[Course of disease and related epidemiological parameters of COVID-19: a prospective study based on contact tracing cohort].
Zhonghua Yu Fang Yi Xue Za Zhi
; 56(4): 474-478, 2022 Apr 06.
Article
in Chinese
| MEDLINE | ID: covidwho-1834947
ABSTRACT
Objective:
To analyze the course of disease and epidemiological parameters of COVID-19 and provide evidence for making prevention and control strategies.Methods:
To display the distribution of course of disease of the infectors who had close contacts with COVID-19 cases from January 1 to March 15, 2020 in Guangdong Provincial, the models of Lognormal, Weibull and gamma distribution were applied. A descriptive analysis was conducted on the basic characteristics and epidemiological parameters of course of disease.Results:
In total, 515 of 11 580 close contacts were infected, with an attack rate about 4.4%, including 449 confirmed cases and 66 asymptomatic cases. Lognormal distribution was fitting best for latent period, incubation period, pre-symptomatic infection period of confirmed cases and infection period of asymptomatic cases; Gamma distribution was fitting best for infectious period and clinical symptom period of confirmed cases; Weibull distribution was fitting best for latent period of asymptomatic cases. The latent period, incubation period, pre-symptomatic infection period, infectious period and clinical symptoms period of confirmed cases were 4.50 (95%CI3.86-5.13) days, 5.12 (95%CI4.63-5.62) days, 0.87 (95%CI0.67-1.07) days, 11.89 (95%CI9.81-13.98) days and 22.00 (95%CI21.24-22.77) days, respectively. The latent period and infectious period of asymptomatic cases were 8.88 (95%CI6.89-10.86) days and 6.18 (95%CI1.89-10.47) days, respectively.Conclusion:
The estimated course of COVID-19 and related epidemiological parameters are similar to the existing data.
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Contact Tracing
/
COVID-19
Type of study:
Cohort study
/
Observational study
/
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Zhonghua Yu Fang Yi Xue Za Zhi
Year:
2022
Document Type:
Article
Affiliation country:
Cma.j.cn112150-20220107-00025
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