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. 2022 Sep;7(3):486-497.
doi: 10.1016/j.idm.2022.07.007. Epub 2022 Aug 9.

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

Bin Deng  1 , Weikang Liu  1 , Zhinan Guo  2 , Li Luo  1 , Tianlong Yang  1 , Jiefeng Huang  1 , Buasiyamu Abudunaibi  1 , Yidun Zhang  2 , Xue Ouyang  2 , Demeng Wang  2 , Chenghao Su  3 , Tianmu Chen  1
Affiliations

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

Bin Deng et al. Infect Dis Model. 2022 Sep.

Abstract

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.

Keywords: COVID-19; Cycle threshold value; Natural history.

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Conflict of interest statement

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Figures

Fig. 1
Fig. 1
Fitting distribution of incubation period and intergenerational relationship. (A: Fitting distribution of incubation period; B: Fitting distribution of latent period; C: Fitting distribution of series interval; D: Fitting distribution of Transmission generation times; E: Fitting distribution of generation time lower; F: Fitting distribution of generation time uper.).
Fig. 2
Fig. 2
Difference in onset-reporting time of infected persons in different finding methods.
Fig. 3
Fig. 3
Time-dependent graph of the time required for detection.
Fig. 4
Fig. 4
Differences in Ct values of infected persons with different detection methods. (Ct∗: cycle threshold).
Fig. 5
Fig. 5
Differences in Ct values between different testing companies and genotypes. (Ct∗: cycle threshold).
Fig. 6
Fig. 6
Gender differences in Ct values for different testing companies and genotype testing. (Ct∗: cycle threshold).
Fig. 7
Fig. 7
Age-specific differences in Ct values for different testing companies and genotype testing. (Ct∗: cycle threshold).
Fig. 8
Fig. 8
Differences in Ct values detected by two testing companies at different exposure-to-detection durations and onset-to-detection durations. (Ct∗: cycle threshold).
Fig. 9
Fig. 9
Differences of half-vaccination and vaccination in Ct value. (Ct∗: cycle threshold).
Fig. 10
Fig. 10
Differences in Ct values of infected patients with different clinical severity.
See this image and copyright information in PMC

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