Deng Bin, Liu Weikang, Guo Zhinan, Luo Li, Yang Tianlong, Huang Jiefeng, Abudunaibi Buasiyamu, Zhang Yidun, Ouyang Xue, Wang Demeng, Su Chenghao, Chen Tianmu
State Key Laboratory of Molecular Vaccinology and Molecular Diagnostics, School of Public Health, Xiamen University, Xiamen City, Fujian Province, People's Republic of China.
Xiamen Center for Disease Control and Prevention, Xiamen City, Fujian Province, People's Republic of China.
Infect Dis Model. 2022 Sep;7(3):486-497. doi: 10.1016/j.idm.2022.07.007. Epub 2022 Aug 9.
This study elaborated the natural history parameters of Delta variant, explored the differences in detection cycle thresholds (Ct) among cases.
Natural history parameters were calculated based on the different onset time and exposure time of the cases. Intergenerational relationships between generations of cases were calculated. Differences in Ct values of cases by gender, age, and mode of detection were analyzed statistically to assess the detoxification capacity of cases.
The median incubation period was 4 days; the detection time for cases decreased from 25 to 7 h as the outbreak continued. The average generation time (GT), time interval between transmission generations (TG) and serial interval (SI) were 3.6 ± 2.6 days, 1.67 ± 2.11 days and 1.7 ± 3.0 days. Among the Ct values, we found little differences in testing across companies, but there were some differences in the gender of detected genes. The Ct values continuous to decreased with age, but increased when the age was greater than 60.
This epidemic was started from aggregation of factories. It is more reasonable to use SI to calculate the effective reproduction number and the time-varying reproduction number. And the analysis of Ct values can improve the positive detection rate and improve prevention and control measures.
本研究阐述了德尔塔变异株的自然史参数,探讨了病例间检测循环阈值(Ct)的差异。
根据病例的不同发病时间和暴露时间计算自然史参数。计算病例代际之间的代际关系。对不同性别、年龄和检测方式的病例Ct值差异进行统计学分析,以评估病例的排毒能力。
中位潜伏期为4天;随着疫情持续,病例的检测时间从25小时缩短至7小时。平均代间距(GT)、传播代间隔时间(TG)和序列间隔(SI)分别为3.6±2.6天、1.67±2.11天和1.7±3.0天。在Ct值方面,我们发现不同公司检测结果差异不大,但检测基因的性别存在一些差异。Ct值随年龄增长持续下降,但在年龄大于60岁时有所上升。
本次疫情始于工厂聚集性发病。使用SI计算有效再生数和时变再生数更为合理。对Ct值的分析可以提高阳性检出率,完善防控措施。