Epidemiological and clinical features of SARS-CoV-2 Omicron variant infection in China: A retrospective study

Background: A rapid increase in incidence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Omicron variant occurred in Quanzhou City, Fujian Province, China, in March 2022. This study investigated the epidemiological and clinical features of SARS-CoV-2 Omicron variant (BA.2)-infected patients. Methods: Epidemiological and clinical data of SARS-CoV-2 Omicron variant infected patients admitted to three designated hospitals in Quanzhou were collected and analyzed. Results: : Overall, 2,541 patients infected with BA.2, comprising 1,060 asymptomatic, 1,287 mild, and 194 moderate infections, were enrolled in this study. The percentage of moderate infections was higher in those aged ≥60 than in those aged <18 and 18-59. The median hospitalization duration was 17 (14-20) days. Among the 2,541 patients, 43.52% had a clear history of close contact. The vaccination rate for coronavirus disease was 87.92%, and the percentage of asymptomatic infections was higher in vaccinated patients than in unvaccinated patients. Moreover, 10.82% with underlying diseases, such as hypertension (5.94%) and diabetes mellitus (3.12%), had a higher percentage of moderate infections than those without underlying diseases. The three most common clinical manifestations among the patients were fever (27.47%), dry cough (25.19%), and sore throat (15.31%). The albumin-to-globulin (A/G) ratio and lymphocyte count decreased in the cases of mild and moderate infections, while procalcitonin, erythrocyte sedimentation rate, interleukin-6, D-dimer, and C4 levels increased. The pulmonary computed tomography findings for moderate infections were generally patchy and ground-glass opacities. Conclusions: : Advanced age, non-vaccination, and underlying comorbid disease are high-risk factors for disease progression in Omicron variant-infected patients, while dynamic monitoring of blood routine parameters, A/G ratio, and inflammatory indicators facilitate the prediction of disease progression.