Skip to main content
NCBI home page
Lippincott Open Access logoLink to Lippincott Open Access
. 2025 Oct 21;68(3):e245–e251. doi: 10.1097/JOM.0000000000003586

Differential Odds of COVID-19 Infection Associated With Household and Workplace Exposures in US Health Care Personnel

Eric Kontowicz 1, Amanda K Irish 1, Ian D Plumb 1, Melissa Briggs-Hagen 1, Karisa K Harland 1, Anusha Krishnadasan 1, David A Talan 1, Patrick Ten Eyck 1, Mark T Steele 1, Efrat R Kean 1, Nicholas M Mohr 1, Project PREVENT Network
PMCID: PMC12928784  PMID: 41118238

Health care personnel (HCP) had higher a likelihood of acquiring COVID-19 infection from household exposures but not following workplace exposures. Recent vaccination and prior infection provided protection against COVID-19. These findings support the effectiveness of workplace infection prevention measures and vaccination to reduce COVID-19 transmission in the health care workforce.

Keywords: COVID-19, SARS-CoV-2, health personnel

Abstract

Objective

The aim of the study was to evaluate associations between occupational and nonoccupational COVID-19 exposures, household characteristics, and COVID-19 infection risk among health care personnel (HCP).

Methods

This is a nested analysis of HCP enrolled in a multisite vaccine effectiveness study. COVID-19 infection was confirmed through source documentation. Exposures and household characteristics were self-reported.

Results

HCP with household COVID-19 exposure had significantly higher infection odds, while workplace exposure was associated with decreased odds of infection. No associations were observed for community exposures, living with children, or living with unvaccinated household members.

Conclusions

Household exposure posed greater COVID-19 risk to HCP unlike exposures in the workplace. Combined with demonstrated vaccine effectiveness, these findings suggest that workplace infection control measures were successful, while interventions targeting household transmission may be critical for protecting HCP.

graphic file with name joem-68-e245-g001.jpg

Open in a new tab

LEARNING OUTCOMES

  • After completing this enduring educational activity, the learner will be better able to:

  • Discuss workplace and nonworkplace exposure to individuals with COVID-19 as it relates to COVID-19 infection in health care personnel

  • Describe household characteristics that are associated with increased or decreased odds of COVID-19

  • Recognize the role of past infection or recent vaccination in reducing the odds of COVID-19 among health care personnel

SARS-CoV-2 infections among health care personnel (HCP) have contributed to unprecedented absenteeism in the health workforce, resulting in significant health system strain.1,2 SARS-CoV-2 infections in HCP may lead to transmission in the workplace or household perpetuating spread to others in the community.3–5

In the prevaccine era, HCP were thought to be at greater risk of SARS-CoV-2 infection than the general population due to frequent and prolonged occupational exposures.6–8 Although working with COVID-19 patients has been associated with an increased risk of SARS-CoV-2 infection,9 several studies identified exposure to infected household members as the greatest risk factor impacting SARS-CoV-2 infection among HCP.10–13 Vaccination against SARS-CoV-2 in HCP has been shown to be effective, not only by protecting HCP against infection, but also by conferring an estimated 30%–60% indirect protection of unvaccinated household members.14–16 Vaccines are effective at reducing the likelihood of viral transmission in those vaccinated compared to those who are not.17,18 However, the importance of unvaccinated household members is less clear.

The purpose of this study was to evaluate the associations between both occupational and nonoccupational exposure to individuals with COVID-19 and the risk of symptomatic SARS-CoV-2 infection among HCP enrolled in a multicenter vaccine effectiveness study. Additionally, we examined whether household size, living with children, and living with unvaccinated household members were associated with increased odds of HCP COVID-19. We hypothesized that larger household sizes and the presence of unvaccinated household members would be associated with higher odds of COVID-19 among HCP.

METHODS

We used data from HCP enrolled in Preventing Emerging Infections through Vaccine Effectiveness Testing Project (PREVENT) II. PREVENT methods have been previously reported.19 For this analysis, we included HCP tested for SARS-CoV-2 between August 13, 2022, and February 27, 2024. The case-to-control ratio for PREVENT II recruitment was maintained between 1:1 to 1:6 based on the number of cases and controls tested each week. HCP were enrolled using self-report by electronic survey instruments after obtaining informed consent. All vaccine doses and SARS-CoV-2 tests reported at enrollment were verified via source document verification.

This report was prepared in accordance with Strengthening the Reporting of Observational Studies in Epidemiology (Supplemental Digital Content, http://links.lww.com/JOM/C155).20 This activity was reviewed by the CDC and local institutional review boards (IRB), deemed nonresearch, and conducted in compliance with applicable federal law and CDC policy.21 Written consent was obtained for all participants.

All included HCP were tested for SARS-CoV-2 and stratified as test positive or negative. Reverse transcription polymerase chain reaction (RT-PCR) or other nucleic acid amplification test were required for controls, whereas RT-PCR, nucleic acid amplification test, or antigen tests were permitted for enrollment of test positive cases. HCP testing positive for SARS-CoV-2 were required to have at least one COVID-19 symptom in a period of 14 days before or after the qualifying test.22,23 A list of COVID-19 symptoms provided in Supplementary Digital Content (SDC) Table 1 (http://links.lww.com/JOM/C156). Each participant completed electronic screening and consent surveys within 60 days of their SARS-CoV-2 testing date. Eligible participants had an additional 14 days after completing their screening survey to complete a baseline survey that assessed total household occupancy (including themselves), with whom they lived (i.e., children, spouse or significant other, etc.), if they lived with a nonvaccinated individual, if they had close contact with test-confirmed or suspected individuals with SARS-CoV-2 infection at work, in their household, or community within 14 days prior to the onset of their symptoms (for symptomatic cases or controls) or prior to their testing date (for asymptomatic controls), self-reported positive SARS-CoV-2 nasal swab or saliva test prior to their PREVENT II testing, and if so the date of that positive test (SDC Table 2, http://links.lww.com/JOM/C156). HCP were included if they completed the screening survey within 60 days of their enrollment SARS-CoV-2 testing date for the PREVENT II study, completed the baseline survey within 14 days after completing the screening survey, and their SARS-CoV-2 and vaccination records could be verified. HCP were excluded if they were vaccinated within 14 days prior to SARS-CoV-2 testing, reported a prior infection date that was after their validated PREVENT II testing date, or did not disclose any demographic information on the baseline enrollment form.

Primary Outcome and Exposures

The primary outcome was symptomatic SARS-CoV-2 (hereafter termed COVID-19) infection based on diagnostic testing results at the time of enrollment and HCP-reported symptoms. The main exposures of interest included: HCP exposure to an individual with known or suspected COVD-19 in the workplace, at home, or in the community, household size, living with at least one unvaccinated household member, and living with at least one child. We collected the following information from HCP self-report: household size, living a child, living with an unvaccinated household member, close contact with an individual with known or suspected COVID-19 within or outside of a healthcare facility, household, or community, and HCP history of prior SARS-CoV-2 infection.

Definitions

We defined household size as lives “alone,” “with one person,” with two or three people,” or “with four or more people” based on HCP-report of the total household occupancy. HCP were defined as recently vaccinated if they received a vaccine dose more than 14 days before and within 6 months of their enrollment SARS-CoV-2 test.24 We defined prior SARS-CoV-2 infection as an HCP-reported positive nasal swab or saliva test within 12 months prior to their PREVENT II enrollment test.25,26 Exposure to an individual with COVID-19 was defined as HCP-reported exposure to an individual known or suspected to have COVID-19 in the workplace, household, or community 14 days prior to the start of HCP symptoms (for symptomatic cases or controls) or testing (for asymptomatic control). HCP reporting living with a child or with an unvaccinated household member were defined accordingly. Age categories were grouped as years: 18–49, 50–64, and 65+ based on calculated age. Number of underlying health conditions was dichotomized into fewer than two or two or more. Race and ethnicity, sex, education level, and rob role were obtained through self-report. For individuals with missing data for race and ethnicity, sex, or education level, responses were categorized as “Missing” and included in analysis.

Statistical Methods

Summary statistics are presented for continuous variables as medians with interquartile ranges. Mixed-effects logistic regression models treating SARS-CoV-2 testing site and month as random effects were performed for each covariate and outcome. We used multivariable, mixed-effects logistic regression to fit four models and estimate the odds of HCP COVID-19 in association with: 1. Self-reported exposure to an individual with confirmed symptomatic COVID-19 in the workplace, home or community; 2. Living with children; 3. Living with at least one unvaccinated household member; and 4. Living with children or living with at least one unvaccinated household member. All multivariable, mixed-effect models used testing site and month as random effects and the following covariates selected a priori based on previous literature as fixed effects: age category, sex, race/ethnicity, job role, education level, presence of two or more comorbidities, HCP vaccination status, and prior infection.19,27 Models 2–4 also included household size as a fixed effect.

This study spanned a long period with evolving dominant viral variants and changing vaccine effectiveness, thus we conducted a stratified analysis based on whether HCP were tested during the Omicron-dominant period or the post-Omicron period. The Omicron period was defined as August 2022 through March 31, 2023, and the post-Omicron period as April 1, 2023 onward.28 For this stratified analysis, we applied the same mixed-effects multivariable modeling strategy described above, but included only testing location as a random effect, as models did not converge when clustering by both month and site of testing.

An exploratory analysis was performed to assess the association between reported prior SARS-CoV-2 infection (instead of enrollment with COVID-19) and living with an unvaccinated household member or children. These analyses implemented similar mixed-effect logistic regression methods as described above. We conducted this exploratory analysis to support interpretation of our main findings, as prior infections may have influenced healthcare personnel immunity or transmission dynamics within their households. All statistical testing utilized two-sided tests with α < 0.05. We assessed data for collinearity using the variance inflation factor (VIF), with variables having a VIF <5 considered noncollinear.29 HCP with missing demographic variables were retained in the analysis by incorporating a “Missing” category within the respective categorical variables. Variable interaction was assessed by fitting models with and without interaction terms and evaluating model fit using the Akaike information criterion (AIC). Interactions were deemed nonsignificant if the AIC was higher for models that including the interaction term compared to those without it.30 All statistical analysis was performed in R version 4.3.1 (R Core Team, R Foundation for Statistical Computing, Vienna, Austria).

RESULTS

Participant Characteristics

A total of 4417 participants (12.5% of 35,355 invited HCP in PREVENT II) completed the screening and baseline surveys required for inclusion. Individuals were excluded if they were vaccinated within 2 weeks of SARS-CoV-2 testing (88, 2.0%), they reported a previous SARS-CoV-2 infection date after their enrollment testing date (77, 1.7%) or did not provide any demographic information (7, 0.2%) (SDC Figure 1, http://links.lww.com/JOM/C156). We included 4245 HCP for this analysis. The median time between SARS-CoV-2 enrollment testing and baseline survey completion was 22 days (interquartile range [IQR] 18–31 days). COVID-19 was confirmed in 2025 (47.7%) participants. Overall, 1103 (26.0%) HCP reported a prior SARS-CoV-2 infection within 12 months prior to their PREVENT II enrollment test. The median time between a participant’s self-reported prior SARS-CoV-2 infection and PREVENT II enrollment test was 241 days (IQR 161–308 days). Most included HCP were between the ages 18 and 49 (3213, 75.7%), White non-Hispanic (2853, 67.2%), female (3464, 81.6%), nurse or nurse assistant (1426, 33.6%), and did not receive a vaccine dose 6 months before their screening test (3064, 72.3%). However, nearly all the included HCP (4181, 98.5%) had received at least one vaccine dose. Complete participant characteristics are presented in SDC Table 3 (http://links.lww.com/JOM/C156).

Household Characteristics

The median number of total household members was two (IQR = 2–4). A total of 624 (14.7%) HCP indicated they lived alone, 1499 (35.3%) with one other household member, 1601 (37.7%) with two or three other household members, and 521 (12.3%) with four or more household members (Fig. 1). When asked to specify the individuals residing within the household, 1806 (42.5%) HCP indicated they lived with at least one child, 2795 (65.8%) with a spouse or significant other, 271 (6.4%) with a roommate, and 513 (12.1%) with other family. A total of 822 (19.4%) HCP indicated that they lived with an unvaccinated individual.

FIGURE 1.

FIGURE 1

Open in a new tab

Household size and household size categories stratified by COVID-19 status among HCP.

Exposure to Individuals With Test-Confirmed or Suspected COVID-19 Illness

A total of 1836 (43.3%) HCP reported having contact with an individual with test-confirmed or suspected COVID-19 illness at work (1080, 58.8%), in the household (609, 33.2%), or community (426, 23.2%). Of those reporting exposure to a household member with known SARS-CoV-2 infection, 338 (55.5%) reported living with a child and 131 (21.5%) reported living with an unvaccinated household member.

Factors Associated With HCP COVID-19

Using bivariate mixed-effects regression, we found that exposure to a household member with known COVID-19 was associated with increased odds of COVID-19 (unadjusted odds ratio [uOR] = 2.20, 95% confidence interval [95% CI] 1.82–2.67). This was not observed for workplace or community exposures. We also found that HCP reporting living with children had increased odds of exposure to a household member with COVID-19 (uOR = 1.89 [1.59–2.25]).

We did not find an association between living with children or living with an unvaccinated household member and HCP COVID-19 (Table 1, Fig. 2). Reported prior SARS-CoV-2 infection (uOR = 0.40 [0.35–0.47]) was associated with reduced odds of HCP COVID-19 (Table 1, Fig. 3). In an exploratory analysis, HCP reporting prior SARS-CoV-2 infection was associated with living with an unvaccinated household member (uOR = 1.21 [1.02–1.44]) but was not associated with living with children (Fig. 2, footnote).

TABLE 1.

Unadjusted and Adjusted Odds Ratios for COVID-19 Among HCP by Reported Household Characteristics, HCP Prior Infection, and HCP Current Vaccination Status

Variable uOR [95% CI] Multivariable Model 2
aOR [95% CI]		 Multivariable Model 3
aOR [95% CI]		 Multivariable Model 4
aOR [95% CI]
House size category
 Alone Ref
 One other 1.30 [1.06–1.59] 1.32 [1.07–1.63] 1.34 [1.09–1.65] 1.32 [1.07–1.63]
 Two or three 1.20 [0.98–1.47] 1.12 [0.87–1.45] 1.26 [1.02–1.56] 1.13 [0.88–1.46]
 Four or more 1.17 [0.91–1.50] 1.07 [0.79–1.46] 1.22 [0.92–1.60] 1.09 [0.80–1.49]
Reported living with children
 No Ref
 Yes 1.06 [0.93–1.21] 1.14 [0.94–1.39] 1.16 [0.95–1.41]
Unvaccinated household member
 No Ref
 Yes 0.99 [0.84–1.17] 0.97 [0.81–1.17] 0.94 [0.78–1.14]
HCP reported previous SARS-CoV-2 infection within 12 months
 No Ref
 Yes 0.40 [0.35–0.47] 0.40 [0.34–0.47] 0.40 [0.34–0.47] 0.40 [0.34–0.47]
HCP received COVID-19 vaccination within 6 months
 No Ref
 Yes 0.86 [0.74–1.01] 0.81 [0.69–0.96] 0.81 [0.69–0.95] 0.81 [0.69–0.95]
Open in a new tab

Bolded values indicate statistical significance at P <0.05.

Each column represents a separate unadjusted or multivariable model. All multivariable models adjusted for household size category, age, sex, race/ethnicity, job role, education level, presence of two or more comorbidities, HCP current vaccination, and prior infection status as fixed effects. Additionally, model 2 adjusted for living with children, model 3 adjusted for living with at least one unvaccinated household member, and model 4 adjusted for both living with children or with an unvaccinated household member. SARS-CoV-2 testing site and one-month period when testing was performed were treated as random effects in all models. Bolded values indicate statistical significance at P < 0.05.

95% CI, 95% confidence interval; aOR, adjusted odds ratio; uOR, unadjusted odds ratio.

FIGURE 2.

FIGURE 2

Open in a new tab

Unadjusted odds ratios for COVID-19 among HCP, by reported characteristics. Results from individual mixed effects, logistic regression models. HCP prior COVID-19 illness, current vaccination, household size (living with one other, living with two or three others, living with 4 or more), and living with an unvaccinated household member were treated as fixed effects. SARS-CoV-2 testing site and one-month period when testing was performed were treated as random effects. Footnote: A secondary, exploratory analysis assessed the associations between HCP reported previous SARS-CoV-2 infection (rather than enrollment with COVID-19) and living with an unvaccinated household member or children. These analyses found HCP reporting prior SARS-CoV-2 infection was associated with living with an unvaccinated household member (uOR = 1.21 [1.02–1.44]), but no significant association was found for living with children (uOR = 1.08 [0.94–1.24]).

FIGURE 3.

FIGURE 3

Open in a new tab

Adjusted odds ratios for COVID-19 among HCP by location of reported exposure to a person with COVID-19. Results from multivariable, mixed effects, logistic regression model that adjusted for age, sex, race/ethnicity, job role, education level, presence of two or more comorbidities, HCP current vaccination, HCP reported prior SARS-CoV-2 infection and exposure locations as fixed effects. SARS-CoV-2 testing site and one-month period when testing was performed were treated as random effects.

HCP living with one other person had higher odds of COVID-19 compared to HCP living alone (uOR = 1.29 [1.06–1.59], Table 1, Figure 2). We did not find an association for HCP who lived with two or three other people, or four or more other people and COVID-19 (Table 1, Fig. 2).

Multivariable modeling indicated that being exposed to a household member with known SARS-CoV-2 infection was associated with increased odds of COVID-19 (adjusted odds ratio [aOR] = 2.21, 95% CI [1.81–2.69]). HCP exposed to individuals with known SARS-CoV-2 infection at work were found to have lower odds of COVID-19 (aOR = 0.83 [0.70–0.98]) while those not sure had higher odds of COVID-19 (aOR = 1.19 [1.01–1.39]) (Fig. 3). The stratified analysis by pandemic phase showed similar results. Complete model results provided in SDC Table 4 (http://links.lww.com/JOM/C156).

Using separate multivariable models we did not find an association between living with children nor living with an unvaccinated household member and COVID-19. When adjusting for both living with children and at least one unvaccinated household member, similar results were observed (Table 1). Compared to HCP who lived alone, HCP who lived with one other person had increased odds of COVID-19 in all multivariable models (Table 1). Living with two or three others was associated with increased odds of HCP COVID-19 in one model but not the others, while no association was observed for those living with four or more individuals (Table 1). In all multivariable models, we found that known prior SARS-CoV-2 infection, recent SARS-CoV-2 vaccination, and HCP who identified as Hispanic or Latino had lower odds of COVID-19 (Table 1). The stratified analysis yielded similar results, except that HCP with missing race and ethnicity data consistently had lower odds of COVID-19 during the Omicron period. In addition, no association was observed between recent vaccination and lower odds of HCP COVID-19 during the post-Omicron period. Complete model results provided in SDC Tables 4–7 (http://links.lww.com/JOM/C156). We assessed data for collinearity and screened for interactions between variables and found no statistically significant findings.

DISCUSSION

Our findings suggest that workplace exposure to individuals with known or suspected COVID-19 did not significantly increase COVID-19 infection risk among HCP. Conversely, HCP exposure to infected household members was associated with increased COVID-19 odds. We observed no association between HCP infection and living with children or unvaccinated household members. These results demonstrate that household transmission represents a substantial source HCP, while workplace exposure and specific household characteristics, such as the presence of children or unvaccinated individuals, may contribute less to overall risk.

Previous studies have shown that exposure to test-confirmed household members with COVID-19 increases infection risk among HCP,10,31,32 while workplace exposure poses lower risk.16,33,34 Our findings align with these reports and highlight the role of household transmission in HCP infections, particularly during the Omicron and subvariant phases of the pandemic. The reduced workplace transmission may reflect shorter exposure duration, adherence to contact and respiratory precautions, or recall bias compared to household settings. Institutional infection prevention strategies, such as mask use and personal protective equipment requirements—protections typically absent in home environments—likely contributed to lower workplace transmission rates.

We found no association between living with children and HCP COVID-19 at enrollment or prior SARS-CoV-2 infection, despite observing an association between household COVID-19 exposure and living with children. This lack of association likely reflects the impact of SARS-CoV-2 across all age groups rather than being concentrated in children.35,36 Household transmission appear similar for children and adults37 suggesting HCP face comparable exposure risk from household members regardless of age.

Contrary to our hypothesis, living with unvaccinated household members demonstrated no association with HCP COVID-19. However, exploratory analysis revealed a link to prior SARS-CoV-2 infection. Because prior infection was associated with lower COVID-19 odds, HCP living with unvaccinated household members may have experienced higher past infection rates, providing protective immunity that potentially confounds our observed association. While some studies suggest indirect protection from vaccinated household members,14,38 this impact may be limited as immunity against infection wanes over time and proves more effective at preventing severe illness than infection.39,40

Compared to those who live alone, HCP living with one other household member had increased COVID-19 odds across all multivariable models. However, we found no association for those living with two or more people. Most HCP reporting living with two or more other household members also lived with children (76.2% of those living with two or three other household members and 81.1% of those living with four or more household members), likely explaining the absence of association between these household size categories and HCP COVID-19 when adjusting for living with children. These findings suggest that HCP in larger households more commonly live with children, and children in these households may contribute to increased COVID-19 odds.

Prior HCP SARS-CoV-2 infection and current vaccination status were consistently associated with lower COVID-19 odds in our multivariable models. A meta-analysis of 65 studies from 19 countries demonstrated pooled effectiveness of past infection against Omicron BA.1 variant reinfection of 45.3% (95% uncertainty interval [UI] 17.3–76.1]).26 A separate meta-analysis found that hybrid immunity from vaccination and prior infection conferred protection against reinfection at least 3 months (effectiveness = 68.6% [58.8–76.9]) and 6 months following the first booster (effectiveness = 46.5 [36.0–57.3]).40 Vaccination and prior infection also reduce infectiousness and transmission likelihood of SARS-CoV-2 to close contacts.14,18,41,42 Our results and prior studies suggest that HCP vaccination status and household members’ vaccination or infection history could influence odds of infection following household COVID-19 exposure.

This study has several limitations. We lacked data on household members’ ages, vaccination timing, and prior infections which prevented further analysis and restricted interpretation of our findings regarding young children or unvaccinated household members. Misclassification of prior infections and exposures likely occurred, as we only captured known infections among study participants. Immunity from vaccination or infection wanes over time, influencing transmission dynamics. HCP may demonstrate greater awareness of household exposures than exposures in other settings, and we could not assess household COVID-19 prevention efforts. As a case-control study, we faced potential residual confounding, misclassification, and recall bias. We relied on self-reported COVID-19 exposures, which could not be independently verified; therefore, some misclassification may have occurred, particularly regarding community contacts. The survey question regarding living with children lacked defined age ranges, potentially explaining nonsignificant findings, as risk likely varies by age due to school and daycare attendance patterns.43 A dedicated household study could address these uncertainties. Lastly, this study was conducted among HCP enrolled in a vaccine effectiveness study across multiple large academic medical centers; therefore, the generalizability of our findings is likely limited to similar HCP populations. Despite these limitations, we remain confident in our findings and conclusions.

CONCLUSIONS

In conclusion, household COVID-19 exposure was associated with increased SARS-CoV-2 infection risk among HCP, while workplace exposure was associated with decreased infection risk. COVID-19 vaccination demonstrated continued protection against COVID-19 in this population. Living with children or unvaccinated household members was not associated with HCP COVID-19 infection risk.

ACKNOWLEDGMENTS

The authors acknowledge the following participating Project PREVENT medical centers: Baystate Medical Center, Springfield, Massachusetts; Brigham and Women’s Hospital, Boston, Massachusetts; Duke University Durham, North Carolina; Jackson Memorial Hospital, Miami, Florida; Johns Hopkins Hospital, Baltimore, Maryland; University Medical Center New Orleans, Louisiana State University Health Sciences Center New Orleans Louisiana; Olive View-University of California Los Angeles Medical Center, Los Angeles, California; Jefferson Health, Philadelphia, Pennsylvania; Oregon Health & Science University, Portland, Oregon; Thomas Jefferson University, Philadelphia, Pennsylvania; University Health Truman Medical Center/University of Missouri-Kansas City, Kansas City, Missouri; University of Alabama at Birmingham, Birmingham, Alabama; University of California-Los Angeles Ronald Reagan Medical Center, Los Angeles, California; University of Chicago Medicine, Chicago, Illinois; University of Iowa Hospitals & Clinics, Iowa City, Iowa; University of Massachusetts Memorial Medical Center, Worcester, Massachusetts; University of New Mexico Health Sciences Center, Albuquerque, New Mexico; University of San Francisco, Fresno Community Medical Center, Fresno, California; University of Utah, Salt Lake City, Utah; University of Washington, Seattle, Washington; and Valleywise Health Medical Center, Phoenix, Arizona. The authors would also like to acknowledge the following individuals: Glen Abedi, Bechtler Addison, Danielle Beckham, Erin Biddiscombe, Rylee Bledsoe, Tamara Brocks, Morgan Brower, Emmanuel Chen, Harrison Chen, Nikki Daniels, Maria Davila, Martine Desulme, Sofia DiFulvio, Svea Eckstrand, Alicia Edwardson, Rosanna Escobar, Danielle Ferdinand, Suzette Fernandez, Sophie Finkelstein, Luke Francese, James Galbraith, Abigail L Girardin, Karina Goicochea, Eva Gonzalez, Nathan Graff, Manar Y Hamied, Cady Hart, Mohammad Adrian Hasdianda, Tammy Hawley, Kristen Hepfer, Carson Herman, Kate Higgins, Karen Hopcia, Leslie Olivia Hopkins, Lauren Howard, Jade James-Gist, Jonathan Jui, Patrick McGrath, Chloe Namias, Miguel Neeley, Sankan Nyanseor, Liam Pauli, Peter Poerzgen, Tedra Porter, Antonella Riega, Micki Rockett, Jonathan Rufino, Mazin Sabeh, Joshua Sarafian, Michelle Tetro, Tala Teymour, Denise Tritt, Nikita Umale, Jaran White, Caitlin Wizda, Gao Xiong, Madeline Young, and Sepahrad Zamani.

Footnotes

The Project PREVENT Network includes the following: Monica Bahamon, MPH; David G Beiser, MD, MS; Silas Bussmann, MPH, MBA; Jacqueline Caldera, BS; Brian Chinnock, MD; Anne K Chipman, MD, MS; James C Crosby, MD; Marcel E Curlin, MD; Gaby Dashler, BS; Katherine Elkort, BS; Stephanie A Eucker, MD, PhD; Brett Faine, PharmD, MS; Jon Femling, MD, PhD; Jake Hampton, BA; John P Haran, MD, PhD; Dean M Hashimoto, MD; Rawan Hassanain, MBBS; Peter C Hou, MD; Michelle Huber, MD, MPH; Laurie Kemble, BHS, CRT, CCRC; Carla Kingsbury, BS; Lilly C Lee; Stephen C Lim, MD; Abigail Lopes, BA; Frank LoVecchio, DO, MPH; William Mower, MD, PhD; Mary Mulrow, MA, MN; Utsav Nandi, MD, MSCI; Kavitha Pathmarajah, MPH; Richard E Rothman, MD, PhD; Sara Roy, MsCR; Walter A Schrading, MD; Howard A Smithline; Lucia Solis, BS; Amy M Stubbs, MD; Joseph Stuppy, BS; Jillian M Tozloski, MS; Mastura Wahedi, BS; Kelli Wallace, MS; Jane Yee, MD; Tracy Young, MS; Anne Zepeski, PharmD.

CDC Disclaimer: The findings and conclusions in this article are those of the authors and do not necessarily represent the views of the Centers for Disease Control and Prevention.

Funding sources: This project was funded by the Centers for Disease Control and Prevention (CDC) (U01CK000480). The project was additionally supported by the Institute for Clinical and Translational Science at the University of Iowa through a grant from the National Center for Advancing Translational Sciences of the National Institutes of Health (UM1TR004403).

Conflicts of interests: None declared.

Specific author contributions of every author listed: EK performed all analyses presented in this manuscript and was a major contributor in writing the manuscript. AKI and NMM both assisted in conceptualization of the research in addition to being major contributors in writing the manuscript. IDP, MBH, KDH, AK, DAT, PTE, MTS, and ERK all made substantial contributions to interpretation of the data and provided substantive revisions. All authors have read and approved the final manuscript for submission.

Data availability: The datasets generated and/or analyzed during the current study are available in the PREVENT II repository on Opens Science Framework https://osf.io/yqwxn/?view_only=8d2034ee64394f1aa6e2a23422caff8c.

EQUATER Network checklist utilized: STROBE.

AI detailed statements as fully described in the AI section: No AI was utilized at any stage during research development & design, data collection, manuscript preparation etc.

Ethical Consideration & Disclosure(s): This activity was reviewed by CDC, deemed not research, and was conducted consistent with applicable federal law and CDC policy. In addition, the activity was deemed nonresearch by local institutional review boards (IRB), except for one site's IRB that considered this project to be human subject research. Written consent was obtained for all participants.

Supplemental digital contents are available for this article. Direct URL citation appears in the printed text and is provided in the HTML and PDF versions of this article on the journal’s Web site (www.joem.org).

Contributor Information

Amanda K. Irish, Email: amanda-irish@uiowa.edu.

Ian D. Plumb, Email: ydk9@cdc.gov.

Melissa Briggs-Hagen, Email: vka5@cdc.gov.

Karisa K. Harland, Email: kari-harland@uiowa.edu.

Anusha Krishnadasan, Email: idnet@ucla.edu.

David A. Talan, Email: dtalan@ucla.edu.

Patrick Ten Eyck, Email: patrick-teneyck@uiowa.edu.

Mark T. Steele, Email: mark.steele@uhkc.org.

Efrat R. Kean, Email: efrat.kean@jefferson.edu.

Nicholas M. Mohr, Email: nicholas-mohr@uiowa.edu.

REFERENCES

  • 1.Impact of the COVID-19 pandemic on the hospital and outpatient clinician workforce: challenges and policy responses (Issue Brief No. HP-2022-13). Washington, DC: Office of the Assistant Secretary for Planning and Evaluation, U.S. Department of Health and Human Services; 2022. [Google Scholar]
  • 2.Maltezou HC, Ledda C, Sipsas NV. Absenteeism of healthcare personnel in the COVID-19 era: a systematic review of the literature and implications for the post-pandemic seasons. Healthcare (Basel) 2023;11:2950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Shah ASV Wood R Gribben C, et al. Risk of hospital admission with coronavirus disease 2019 in healthcare workers and their households: nationwide linkage cohort study. BMJ 2020;371:m3582. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Lindsey BB Villabona-Arenas CJ Campbell F, et al. Characterising within-hospitalSARS-CoV-2 transmission events using epidemiological and viral genomic data across two pandemic waves. Nat Commun 2022;13:671. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Klompas M, Karan A. Preventing SARS-CoV-2 transmission in health care settings in the context of the omicron variant. JAMA 2022;327:619–620. [DOI] [PubMed] [Google Scholar]
  • 6.Vyas N Bennett A Shaver N, et al. SARS-CoV-2 transmission risk for common group activities and settings: a living scoping review. Eur J Public Health 2024;34:196–201. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Nguyen LH Drew DA Graham MS, et al. Risk of COVID-19 among front-line health-care workers and the general community: a prospective cohort study. Lancet Public Health 2020;5:e475–e483. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 8.Le D, Hawkins D. Variation in employment in healthcare occupations and county-level differences in COVID-19 cases in the United States of America. J Occup Environ Med 2021;63:629–631. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Shah MM Spencer BR Feldstein LR, et al. Occupations associated with severe acute respiratory syndrome coronavirus 2 infection and vaccination, US blood donors, May 2021–December 2021. Clin Infect Dis 2023;76:1285–1294. [DOI] [PubMed] [Google Scholar]
  • 10.Bahrs C Weis S Kesselmeier M, et al. Non-patient-related SARS-CoV-2 exposure from colleagues and household members poses the highest infection risk for hospital employees in a German university hospital: follow-up of the prospective co-HCW seroprevalence study. Infection 2023;51:1051–1059. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Carazo S Villeneuve J Laliberte D, et al. Risk and protective factors for severe acute respiratory coronavirus virus 2 (SARS-CoV-2) infection among healthcare workers: a test-negative case-control study in Quebec, Canada. Infect Control Hosp Epidemiol 2023;44:1121–1130. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Piccoli L Ferrari P Piumatti G, et al. Risk assessment and seroprevalence of SARS-CoV-2 infection in healthcare workers of COVID-19 and non-COVID-19 hospitals in Southern Switzerland. Lancet Reg Health Eur 2021;1:100013. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Eyre DW Lumley SF O'Donnell D, et al. Differential occupational risks to healthcare workers from SARS-CoV-2 observed during a prospective observational study. Elife 2020;9:e60675. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14.Salo J Hagg M Kortelainen M, et al. The indirect effect of mRNA-based COVID-19 vaccination on healthcare workers' unvaccinated household members. Nat Commun 2022;13:1162. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Shah ASV Gribben C Bishop J, et al. Effect of vaccination on transmission of SARS-CoV-2. N Engl J Med 2021;385:1718–1720. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kohler P Dörr T Friedl A, et al. SARS-CoV-2 risk in household contacts of healthcare workers: a prospective cohort study. Antimicrob Resist Infect Control 2023;12:98. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.McCormick DW Konkle SL Magleby R, et al. SARS-CoV-2 infection risk among vaccinated and unvaccinated household members during the Alpha variant surge–Denver, Colorado, and San Diego, California, January–April 2021. Vaccine 2022;40:4845–4855. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Tan ST Kwan AT Rodríguez-Barraquer I, et al. Infectiousness of SARS-CoV-2 breakthrough infections and reinfections during the Omicron wave. Nat Med 2023;29:358–365. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Pilishvili T Gierke R Fleming-Dutra KE, et al. Effectiveness of mRNA Covid-19 vaccine among U.S. health care personnel. N Engl J Med 2021;385:e90. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Von Elm E, Altman DG, Egger M, Pocock SJ, Gøtzsche PC, Vandenbroucke JP. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 2007;370:1453–1457. [DOI] [PubMed] [Google Scholar]
  • 21.45 C.F.R. part 46.102(l)(2), 21 C.F.R. part 56; 42 U.S.C. §241(d); 5 U.S.C. §552a; 44 U.S.C. §3501 et seq. [Google Scholar]
  • 22.Gottlieb M, Long B. Dermatologic manifestations and complications of COVID-19. Am J Emerg Med 2020;38:1715–1721. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23.Rothan HA, Byrareddy SN. The epidemiology and pathogenesis of coronavirus disease (COVID-19) outbreak. J Autoimmun 2020;109:102433. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Plumb ID Mohr NM Hagen M, et al. Effectiveness of a messenger RNA vaccine booster dose against coronavirus disease 2019 among US healthcare personnel, October 2021–July 2022. Open Forum Infect Dis 2023;10:ofad457. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Goldberg Y Mandel M Bar-On YM, et al. Protection and waning of natural and hybrid immunity to SARS-CoV-2. N Engl J Med 2022;386:2201–2212. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Stein C Nassereldine H Sorensen RJ, et al. Past SARS-CoV-2 infection protection against re-infection: a systematic review and meta-analysis. Lancet 2023;401:833–842. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Li H Burm SW Hong SH, et al. A comprehensive review of coronavirus disease 2019: epidemiology, transmission, risk factors, and international responses. Yonsei Med J 2021;62:1–11. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28.Hadley E Yoo YJ Patel S, et al. Insights from an N3C RECOVER EHR-based cohort study characterizing SARS-CoV-2 reinfections and Long COVID. Commun Med (Lond) 2024;4:129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Belsley DA, Kuh E, Welsch RE. Regression Diagnostics: Identifying Influential Data and Sources of Collinearity. John Wiley & Sons; 2005. [Google Scholar]
  • 30.Li W, Nyholt DR. Marker selection by Akaike information criterion and Bayesian information criterion. Genet Epidemiol 2001;21(S1):S272–S277. [DOI] [PubMed] [Google Scholar]
  • 31.Paris C Tadié E Heslan C, et al. Risk factors for SARS-CoV-2 infection among health care workers. Am J Infect Control 2022;50:375–382. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Lopez Bernal J Panagiotopoulos N Byers C, et al. Transmission dynamics of COVID-19 in household and community settings in the United Kingdom, January to March 2020. Euro Surveill 2022;27:2001551. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Shah VP Breeher LE Alleckson JM, et al. Occupational exposure to severe acute respiratory coronavirus virus 2 (SARS-CoV-2) and risk of infection among healthcare personnel. Infect Control Hosp Epidemiol 2022;43:1785–1789. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 34.Wight E Swift M O'Horo JC, et al. COVID-19 infections in health care personnel by source of exposure and correlation with community incidence. J Occup Environ Med 2022;64:675–678. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Yang HS Costa V Racine-Brzostek SE, et al. Association of age with SARS-CoV-2 antibody response. JAMA Netw Open 2021;4:e214302. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 36.Goldstein E, Lipsitch M, Cevik M. On the effect of age on the transmission of SARS-CoV-2 in households, schools, and the community. J Infect Dis 2021;223:362–369. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Zhu Y, Xia Y, Pickering J, Bowen AC, Short KR. The role of children in transmission of SARS-CoV-2 variants of concern within households: an updated systematic review and meta-analysis, as at 30 June 2022. Euro Surveill 2023;28:2200624. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Hayek S Shaham G Ben-Shlomo Y, et al. Indirect protection of children From SARS-CoV-2 infection through parental vaccination. Science 2022;375:1155–1159. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Ssentongo P Ssentongo AE Voleti N, et al. SARS-CoV-2 vaccine effectiveness against infection, symptomatic and severe COVID-19: a systematic review and meta-analysis. BMC Infect Dis 2022;22:439. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Bobrovitz N Ware H Ma X, et al. Protective effectiveness of previous SARS-CoV-2 infection and hybrid immunity against the omicron variant and severe disease: a systematic review and meta-regression. Lancet Infect Dis 2023;23:556–567. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41.Eyre DW Taylor D Purver M, et al. Effect of Covid-19 vaccination on transmission of alpha and delta variants. N Engl J Med 2022;386:744–756. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Layan M Gilboa M Gonen T, et al. Impact of BNT162b2 vaccination and isolation on SARS-CoV-2 transmission in Israeli households: an observational study. Am J Epidemiol 2022;191:1224–1234. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Hyde Z. COVID-19, children and schools: overlooked and at risk. Med J Aust 2020;213:444–446.e1. [DOI] [PubMed] [Google Scholar]

Articles from Journal of Occupational and Environmental Medicine are provided here courtesy of Wolters Kluwer Health

RESOURCES