVID-19 patients. METHODS: We conducted a case-control study of severe COVID-19 infection among patients hospitalized at a large academic referral hospital between March 2020 and May 2021. SARS-CoV-2 WGS was performed, and demographic and clinical characteristics were obtained from the EHR. Severe COVID-19 (case patients) was defined as having one or more of the following: requirement for supplemental oxygen, mechanical ventilation, or death during hospital admission. Controls were hospitalized patients diagnosed with COVID-19 who did not meet the criteria for severe infection. We constructed predictive models incorporating clinical and demographic variables as well as WGS data including lineage, clade, and SARS-CoV-2 SNP/GWAS data for severe COVID-19 using multiple logistic regression. RESULTS: Of 1,802 hospitalized SARS-CoV-2-positive patients, we performed WGS on samples collected from 590 patients, of whom 396 were case patients and 194 were controls. Age (p = 0.001), BMI (p = 0.032), test positive time period (p = 0.001), Charlson comorbidity index (p = 0.001), history of chronic heart failure (p = 0.003), atrial fibrillation (p = 0.002), or diabetes (p = 0.007) were significantly associated with case-control status. SARS-CoV-2 WGS data did not appreciably change the results of the above risk factor analysis, though infection with clade 20A was associated with a higher risk of severe disease, after adjusting for confounder variables (p = 0.024, OR = 3.25; 95%CI: 1.31-8.06). CONCLUSIONS: Among people hospitalized with COVID-19, older age, higher BMI, earlier test positive period, history of chronic heart failure, atrial fibrillation, or diabetes, and infection with clade 20A SARS-CoV-2 strains can predict severe COVID-19.

SARS-CoV-2 N gene mutations impact detection by clinical molecular diagnostics: reports in two cities in the United States.

Nasal and nasopharyngeal swab specimens tested by the Cepheid Xpert Xpress SARS-CoV-2 were analyzed by whole-genome sequencing based on impaired detection of the N2 target. Each viral genome had at least one mutation in the N gene, which likely arose independently in the New York City and Pittsburgh study sites.