Abstract

Background

The SARS-CoV-2 pandemic remains a major threat worldwide. Healthcare workers (HCWs) are particularly impacted by the COVID-19 pandemic with high infection rates reported from HCWs in hard-hit regions2,3, raising concerns about nosocomial infections and the effectiveness of personal protective equipment in protecting HCWs. Asymptomatic infection is estimated 17.9% to 33.3%4 and is a common source of transmission5. We designed a HCW testing program to address patient and employee concerns about exposures in the healthcare setting at our 808-bed health system. During the time of employee testing, the mean (range) number of inpatients with a diagnosis of COVID was 30 (22–38) of a mean (range) daily census of 560 (492–602) (approximately 5.4%).

Methods

This opt-in program offered SARS-CoV-2 testing of asymptomatic HCWs with paired nasopharyngeal or mid-turbinate swab for PCR (Roche) and serum IgG antibody testing (Diazyme). While initially designed as a pilot project in the Emergency Departments and COVID-19 units, it was quickly expanded to a health system-wide initiative.

Results

From April 22 to June 2, PCR testing was performed on 5826 asymptomatic HCWs with four PCR tests resulting positive (0.09%). Of 5589 serologic tests (anti-SARS-CoV-2 IgG) performed, 57 tested positive (1.02 %). All HCW with a positive IgG had a concurrent negative PCR.

Conclusion

In this cross-sectional evaluation, the point prevalence of SARS-CoV-2 IgG in asymptomatic HCWs at UC San Diego was less than 1%, supporting modeling estimations at the San Diego County level of very low levels of community exposure at the time of this testing. Further analyses of incidence rates and potential risk factors such as employee roles within the healthcare system, community and healthcare exposures, and home zip code are underway. Asymptomatic HCW testing is a strategy that can provide the perception of additional safety to both the workforce and patients as the health system reopens, while potentially reduce transmission from asymptomatic persons through active case finding and isolation.

Disclosures

Randy Taplitz, MD, Merck (Advisor or Review Panel member)

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing and/or sequencing capacity, which can also introduce biases^1-3. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing^4,5. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We developed and deployed improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detected emerging variants of concern up to 14 days earlier in wastewater samples, and identified multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.

Summary

As SARS-CoV-2 continues to spread and evolve, detecting emerging variants early is critical for public health interventions. Inferring lineage prevalence by clinical testing is infeasible at scale, especially in areas with limited resources, participation, or testing/sequencing capacity, which can also introduce biases. SARS-CoV-2 RNA concentration in wastewater successfully tracks regional infection dynamics and provides less biased abundance estimates than clinical testing. Tracking virus genomic sequences in wastewater would improve community prevalence estimates and detect emerging variants. However, two factors limit wastewater-based genomic surveillance: low-quality sequence data and inability to estimate relative lineage abundance in mixed samples. Here, we resolve these critical issues to perform a high-resolution, 295-day wastewater and clinical sequencing effort, in the controlled environment of a large university campus and the broader context of the surrounding county. We develop and deploy improved virus concentration protocols and deconvolution software that fully resolve multiple virus strains from wastewater. We detect emerging variants of concern up to 14 days earlier in wastewater samples, and identify multiple instances of virus spread not captured by clinical genomic surveillance. Our study provides a scalable solution for wastewater genomic surveillance that allows early detection of SARS-CoV-2 variants and identification of cryptic transmission.