Epidemiological features of SARS-CoV-2 Omicron infection under new control strategy: a cross-sectional study of the outbreak since December 2022 in Sichuan, China

Abstract

Background A major shift in the “dynamic zero-COVID” policy was announced by China’s National Health Commission on December 7, 2022, and the subsequent immediate large-scale outbreak of SARS-CoV-2 infections in the entire country has caused worldwide concern. This observational cross-sectional study aimed to describe the epidemiological characteristics of this outbreak in Sichuan, China. Methods All data were self-reported online by volunteers. We described the epidemic by characterizing the infection, symptoms, clinical duration, severity, spatiotemporal clustering, and dynamic features of the disease. Prevalence ratio (PR), Odds ratios (ORs) and adjusted ORs were calculated to analyze the associations between risk factors and infection and the associations of risk factors with clinical severity using log-binomial and multivariable logistic regression models; 95% confidence intervals (CIs) and Wald test results were reported. The prevalence rates and clinical severity among different subgroups were compared using the Chi-square and trend Chi-square tests. Results Between January 6 and 12, 2023, 138,073 volunteers were enrolled in this survey, and 102,645 were infected with COVID-19, holding a prevalence rate of 74.34%; the proportion of asymptomatic infections was 1.58%. Log-binomial regression revealed that the risk of infection increased among those living in urban areas. Multivariable logistic regression analysis showed that female sex, chronic diseases, older age and the fewer doses of vaccine received were associated with an increased risk of severe clinical outcomes after infection. We estimated the mean reproduction number during this pandemic was 1.83. The highest time-dependent reproduction number was 4.15; this number decreased below 1 after 11 days from December 7, 2022. Temporal trends revealed a single peak curve with a plateau pattern of incidence during the outbreak, whereas spatiotemporal clustering analysis showed that the onset in 21 cities in the Sichuan province had four-wave peaks. Conclusions The peak of the first wave of Omicron infection in Sichuan Province had passed and could be considered a snapshot of China under the new control strategy. There were significant increases in the risk of severe clinical outcomes after infection among females, with chronic diseases, and the elderly. The vaccines have been effective in reducing poor clinical outcomes.

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

“…Our study revealed a cumulative incidence of SARS-CoV-2 Omicron infection of 86.4% (95% CI 85.2%-87.7%) among hospital staff from Chengdu Women's and Children's Hospital. As expected, it was higher than that reported among the general population of 74.3% in the same province [12], suggesting a greater infection risk faced by hospital staff during an Omicron outbreak. In addition, our rate was much higher than that previously reported for healthcare workers in other studies, most of which had an even longer time frame than our research [13][14][15][16][17].…”

“…BMI: body mass index, SD: standard deviation.a Chi-square test or ANOVA for differences among the three groups: con rmed COVID-19 diagnosis, probable COVID-19, and no COVID-19-like symptoms.Table 2 compares the COVID-19-related characteristics between individuals with a COVID-19 diagnosis and highly suspected COVID-19 patients. The former group reported a greater median number of COVID-19 symptoms(14,) and a higher percentage of individuals taking leave from work due to illness (44.5%) than did participants in the latter group (13, IQR[9][10][11][12][13][14][15][16][17]; 30%). However, no statistically signi cant differences in disease severity (using either admission to hospital or diagnosis of pneumonia as a proxy) were detected between the two groups (p > 0.05).…”

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

“…Our study revealed a cumulative incidence of SARS-CoV-2 Omicron infection among hospital staff from Chengdu Women’s and Children’s Hospital to be 86.4% (95% CI 85.2%-87.7%), which was higher than the reported rate of 74.3% among the general population in the same province [ 18 ]. However, since our study was conducted more than one week later, it is uncertain whether hospital staff faced a greater infection risk compared to individuals in the community or if the timing difference influenced the documentation of cumulative incidence rates during a rapid and widespread Omicron outbreak.…”

“…Table 2 compares the COVID-19-related characteristics between individuals with a COVID-19 diagnosis and highly suspected COVID-19 patients. The former group reported a greater median number of COVID-19 symptoms (14, IQR [ 11 – 18 ]) and a higher percentage of individuals taking leave from work due to illness (44.5%) than did participants in the latter group (13, IQR [ 9 – 17 ]; 30%). However, no statistically significant differences in disease severity (using either admission to hospital or diagnosis of pneumonia as a proxy) were detected between the two groups ( p > 0.05).…”