Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios

doi:10.1007/s11684-020-0787-4

Front. Med.

2020, Vol. 14

Issue (5) : 613-622 https://doi.org/10.1007/s11684-020-0787-4

RESEARCH ARTICLE

Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios

Chen Xu¹, Yinqiao Dong², Xiaoyue Yu¹, Huwen Wang¹, Lhakpa Tsamlag¹, Shuxian Zhang¹, Ruijie Chang¹, Zezhou Wang³, Yuelin Yu¹, Rusi Long¹, Ying Wang¹, Gang Xu¹, Tian Shen¹, Suping Wang¹, Xinxin Zhang⁴(

), Hui Wang¹(

), Yong Cai¹(

)

¹. School of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
². Department of Environmental and Occupational Health, School of Public Health, China Medical University, Shenyang 110122, China
³. Department of Cancer Prevention, Shanghai Cancer Center, Fudan University; Department of Oncology, Shanghai Medical College, Fudan University, Shanghai 200025, China
⁴. Research Laboratory of Clinical Virology, National Research Center for Translational Medicine (Shanghai), Ruijin Hospital and Ruijin Hospital North Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China

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Abstract

The coronavirus disease 2019 (COVID-19) has become a life-threatening pandemic. The epidemic trends in different countries vary considerably due to different policy-making and resources mobilization. We calculated basic reproduction number (R₀) and the time-varying estimate of the effective reproductive number (R_t) of COVID-19 by using the maximum likelihood method and the sequential Bayesian method, respectively. European and North American countries possessed higher R₀ and unsteady R_t fluctuations, whereas some heavily affected Asian countries showed relatively low R₀ and declining R_t now. The numbers of patients in Africa and Latin America are still low, but the potential risk of huge outbreaks cannot be ignored. Three scenarios were then simulated, generating distinct outcomes by using SEIR (susceptible, exposed, infectious, and removed) model. First, evidence-based prompt responses yield lower transmission rate followed by decreasing R_t. Second, implementation of effective control policies at a relatively late stage, in spite of huge casualties at early phase, can still achieve containment and mitigation. Third, wisely taking advantage of the time-window for developing countries in Africa and Latin America to adopt adequate measures can save more people’s life. Our mathematical modeling provides evidence for international communities to develop sound design of containment and mitigation policies for COVID-19.

Keywords reproduction number SEIR model COVID-19 estimate

Corresponding Author(s): Xinxin Zhang,Hui Wang,Yong Cai

Just Accepted Date: 06 April 2020 Online First Date: 27 May 2020 Issue Date: 12 October 2020

Cite this article:

Chen Xu,Yinqiao Dong,Xiaoyue Yu, et al. Estimation of reproduction numbers of COVID-19 in typical countries and epidemic trends under different prevention and control scenarios[J]. Front. Med., 2020, 14(5): 613-622.

URL:

https://academic.hep.com.cn/fmd/EN/10.1007/s11684-020-0787-4
https://academic.hep.com.cn/fmd/EN/Y2020/V14/I5/613

Fig.1 Estimation of basic reproduction numbers of COVID-19 epidemic in 12 typical countries. The maximum likelihood method was used to estimate the values of basic reproduction number (R₀) of COVID-19 in 12 mainly affected countries from different continents. The dots and vertical bars represent the value of R₀ and 95% confidence interval, respectively.

Fig.2 Time-varying estimations of the effective reproduction number in selected European and North American countries. The sequential Bayesian method was used to calculate time-varying estimations of the effective reproduction number (R_t) in Italy, France, Spain, Germany, the UK, and United States of America. Light gray ribbon means 95% confidence interval. The dotted line indicates the target value of 1 for the effective reproduction number required for control.

Fig.3 Time-varying estimations of the effective reproduction number in selected Asian, African, and Latin American countries. The sequential Bayesian method was used to calculate time-varying estimations of the effective reproduction number (R_t) in Japan, Republic of Korea, Islamic Republic of Iran, South Africa, Algeria, and Argentina. Light gray ribbon means 95% confidence interval. The dotted line indicates the target value of 1 for the effective reproduction number required for control.

Fig.4 Estimated epidemic trend of COVID-19 under scenario 1. Different colors were used to distinguish the trends of estimated and confirmed cases as well as different stages of estimated tendency divided by the values of basic reproduction number (R₀) and effective reproduction number (R_e). The highest number of infections would be 2412 on April 20, 2020 in our simulated model.

Fig.5 Estimated epidemic trend of COVID-19 under scenario 2. Different colors were used to distinguish the trends of estimated and confirmed cases as well as different stages of estimated tendency divided by the values of basic reproduction number (R₀) and effective reproduction number (R_e). The highest number of infections would be 209 517 on April 27, 2020 in our simulated model.

Fig.6 Estimated epidemic trend of COVID-19 under scenario 3. The estimated number of infections will keep rising as time goes by with unchangeable basic reproduction number (R₀) in both country A1 and country A2. The number of infections would reach 16 307 and 71 770 in country A1 and country A2, respectively by May 31, 2020.

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