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Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study.
Lancet Infect Dis. 2020 07; 20(7):793-802.LI

Abstract

BACKGROUND

The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy.

METHODS

We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level.

FINDINGS

We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33-56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0-14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0-9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8-12·4) and the mean serial interval at 5·1 days (1·3-11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74-1·54) in Shenzhen city of Guangdong province and 1·71 (1·32-2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30.

INTERPRETATION

Our estimates of the incubation period and serial interval were similar, suggesting an early peak of infectiousness, with possible transmission before the onset of symptoms. Our results also indicate that, as the epidemic progressed, infectious individuals were isolated more quickly, thus shortening the window of transmission in the community. Overall, our findings indicate that strict containment measures, movement restrictions, and increased awareness of the population might have contributed to interrupt local transmission of SARS-CoV-2 outside Hubei province.

FUNDING

National Science Fund for Distinguished Young Scholars, National Institute of General Medical Sciences, and European Commission Horizon 2020.

Authors+Show Affiliations

School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.ISI Foundation, Turin, Italy.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China.Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.Department of Biostatistics, College of Public Health, Health Professions, and Emerging Pathogens Institute, University of Florida, Gainesville, FL, USA.Vaccine and Infectious Disease Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA; Department of Biostatistics, University of Washington, Seattle, WA, USA.WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China.WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, Li Ka Shing Faculty of Medicine, University of Hong Kong, Hong Kong Special Administrative Region, China.Bruno Kessler Foundation, Trento, Italy.Division of International Epidemiology and Population Studies, Fogarty International Center, National Institutes of Health, Bethesda, MD, USA.ISI Foundation, Turin, Italy; Laboratory for the Modeling of Biological and Socio-technical Systems, Northeastern University, Boston, MA USA.Bruno Kessler Foundation, Trento, Italy. Electronic address: marco.ajelli@gmail.com.School of Public Health, Fudan University, Key Laboratory of Public Health Safety, Ministry of Education, Shanghai, China. Electronic address: yhj@fudan.edu.cn.

Pub Type(s)

Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

Language

eng

PubMed ID

32247326

Citation

Zhang, Juanjuan, et al. "Evolving Epidemiology and Transmission Dynamics of Coronavirus Disease 2019 Outside Hubei Province, China: a Descriptive and Modelling Study." The Lancet. Infectious Diseases, vol. 20, no. 7, 2020, pp. 793-802.
Zhang J, Litvinova M, Wang W, et al. Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study. Lancet Infect Dis. 2020;20(7):793-802.
Zhang, J., Litvinova, M., Wang, W., Wang, Y., Deng, X., Chen, X., Li, M., Zheng, W., Yi, L., Chen, X., Wu, Q., Liang, Y., Wang, X., Yang, J., Sun, K., Longini, I. M., Halloran, M. E., Wu, P., Cowling, B. J., ... Yu, H. (2020). Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study. The Lancet. Infectious Diseases, 20(7), 793-802. https://doi.org/10.1016/S1473-3099(20)30230-9
Zhang J, et al. Evolving Epidemiology and Transmission Dynamics of Coronavirus Disease 2019 Outside Hubei Province, China: a Descriptive and Modelling Study. Lancet Infect Dis. 2020;20(7):793-802. PubMed PMID: 32247326.
* Article titles in AMA citation format should be in sentence-case
TY - JOUR T1 - Evolving epidemiology and transmission dynamics of coronavirus disease 2019 outside Hubei province, China: a descriptive and modelling study. AU - Zhang,Juanjuan, AU - Litvinova,Maria, AU - Wang,Wei, AU - Wang,Yan, AU - Deng,Xiaowei, AU - Chen,Xinghui, AU - Li,Mei, AU - Zheng,Wen, AU - Yi,Lan, AU - Chen,Xinhua, AU - Wu,Qianhui, AU - Liang,Yuxia, AU - Wang,Xiling, AU - Yang,Juan, AU - Sun,Kaiyuan, AU - Longini,Ira M,Jr AU - Halloran,M Elizabeth, AU - Wu,Peng, AU - Cowling,Benjamin J, AU - Merler,Stefano, AU - Viboud,Cecile, AU - Vespignani,Alessandro, AU - Ajelli,Marco, AU - Yu,Hongjie, Y1 - 2020/04/02/ PY - 2020/02/21/received PY - 2020/03/13/revised PY - 2020/03/13/accepted PY - 2020/4/6/pubmed PY - 2020/7/11/medline PY - 2020/4/6/entrez SP - 793 EP - 802 JF - The Lancet. Infectious diseases JO - Lancet Infect Dis VL - 20 IS - 7 N2 - BACKGROUND: The coronavirus disease 2019 (COVID-19) epidemic, caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), began in Wuhan city, Hubei province, in December, 2019, and has spread throughout China. Understanding the evolving epidemiology and transmission dynamics of the outbreak beyond Hubei would provide timely information to guide intervention policy. METHODS: We collected individual information from official public sources on laboratory-confirmed cases reported outside Hubei in mainland China for the period of Jan 19 to Feb 17, 2020. We used the date of the fourth revision of the case definition (Jan 27) to divide the epidemic into two time periods (Dec 24 to Jan 27, and Jan 28 to Feb 17) as the date of symptom onset. We estimated trends in the demographic characteristics of cases and key time-to-event intervals. We used a Bayesian approach to estimate the dynamics of the net reproduction number (Rt) at the provincial level. FINDINGS: We collected data on 8579 cases from 30 provinces. The median age of cases was 44 years (33-56), with an increasing proportion of cases in younger age groups and in elderly people (ie, aged >64 years) as the epidemic progressed. The mean time from symptom onset to hospital admission decreased from 4·4 days (95% CI 0·0-14·0) for the period of Dec 24 to Jan 27, to 2·6 days (0·0-9·0) for the period of Jan 28 to Feb 17. The mean incubation period for the entire period was estimated at 5·2 days (1·8-12·4) and the mean serial interval at 5·1 days (1·3-11·6). The epidemic dynamics in provinces outside Hubei were highly variable but consistently included a mixture of case importations and local transmission. We estimated that the epidemic was self-sustained for less than 3 weeks, with mean Rt reaching peaks between 1·08 (95% CI 0·74-1·54) in Shenzhen city of Guangdong province and 1·71 (1·32-2·17) in Shandong province. In all the locations for which we had sufficient data coverage of Rt, Rt was estimated to be below the epidemic threshold (ie, <1) after Jan 30. INTERPRETATION: Our estimates of the incubation period and serial interval were similar, suggesting an early peak of infectiousness, with possible transmission before the onset of symptoms. Our results also indicate that, as the epidemic progressed, infectious individuals were isolated more quickly, thus shortening the window of transmission in the community. Overall, our findings indicate that strict containment measures, movement restrictions, and increased awareness of the population might have contributed to interrupt local transmission of SARS-CoV-2 outside Hubei province. FUNDING: National Science Fund for Distinguished Young Scholars, National Institute of General Medical Sciences, and European Commission Horizon 2020. SN - 1474-4457 UR - https://www.unboundmedicine.com/medline/citation/32247326/Evolving_epidemiology_and_transmission_dynamics_of_coronavirus_disease_2019_outside_Hubei_province_China:_a_descriptive_and_modelling_study_ DB - PRIME DP - Unbound Medicine ER -