Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (10): 32-37.doi: 10.6040/j.issn.1671-7554.0.2020.0683

Previous Articles     Next Articles

Reproduction number estimation and epidemic analysis of coronavirus disease 2019 in Shandong Province based on Poisson process

ZHU Yuchen1, LI Chunyu1, QI Chang1, WANG Ying1, LIU Lili1, ZHANG Dandan1, WANG Xu1, KANG Dianmin2, LI Xiujun1   

  1. 1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Shandong Center for Disease Control and Prevention, Jinan 250014, Shandong, China
  • Published:2020-10-08

PDF (PC)

546

Abstract: Objective To explore the epidemic dynamics of coronavirus disease 2019(COVID-19)in Shandong Province, and to provide a scientific basis for the future prevention and control of new outbreaks of COVID-19 and other emerging infectious diseases. Methods After collecting the information of 559 confirmed cases with COVID-19 reported by the Shandong Provincial Health Commission and determining the infection date of the cases, a propagation model was established based on the Poisson process and the basic reproduction number and instantaneous reproduction number were calculated during the COVID-19 epidemic in Shandong Province. The results obtained by calculating the instantaneous reproduction numbers based on sequential Bayesian and time-dependent methods were compared. Results The difference between the date of onset of a confirmed case and the date when it was reported generally followed the Weibull distribution. When the COVID-19 outbreak started in Shandong Province, the basic reproduction number(R0)was 2.64(95%CI:1.37-4.51), and the instantaneous reproduction number showed a gradually downward trend with time. Three calculation methods all showed the same trend. Conclusion After the intervention of prevention and control measures, the local epidemic of COVID-19 in Shandong Province has basically ended, but the constant vigilance is necessary in order to prevent the second outbreak of the epidemic.

Key words: Coronavirus pneumonia disease 2019, Basic reproductive number, Instantaneous reproduction number, Poisson process, Bayesian inference

CLC Number: 

  • R183
[1] Guan WJ, Ni ZY, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China[J]. N Engl J Med, 2020, 382(18): 1708-1720.
[2] 中国疾病预防控制中心新型冠状病毒肺炎应急响应机制流行病学组. 新型冠状病毒肺炎流行病学特征分析[J]. 中华流行病学杂志, 2020, 41(2): 145-151. Team TNCPERE. The epidemiological characteristics of an outbreak of 2019 novel coronavirus diseases(COVID-19)in China[J]. Chinese Journal of Epidemiology, 2020, 41(2): 145-151.
[3] 中华预防医学会新型冠状病毒肺炎防控专家组. 关于疫情应急处置阶段转入流行高峰持续防控阶段对策的思考 [J]. 中华流行病学杂志, 2020, 41(3): 297-300. Special Expert Group for Control of the Epidemic of Novel Coronavirus Pneumonia of the Chinese Preventive Medicine. Consideration on the strategies during epidemic stage changing from emergency response to continuous prevention and control[J].Chinese Journal of Epidemiology, 2020, 41(3): 297-300.
[4] 周生余,王春亭,张伟,等. 山东省新型冠状病毒肺炎患者537例临床特征与救治效果[J]. 山东大学学报(医学版), 2020, 58(3): 44-51. ZHOU Shengyu, WANG Chunting, ZHANG Wei, et al. Clinical characteristics and treatment effect of 537 cases of novel coronavirus pneumonia in Shandong Province[J]. Journal of Shandong University(Health Sciences), 2020, 58(3): 44-51.
[5] Tu W, Tang H, Chen F, et al. Epidemic update and risk assessment of 2019 novel coronavirus — China, January 28, 2020[J]. CCDCW, 2020, 2(6): 83-86.
[6] 山东省卫生健康委员会. 2020年3月11日0时至12时山东省新型冠状病毒肺炎疫情情况[EB/OL].(2020-03-11)[2020-04-24]. http://wsjkw.shandong.gov.cn/ztzl/rdzt/qlzhfkgz/tzgg/202003/t20200311_3046408.html.
[7] Su Y, Gelman A, Yajima M. Multiple imputation with diagnostics(mi)in R: opening windows into the black box[J]. J Stat Softw, 2011, 45(2): 1-31.
[8] Buuren S, Groothuis-Oudshoorn K. Mice: multivariate imputation by chained equations in R[J]. J Stat Softw, 2011, 45(3): 1-67.
[9] Honaker J, King G, Blackwell M. Amelia II: a program for missing data[J]. J Stat Softw, 2011, 45(7): 1-47.
[10] Dye C. Infectious diseases of humans: dynamics and control by R.M. Anderson and R.M. May[J]. Trends in Ecology & Evolution, 1991, 6(10): 340-341.
[11] Lipsitch M, Cohen T, Cooper B, et al. Transmission dynamics and control of severe acute respiratory syndrome[J]. Science, 2003, 300(5627): 1966-1970.
[12] White LF, Pagano M. A likelihood-based method for real-time estimation of the serial interval and reproductive number of an epidemic[J].Stat Med, 2008, 27(16): 2999-3016.
[13] Cori A, Ferguson NM, Fraser C, et al. A new framework and software to estimate time-varying reproduction numbers during epidemics[J].Am J Epidemiol, 2013, 178(9): 1505-1512.
[14] Nishiura H, Linton NM, Akhmetzhanov AR. Serial interval of novel coronavirus(COVID-19)infections [J]. Int J Infect Dis, 2020, 93: 284-286. doi:10.1016/j.ijid.2020.02.060.
[15] Du Z, Xu X, Wu Y, et al. Serial interval of COVID-19 among publicly reported confirmed cases[J]. Emerg Infect Dis, 2020, 26(6): 1341-1343.
[16] Bettencourt LMA, Ribeiro RM. Real time Bayesian estimation of the epidemic potential of emerging infectious diseases[J]. PLoS One, 2008, 3(5): e2185. doi: 10.1371/journal.pone.0002185.
[17] Wallinga J, Teunis P. Different epidemic curves for severe acute respiratory syndrome reveal similar impacts of control measures[J]. Am J Epidemiol, 2004, 160(6): 509-516.
[18] Mahase E. China coronavirus: what do we know so far? [J]. BMJ, 2020, 368: m308. doi: 10.1136/bmj.m308.
[19] Wu JT, Leung K, Leung GM. Nowcasting and forecasting the potential domestic and international spread of the 2019-nCoV outbreak originating in Wuhan, China: a modelling study[J].The Lancet, 2020, 395(10225): 689-697.
[20] Backer JA, Klinkenberg D, Wallinga J. Incubation period of 2019 novel coronavirus(2019-nCoV)infections among travellers from Wuhan, China, 20-28 January 2020[J]. Euro Surveill, 2020, 25(5): 2000062. doi: 10.2807/1560-7917.ES.2020.25.5.2000062.
[21] Lauer SA, Grantz KH, Bi Q, et al. The incubation period of coronavirus disease 2019(COVID-19)from publicly reported confirmed cases: estimation and application[J].Ann Intern Med, 2020, 172(9): 577-582.
[22] Ki M, Task Force for 2019-nCoV. Epidemiologic characteristics of early cases with 2019 novel coronavirus(2019-nCoV)disease in Korea [J].Epidemiol Health, 2020, 42: e2020007. doi: 10.4178/epih.e2020007.
[23] Linton NM, Kobayashi T, Yang Y, et al. Incubation period and other epidemiological characteristics of 2019 novel coronavirus infections with right truncation: a statistical analysis of publicly available case data[J]. J Clin Med, 2020, 9(2): 538. doi: 10.3390/jcm9020538.
[24] 高文静, 李立明. 新型冠状病毒肺炎潜伏期或隐性感染者传播研究进展[J]. 中华流行病学杂志, 2020, 41(4): 485-488. GAO Wenjing, LI Liming. Advances on presymptomatic or asymptomatic carrier transmission of COVID-19[J].Chinese Journal of Epidemiology, 2020, 41(4): 485-488.
[25] Lessler J, Reich NG, Cummings DAT, et al. Outbreak of 2009 pandemic influenza A(H1N1)at a New York City school[J]. N Engl J Med, 2009, 361(27): 2628-2636.
[26] Cauchemez S, Boëlle PY, Thomas G, et al. Estimating in real time the efficacy of measures to control emerging communicable diseases[J]. Am J Epidemiol, 2006, 164(6): 591-597.
[27] Cauchemez S, Bhattarai A, Marchbanks TL, et al. Role of social networks in shaping disease transmission during a community outbreak of 2009 H1N1 pandemic influenza[J]. Proc Natl Acad Sci U S A, 2011, 108(7): 2825-2830.
[1] LI Chunyu, ZHU Yuchen, QI Chang, LIU Lili, ZHANG Dandan, WANG Xu, XU Xueli, LI Xiujun. Epidemic dynamics of COVID-19 in Xinyang City, Henan Province [J]. Journal of Shandong University (Health Sciences), 2020, 58(10): 38-43.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
No Suggested Reading articles found!
Copyright 2018 © Editorial office of Journal of Shandong University (Health Sciences)
Supported by Beijing Magtech Co.Ltd