Epidemiological characteristics of an epidemic of 2019-nCoV Omicron variant infection in Beijing
10.3760/cma.j.cn112338-20220901-00753
- VernacularTitle:北京市一起新型冠状病毒Omicron变异株聚集性疫情特征分析
- Author:
Yamin SUN
1
;
Feng LIU
;
Wei CAI
;
Lina JIN
;
Li GUO
;
Run CAI
;
Rujing SHI
;
Fangyao LIU
;
Chu JIANG
;
Jiye FU
;
Yang PAN
;
Xiangfeng DOU
;
Shuangsheng WU
Author Information
1. 北京市海淀区疾病预防控制中心传染病地方病控制科，北京 100094
- Keywords:
COVID-19;
Omicron variant;
Cluster epidemic;
Secondary attack rate
- From:
Chinese Journal of Epidemiology
2022;43(12):1881-1886
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To analyze the epidemiological characteristics and transmission chain of an epidemic of COVID-19 in Haidian district, Beijing.Methods:Descriptive epidemiological method was used to analyze the epidemiological characteristics of the epidemic, and field investigation and big data technology were used to analyze the transmission chain of the epidemic.Results:From April 27 to May 13, 2022, an epidemic of COVID-19 occurred in Haidian district. The strains isolated from the cases were identified by whole genome sequencing as Omicron variant (BA.2.2 evolutionary branch). A total of 38 infection cases were detected, including 34 confirmed cases and 4 asymptomatic cases. Most cases were mild ones (88.2%), no severe, critical or death cases occurred. The early clinical symptoms were mainly sore throat (50.0%) and cough (29.4%). The epidemic lasted for 17 days, resulting in 7 generations of the cases and involving 3 community transmissions, 2 working place transmissions and 8 family transmissions; the main infection routes were co-residence (47.6%) and co-space exposure (31.6%). The intergenerational interval M( Q1, Q3)was 3 (1, 6) days. The overall secondary attack rate was 1.5% (37/2 482), and the family secondary attack rate was 36.7% (18/49). Conclusions:The cases in this COVID-19 epidemic caused by Omicron variant had mild clinical symptoms, but the case clustering in families and communities was obvious, the transmission was rapid, and the risk for co-space exposure was high. It is necessary to use information technology to identify close contacts in the local population for the rapid and effective blocking of the epidemic spread.
