RESUMO
BackgroundQuantifying occupational risk factors for SARS-CoV-2 infection among healthcare workers can inform efforts to improve healthcare worker and patient safety and reduce transmission. This study aimed to quantify demographic, occupational, and community risk factors for SARS-CoV-2 seropositivity among healthcare workers in a large metropolitan healthcare system. MethodsWe analyzed data from a cross-sectional survey conducted from April through June of 2020 linking risk factors for occupational and community exposure to COVID-19 with SARS-CoV-2 seropositivity. A multivariable logistic regression model was fit to quantify risk factors for infection. Participants were employees and medical staff members who elected to participate in SARS-CoV-2 serology testing offered to all healthcare workers as part of a quality initiative, and who completed a survey on exposure to COVID-19 and use of personal protective equipment. Exposures of interest included known demographic risk factors for COVID-19, residential zip code incidence of COVID-19, occupational exposure to PCR test-positive healthcare workers or patients, and use of personal protective equipment. The primary outcome of interest was SARS-CoV-2 seropositivity. ResultsSARS-CoV-2 seropositivity was estimated to be 5.7% (95% CI: 5.2%-6.1%) among 10,275 healthcare workers. Community contact with a person known or suspected to have COVID-19 (aOR=1.9, 95% CI:1.4-2.5) and zip code level COVID-19 incidence (aOR: 1.4, 95% CI: 1.0-2.0) increased the odds of infection. Black individuals were at high risk (aOR=2.0, 95% CI:1.6-2.4). Overall, occupational risk factors accounted for 27% (95% CI: 25%-30%) of the risk among healthcare workers and included contact with a PCR test-positive healthcare worker (aOR=1.2, 95% CI:1.0-1.6). ConclusionsCommunity risk factors, including contact with a COVID-19 positive individual and residential COVID-19 incidence, are more strongly associated with SARS-CoV-2 seropositivity among healthcare workers than exposure in the workplace.
RESUMO
In response to the COVID-19 pandemic, institutions of higher education in almost every nation closed in the first half of 2020. University administrators are now facing decisions about if and how to safely return students, staff and faculty to campus. To provide a framework to evaluate various strategies, we developed a susceptible-exposed-infectious-recovered (SEIR) type deterministic compartmental transmission model of SARS-CoV-2 among students, staff and faculty. Our goals were to support the immediate pandemic planning at our own university, and to provide a flexible modeling framework to inform the planning efforts at similar academic institutions. We parameterized the model for our institution, Emory University, a medium-size private university in Atlanta, Georgia. Control strategies of isolation and quarantine are initiated by screening (regardless of symptoms) or testing (of symptomatic individuals). We explore a range of screening and testing frequencies and perform a probabilistic sensitivity analysis of input parameters. We find that monthly and weekly screening can reduce cumulative incidence by 30% and 81% in students, respectively, while testing with a 2-, 4- and 7-day delay results in an 92%, 85% and 73% reduction in cumulative incidence in students over the semester, respectively. Smaller reductions are observed among staff and faculty. A testing strategy requires far fewer diagnostic assays to be implemented than a screening assay. Our intervention model is conservative in that we assume a fairly high reproductive number. We find that community-introduction of SARS-CoV-2 infection onto campus may be controlled with effective testing, isolation, contract tracing and quarantine, but that cases, hospitalization, and (in some scenarios) deaths may still occur. In addition to estimating health impacts, this model can help to predict the resource requirements in terms of diagnostic capacity and isolation/quarantine facilities associated with different strategies.
