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程悦, 刘竹, 龙露, 党盛源, 胡敏, 谢汶君, 袁齐武, 戴映雪, 陈恒. 成都市新冠肺炎聚集性疫情流行病学与病原基因特征[J]. 中国公共卫生, 2022, 38(6): 752-757. DOI: 10.11847/zgggws1136549
引用本文: 程悦, 刘竹, 龙露, 党盛源, 胡敏, 谢汶君, 袁齐武, 戴映雪, 陈恒. 成都市新冠肺炎聚集性疫情流行病学与病原基因特征[J]. 中国公共卫生, 2022, 38(6): 752-757. DOI: 10.11847/zgggws1136549
CHENG Yue, LIU Zhu, LONG Lu, . Epidemiology and viral genomic characteristics of COVID-19 clustering epidemics of in Chengdu city[J]. Chinese Journal of Public Health, 2022, 38(6): 752-757. DOI: 10.11847/zgggws1136549
Citation: CHENG Yue, LIU Zhu, LONG Lu, . Epidemiology and viral genomic characteristics of COVID-19 clustering epidemics of in Chengdu city[J]. Chinese Journal of Public Health, 2022, 38(6): 752-757. DOI: 10.11847/zgggws1136549

成都市新冠肺炎聚集性疫情流行病学与病原基因特征

Epidemiology and viral genomic characteristics of COVID-19 clustering epidemics of in Chengdu city

  • 摘要:
      目的   分析新冠肺炎聚集性疫情流行病学及病毒基因序列特征,探讨可能影响聚集性疫情发生发展的危险因素。
      方法  对四川省成都市2020年1 — 2月新冠肺炎聚集性疫情特征进行流行病学分析。用实时荧光RT-PCR方法检测标本中的新型冠状病毒(SARS-CoV-2)核酸,用NGS测序技术测定病原基因序列,分析病毒基因型别和变异特征。
      结果  成都市2020年1 — 2月共发生24起聚集性疫情,共75例病例。发生在农村的每起疫情病例数多于城镇。79.17 %(19/24)的首发病例具有成都以外旅居史,病毒传播类型主要为家庭传播(22/24)。发病后未就医、及时就医和作为密接隔离的病例其发病到核酸检测阳性的平均间隔时间依次缩短,分别为7.67、5.54和2.05 d(P < 0.0001)。包含无自觉症状患者的疫情病例数(平均4.25例)多于不包含无自觉症状患者的疫情(平均2.56例)(P < 0.05)。首发病例标本的病毒核酸检测ORF1ab基因Ct值 < 续发病例(P < 0.05)。病毒基因型主要为B.1.1、B和A型。突变位点集中在ORF1ab区,刺突糖蛋白区(S),核衣壳蛋白区(N)3个区域,突变集中的基因区域在各起疫情间无显著差异。
      结论  城乡差异,人员流动性,家庭聚集,不及时就医是聚集性疫情发生的危险因素,潜伏期病例和无症状感染者对疫情规模有重要影响。在疫情研判时,须结合流行病学和病毒基因序列特征分析,有助于阐明聚集性疫情的源头和传播特征。

     

    Abstract:
      Objective  To 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.
      Methods  The 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.
      Results  Totally 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.
      Conclusion  For 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.

     

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