Journal of Shandong University (Health Sciences) ›› 2020, Vol. 58 ›› Issue (10): 38-43.doi: 10.6040/j.issn.1671-7554.0.2020.0642

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Epidemic dynamics of COVID-19 in Xinyang City, Henan Province

LI Chunyu1, ZHU Yuchen1, QI Chang1, LIU Lili1, ZHANG Dandan1, WANG Xu1, XU Xueli2, LI Xiujun1   

  1. 1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. Xinyang Pingqiao District Center for Disease Control and Prevention, Xinyang 464100, Henan, China
  • Published:2020-10-08

Abstract: Objective To explore epidemic dynamics of coronavirus disease 2019(COVID-19)in Xinyang City so as to provide scientific basis for optimizing the prevention and control strategies and evaluating the effects of intervention. Methods The epidemic data of official report was collected. The date of infection was determined to estimate the incubation period. At the same time, the infectious disease dynamic model of SEIR was constructed to analyze the development of disease and the dynamic changes of epidemic situations when the time of implementing prevention and control policies was changed. Results A total of 274 cases were reported in Xinyang City, with the incidence rate of 3.72 out of 100 000. The median incubation period was 6.00(4.00, 7.25)days. Model analysis showed that the basic reproductive number(R0)was 2.86 and the effective reproductive number decreased to 0.29 after the prevention and control measures were taken. If prevention and control measures were taken three days in advance, the number of cases would reduce by 50.5%, while three days later, the number of cases would double. Conclusion The epidemic spread rapidly in Xinyang City, but was quickly controlled under the strong prevention and control measures of the state.

Key words: Coronavirus disease 2019, Epidemic feature, Dynamic model of infectious disease, Basic reproductive number, Prevention and control strategy

CLC Number: 

  • R183
[1] Chen N, Zhou M, Dong X. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study[J]. Lancet, 2020, 6736(20): 1-7.
[2] 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.
[3] WHO.Coronavirus disease(COVID-19)global epidemiological situation [EB/OL].(2020-08-24)[2020-08-26]. https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200824-weekly-epi-update.pdf?sfvrsn=806986d1_4.
[4] Zhao S, Zhuang Z, Ran J, et al. The association between domestic train transportation and novel coronavirus outbreak in China, from 2019 to 2020: a data-driven correlational report[J]. Travel Med Infect Dis, 2020, 33: 101568. doi: 10.1016/j.tmaid.2020.101568.
[5] 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]. Lancet, 2020, 6736(20): 1-9.
[6] 河南省统计局. 河南省统计年鉴2019[EB/OL].(2020-01-21)[2020-05-14]. http://oss.henan.gov.cn/sbgt-wztipt/attachment/hntjj/hntj/lib/tjnj/2019/zk/indexch.htm.
[7] Uttley L, Carroll C, Wong R, et al. Creutzfeldt-Jakob disease: a systematic review of global incidence, prevalence, infectivity, and incubation[J]. Lancet Infect Dis, 2020, 20(1): e2-e10. doi: 10.1016/S1473-3099(19)30615-2.
[8] Armenian HK, Lilienfeld AM. Incubation period of disease[J]. Epidemiol Rev, 1983, 5(1): 1-15.
[9] 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.
[10] Backer JA, Klinkenberg D, Wallinga J. Incubation period of 2019 novel coronavirus(2019-NCoV)infections among travelers from Wuhan, China, 20-28 January 2020[J]. Euro Surveill, 2020, 25(5): 2000062. doi: 10.2807/1560-7917.ES.2020.25.5.2000062.
[11] Li Q, Guan X, Wu P, et al. Earlytransmission dynamics in Wuhan, China, of novel coronavirus-infected pneumonia[J]. N Engl J Med, 2020, 382(13): 1199-1207.
[12] Li R, Pei S, Chen B, et al. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus(SARS-CoV2)[J]. Science, 2020, 368(6490): 489-493.
[13] 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.
[14] 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.
[15] 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[J]. Lancet Infect Dis, 2020, 3099(20): 1-10.
[16] Yu P, Zhu J, Zhang Z, et al. A familial cluster of infection associated with the 2019 Novel Coronavirus indicating possible person-to-person transmission during the incubation period[J]. J Infect Dis, 2020, 221(11):1757-1761.
[17] Zou L, Ruan F, Huang M, et al. SARS-CoV-2 viral load in upper respiratory specimens of infected patients[J]. N Engl J Med, 2020, 382(12): 1177-1179.
[18] Pung R, Chiew CJ, Young BE, et al. Investigation of rhree clusters of COVID-19 in singapore: implications for surveillance and response measures[J]. Lancet, 2020, 19(20): 1-8.
[19] Riou J, Althaus CL. Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus(2019-NCoV), December 2019 to January 2020[J]. Euro Surveill, 2020, 25(4): 2000058. doi: 10.2807/1560-7917.ES.2020.25.4.2000058.
[20] Du Z, Wang L, Cauchemez S, et al. Risk for transportation of 2019 novel coronavirus disease from Wuhan to other cities in China[J]. Emerg Infect Dis, 2020, 26(5): 1049-1052.
[21] Ionides EL, Bretó C, King AA. Inference for nonlinear dynamical systems[J]. Proc Natl Acad Sci U S A, 2006, 103(49): 18438-18443.
[22] King AA, Ionides EL, Pascual M, et al. Inapparent infections and cholera dynamics[J]. Nature, 2008, 454(7206): 877-880.
[23] Pei S, Morone F, Liljeros F, et al. Inference and control of the nosocomial transmission of methicillin-resistant Staphylococcus aureus[J]. Elife, 2018, 7: e40977. doi: 10.7554/eLife.40977.
[24] He D, Ionides EL, King AA. Plug-and-play inference for disease dynamics: measles in large and small populations as a case study[J]. J R Soc Interface, 2010, 7(43): 271-283.
[25] Diekmann O, Heesterbeek JAP, Metz JAJ. On the definition and the computation of the basic reproduction ratio R0 in models for infectious diseases in heterogeneous populations[J]. J Math Biol, 1990, 28(4): 365-382.
[26] 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.
[27] Tian S, Hu N, Lou J, et al. Characteristics of COVID-19 infection in Beijing[J]. J Infect, 2020, 80(4): 401-406.
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