Epidemiological characteristics of first-time SARS-CoV-2 Omicron infection among hospital staff in Chengdu, China

Abstract

Background: After China ended its ‘dynamic zero-COVID policy’ on 7 December 2022, a large-scale outbreak of SARS-CoV-2 Omicron infections emerged across the country. We conducted a hospital-wide prospective study to document the epidemiological characteristics of the outbreak among healthcare workers in a hospital of Chengdu, where no previous staff SARS-CoV-2 infections were detected. Methods: All hospital staff members were invited to complete an online questionnaire on COVID-19 in January 2023, and SARS-CoV-2 infection cases were followed up by telephone in June 2023 to collect data on long COVID. Univariable and multivariable logistic regression analyses were performed to evaluate factors associated with SARS-CoV-2 infection. Results: A total of 2,899 hospital staff (93.5%) completed the online questionnaire, and 86.4% were infected with SARS-CoV-2 Omicron. The clinical manifestations of these patients were characterized by a high incidence of systemic symptoms. Cough (83.4%), fatigue (79.8%) and fever (74.3%) were the most frequently reported symptoms. Multivariable logistic analysis revealed that females [adjusted odds ratio (aOR): 1.42, 95% confidence interval (CI): 1.07–1.88] and clinical practitioners (aOR: 10.32, 95% CI: 6.57–16.20) were associated with an increased risk of SARS-CoV-2 infection, whereas advanced age ≥ 60 years (aOR: 0.30, 95% CI: 0.19–0.49) and a three-dose COVID-19 vaccination with the most recent dose administered within 3 months before 7 December 2022 (aOR: 0.44, 95% CI: 0.23–0.87 for within 1 month; aOR: 0.46, 95% CI: 0.22–0.97 for within 1–3 months) were associated with reduced risk. Among the cases, 4.27% experienced long COVID of fatigue, brain fog or both, with the majority reporting minor symptoms. Conclusion: Our findings provide a snapshot of the epidemiological situation of SARS-CoV-2 infection among healthcare workers in Chengdu after China’s deregulation of COVID-19 control. Data in the study can aid in the development and implementation of effective measures to protect healthcare workers and maintain the integrity of healthcare systems during challenging times such as a rapid and widespread Omicron outbreak.