Epidemiology and viral genomic characteristics of COVID-19 clustering epidemics of in Chengdu city - Yue CHENG; Zhu LIU; Lu LONG (Editorial Office of Chinese Journal of Public Health, 2022)
ObjectiveTo analyze epidemiology and viral genomics characteristics of coronavirus disease 2019 (COVID-19) clustering epidemics in Chengdu city and to explore risk factors for the incidence of the cluster epidemics. MethodsThe data on all COVID-19 clustering cases diagnosed in Chengdu city of Sichuan province during January - February, 2020 were collected for descriptive epidemiology analysis. Realtime-PCR was used to detect nucleic acid of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) isolated from the cases' oropharyngeal or nasopharyngeal swab specimens. Next-generation sequencing was performed for genotype and nucleotide polymorphism analysis on the isolated viruses. ResultsTotally 75 cases of 24 clustering epidemics occurred in the city during the period, with more cases for each clustering epidemic in rural regions than in urban and town regions. Travel history was confirmed among 79.17%（19/24） of the first cases of the clustering epidemics and 22 clustering epidemics was correlated with family transmission of the virus. The average time from the disease onset to the viral nucleic acid positive detection were 7.67, 5.54, and 2.05 days for the cases having a delayed seeking medication, having a timely medical treatment, and being isolated as a close contact, with a significant difference in the average time among the case groups (P < 0.0001). The average number of cases in each of the clustering epidemics with symptomatic patients was 4.25, significantly higher than that (2.56) of the clusters without symptomatic patients (P < 0.05). The cycle threshold (Ct) value of ORFlab gene of the strains from the first cases was lower than that from the secondary cases (P < 0.05). For the isolated virus strains, the first three genotypes were B.1.1, B and A; the mutation sites were concentrated in ORFlab, spike glycoprotein (S) and nucleocapsid (N) regions and there were no significant differences in the mutation sites among the strains from the clustering epidemics. ConclusionFor COVID-19 clustering epidemics occurred in Chengdu city, urban-rural disparity, population mobility, family aggregation, and delayed seeking medication are risk factors and the infections' latent period and asymptomatic cases are of important impact on the scale of the clustering epidemics. Investigation on epidemiology and viral genomics characteristics of a clustering epidemic should be conducted for the identification of infection source and virus transmission route of the clustering epidemic.