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Natural history and cycle threshold values analysis of COVID-19 in Xiamen City, China

OBJECTIVE: This study elaborated the natural history parameters of Delta variant, explored the differences in detection cycle thresholds (Ct) among cases. METHODS: Natural history parameters were calculated based on the different onset time and exposure time of the cases. Intergenerational relations...

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Detalles Bibliográficos
Autores principales: Deng, Bin, Liu, Weikang, Guo, Zhinan, Luo, Li, Yang, Tianlong, Huang, Jiefeng, Abudunaibi, Buasiyamu, Zhang, Yidun, Ouyang, Xue, Wang, Demeng, Su, Chenghao, Chen, Tianmu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9361627/
https://www.ncbi.nlm.nih.gov/pubmed/35968394
http://dx.doi.org/10.1016/j.idm.2022.07.007
Descripción
Sumario:OBJECTIVE: This study elaborated the natural history parameters of Delta variant, explored the differences in detection cycle thresholds (Ct) among cases. METHODS: 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. RESULTS: 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. CONCLUSION: 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.