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Evolution of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) seroprevalence among employees of a US academic children’s hospital during coronavirus disease 2019 (COVID-19) pandemic

Published online by Cambridge University Press:  02 December 2021

Brian T. Fisher*
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Anna Sharova
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Craig L. K. Boge
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Sigrid Gouma
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Audrey Kamrin
Affiliation:
Center for Human Phenomic Science, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Jesse Blumenstock
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Sydney Shuster
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Lauren Gianchetti
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Danielle Collins
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Elikplim Akaho
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania
Madison E. Weirick
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Christopher M. McAllister
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Marcus J. Bolton
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Claudia P. Arevalo
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Eileen C. Goodwin
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Elizabeth M. Anderson
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Shannon R. Christensen
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Fran Balamuth
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Audrey R. Odom John
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Yun Li
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Susan Coffin
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Jeffrey S. Gerber
Affiliation:
Division of Infectious Diseases, Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
Scott E. Hensley
Affiliation:
Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
*
Author for correspondence: Brian T. Fisher, E-mail: fisherbria@chop.edu
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Abstract

Objective:

To describe the cumulative seroprevalence of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) antibodies during the coronavirus disease 2019 (COVID-19) pandemic among employees of a large pediatric healthcare system.

Design, setting, and participants:

Prospective observational cohort study open to adult employees at the Children’s Hospital of Philadelphia, conducted April 20–December 17, 2020.

Methods:

Employees were recruited starting with high-risk exposure groups, utilizing e-mails, flyers, and announcements at virtual town hall meetings. At baseline, 1 month, 2 months, and 6 months, participants reported occupational and community exposures and gave a blood sample for SARS-CoV-2 antibody measurement by enzyme-linked immunosorbent assays (ELISAs). A post hoc Cox proportional hazards regression model was performed to identify factors associated with increased risk for seropositivity.

Results:

In total, 1,740 employees were enrolled. At 6 months, the cumulative seroprevalence was 5.3%, which was below estimated community point seroprevalence. Seroprevalence was 5.8% among employees who provided direct care and was 3.4% among employees who did not perform direct patient care. Most participants who were seropositive at baseline remained positive at follow-up assessments. In a post hoc analysis, direct patient care (hazard ratio [HR], 1.95; 95% confidence interval [CI], 1.03–3.68), Black race (HR, 2.70; 95% CI, 1.24–5.87), and exposure to a confirmed case in a nonhealthcare setting (HR, 4.32; 95% CI, 2.71–6.88) were associated with statistically significant increased risk for seropositivity.

Conclusions:

Employee SARS-CoV-2 seroprevalence rates remained below the point-prevalence rates of the surrounding community. Provision of direct patient care, Black race, and exposure to a confirmed case in a nonhealthcare setting conferred increased risk. These data can inform occupational protection measures to maximize protection of employees within the workplace during future COVID-19 waves or other epidemics.

Information

Type
Original Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of The Society for Healthcare Epidemiology of America
Figure 0

Fig. 1. The proportion of eligible participants contributing a blood sample at each study visit. Note. Visit 1: baseline study visit. Visit 2: 1-month study visit with an intended scheduling window of ±14 days and an actual sample collection window of ±15 days. Visit 3: 2-month study visit with an intended scheduling window of ±14 days and an actual sample collection window of −15/+31 days. Visit 4: 6-month study visit with an intended scheduling window of ±30 days and an actual sample collection window of −30/+46 days.

Figure 1

Table 1. SARS-CoV-2 Seroprevalence Rates by Participant Demographic Characteristics and SARS-CoV-2 Infection History

Figure 2

Table 2. SARS-CoV-2 Seroprevalence by Participant Community Exposures

Figure 3

Table 3. SARS-CoV-2 Seroprevalence by Participant Healthcare Occupational Exposures

Figure 4

Table 4. Post Hoc Multivariable Cox Proportional Hazards for Seroprevalence by Patient Factors that May Affect the Risk of SARS-CoV-2 Seroconversiona

Figure 5

Fig. 2. (A) The 1-month, 2-month, and 6-month SARS-CoV-2 IgG levels among participants with a self-reported history of SARS-CoV-2 PCR positivity and with IgG positivity at baseline. (B) The 1-month, 2-month, and 6-month SARS-CoV-2 IgG levels among participants with no self-reported history of SARS-CoV-2 PCR positivity but with IgG positivity at baseline. The dotted line at 0.48 units indicates threshold for positivity of the enzyme-linked immunosorbent assay detecting IgG to the receptor binding domain of the SARS-CoV-2 spike protein. The bold black line indicates linear smoothed conditional means of log2 IgG levels over time for all participants with positive IgG at baseline and for whom subsequent specimen results were available. Grey shadowing represents the 95% confidence intervals around this trajectory. Note. SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; PCR: polymerase chain reaction.

Figure 6

Fig. 3. Cumulative proportion of employees with positive SARS-CoV-2 serology and weekly PCR positivity rates in Philadelphia during the study period. Solid triangles represent weekly PCR positivity rates in Philadelphia. Solid circles represent the weekly cumulative proportion of study participants who were seropositive for SARS-CoV-2.