tetano
Editor, Senior Moderator
Transbound Emerg Dis
. 2020 May 26.
doi: 10.1111/tbed.13647. Online ahead of print.
Estimating the Serial Interval of the Novel Coronavirus Disease (COVID-19) Based on the Public Surveillance Data in Shenzhen, China From January 19 to February 22, 2020
Kai Wang[SUP] 1 [/SUP], Shi Zhao[SUP] 2 3 [/SUP], Ying Liao[SUP] 4 [/SUP], Tiantian Zhao[SUP] 4 [/SUP], Xiaoyan Wang[SUP] 4 [/SUP], Xueliang Zhang[SUP] 1 [/SUP], Haiyan Jiao[SUP] 4 [/SUP], Huling Li[SUP] 4 [/SUP], Yi Yin[SUP] 1 [/SUP], Maggie H Wang[SUP] 2 3 [/SUP], Li Xiao[SUP] 5 [/SUP], Lei Wang[SUP] 1 [/SUP], Daihai He[SUP] 6 [/SUP]
Affiliations
Abstract
Backgrounds: The novel coronavirus disease (COVID-19) poses serious threat to global public health and economics. Serial interval (SI), time between the symptom onsets of a primary case and a second case, is a key epidemiological parameter. We estimated SI of COVID-19 in Shenzhen, China based on 27 records of transmission chains.
Methods: We adopted three parametric models: Weibull, Lognormal and Gamma distributions and an interval censored likelihood framework. The three models were compared using the corrected Akaike information criterion (AICc). We also fitted the epidemic curve of COVID-19 to the exponential growth to estimate the reproduction number.
Findings: Using a Weibull distribution, we estimated mean SI at 5.9 days (95%CI: 3.9-9.6) and a standard deviation (SD) at 4.8 days (95%CI: 3.1-10.1). Using a logistic growth model, we estimated the basic reproduction number in Shenzhen at 2.6 (95%CI: 2.4-2.8).
Conclusion: The SI of COVID-19 is relative shorter than that of SARS and MERS, other two beta coronavirus diseases, which suggests the iteration of the transmission was rapid. It is crucial to isolate close contacts promptly to control the spread of COVID-19 effectively.
Keywords: COVID-19; Shenzhen; basic reproduction number; coronavirus disease; outbreak; serial interval.
This article is protected by copyright. All rights reserved.
. 2020 May 26.
doi: 10.1111/tbed.13647. Online ahead of print.
Estimating the Serial Interval of the Novel Coronavirus Disease (COVID-19) Based on the Public Surveillance Data in Shenzhen, China From January 19 to February 22, 2020
Kai Wang[SUP] 1 [/SUP], Shi Zhao[SUP] 2 3 [/SUP], Ying Liao[SUP] 4 [/SUP], Tiantian Zhao[SUP] 4 [/SUP], Xiaoyan Wang[SUP] 4 [/SUP], Xueliang Zhang[SUP] 1 [/SUP], Haiyan Jiao[SUP] 4 [/SUP], Huling Li[SUP] 4 [/SUP], Yi Yin[SUP] 1 [/SUP], Maggie H Wang[SUP] 2 3 [/SUP], Li Xiao[SUP] 5 [/SUP], Lei Wang[SUP] 1 [/SUP], Daihai He[SUP] 6 [/SUP]
Affiliations
- PMID: 32452648
- DOI: 10.1111/tbed.13647
Abstract
Backgrounds: The novel coronavirus disease (COVID-19) poses serious threat to global public health and economics. Serial interval (SI), time between the symptom onsets of a primary case and a second case, is a key epidemiological parameter. We estimated SI of COVID-19 in Shenzhen, China based on 27 records of transmission chains.
Methods: We adopted three parametric models: Weibull, Lognormal and Gamma distributions and an interval censored likelihood framework. The three models were compared using the corrected Akaike information criterion (AICc). We also fitted the epidemic curve of COVID-19 to the exponential growth to estimate the reproduction number.
Findings: Using a Weibull distribution, we estimated mean SI at 5.9 days (95%CI: 3.9-9.6) and a standard deviation (SD) at 4.8 days (95%CI: 3.1-10.1). Using a logistic growth model, we estimated the basic reproduction number in Shenzhen at 2.6 (95%CI: 2.4-2.8).
Conclusion: The SI of COVID-19 is relative shorter than that of SARS and MERS, other two beta coronavirus diseases, which suggests the iteration of the transmission was rapid. It is crucial to isolate close contacts promptly to control the spread of COVID-19 effectively.
Keywords: COVID-19; Shenzhen; basic reproduction number; coronavirus disease; outbreak; serial interval.
This article is protected by copyright. All rights reserved.