Dynamic estimation of epidemiological parameters of COVID-19 outbreak and effects of interventions on its spread
Background: A key challenge in estimating epidemiological parameters for a pandemic such as the initial COVID-19 outbreak in Wuhan is the discrepancy between the officially reported number of infections and the true number of infections. A common approach to tackling the challenge is to use the number of infections exported from the originating city to infer the true number. This approach can only provide a static estimate of the epidemiological parameters before city lockdown because there are almost no exported cases thereafter.
Methods: We propose a Bayesian estimation method that dynamically estimates the epidemiological parameters by recovering true numbers of infections from day-to-day official numbers. To illustrate the use of this method, we provide a comprehensive retrospection on how the COVID-19 had progressed in Wuhan from January 19 to March 5, 2020. Particularly, we estimate that the outbreak sizes by January 23 and March 5 were 11,239 [95% CI 4,794–22,372] and 124,506 [95% CI 69,526–265,113], respectively.
Results: The effective reproduction number attained its maximum on January 24 (3.42 [95% CI 3.34–3.50]) and became less than 1 from February 7 (0.76 [95% CI 0.65–0.92]). We also estimate the effects of two major government interventions on the spread of COVID-19 in Wuhan.
Conclusions: This case study by our proposed method affirms the believed importance and effectiveness of imposing tight non-essential travel restrictions and affirm the importance and effectiveness of government interventions (e.g., transportation suspension and large scale hospitalization) for effective mitigation of COVID-19 community spread.
Li Q, Guan X, Wu P, et al. Early transmission dynamics in Wuhan, China, of novel coronavirus–infected pneumonia. N Engl J Med 2020;382:1199-207. DOI: https://doi.org/10.1056/NEJMoa2001316
Hellewell J, Abbott S, Gimma A, et al. Feasibility of controlling COVID-19 outbreaks by isolation of cases and contacts. Lancet Global Health 2020;8:e488-96. DOI: https://doi.org/10.1016/S2214-109X(20)30074-7
Cao Z, Zhang Q, Lu X, , et al. Incorporating human movement data to improve epidemiological estimates for 2019-nCoV. medRxiv 2020.02.07.20021071. DOI: https://doi.org/10.1101/2020.02.07.20021071
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. Lancet 2020;395:689–97. DOI: https://doi.org/10.1016/S0140-6736(20)30260-9
Read M, Bridgen JR, Cummings DA, et al. Novel coronavirus 2019- nCoV: Early estimation of epidemiological parameters and epidemic predictions. medRxiv 2020.01.23.20018549. DOI: https://doi.org/10.1101/2020.01.23.20018549
Chinazzi M, Davis JT, Ajelli M, et al. The effect of travel restrictions on the spread of the 2019 novel coronavirus (COVID-19) outbreak. Science 2020;386:395-400. DOI: https://doi.org/10.1126/science.aba9757
Zhao S, Lin Q, Ran J, et al. Preliminary estimation of the basic reproduction number of novel coronavirus (2019-nCoV) in China, from 2019 to 2020: A data-driven analysis in the early phase of the outbreak. Int J Infect Dis 2020;92:214-17. DOI: https://doi.org/10.1016/j.ijid.2020.01.050
Riou CL. Althaus, Pattern of early human-to-human transmission of Wuhan 2019 novel coronavirus (2019-nCoV), December 2019 to January 2020. Euro Surveill 2020;25:2000058. DOI: https://doi.org/10.2807/1560-7917.ES.2020.25.4.2000058
Li R, Pei S, Chen B, et al. Substantial undocumented infection facilitates the rapid dissemination of novel coronavirus (SARS-CoV2). Science 2020;368:489-93. DOI: https://doi.org/10.1126/science.abb3221
Washington Post [Internet]. Travel ban goes into effect in Chinese city of Wuhan as authorities try to stop coronavirus spread. 22 January 2020. Available from: https://www.washingtonpost.com/world/asia_pacific/nine-dead-as-chinese-coronavirus-spreads-despite-efforts-to-contain-it/2020/01/22/1eaade72-3c6d-11ea-afe2-090eb37b60b1_story.html
Liang H, Wu h. Parameter estimation for differential equation models using a frame- work of measurement error in regression models. J Am Stat Assoc 2008;103:1570-83. DOI: https://doi.org/10.1198/016214508000000797
Wang J, Liang H, Chen R. A state space model approach for HIV infection dynamics. J Time Ser Anal 2012;33:841-9. DOI: https://doi.org/10.1111/j.1467-9892.2012.00784.x
Hall P, Ma Y. Quick and easy one-step parameter estimation in differential equations. J R Stat Soc Series B Stat Methodol 2014;76:735-48. DOI: https://doi.org/10.1111/rssb.12040
Chang D, Xu H, Rebaza A, et al. Protecting health-care workers from subclinical coronavirus infection. Lancet Respir Med 2020;8:e13. DOI: https://doi.org/10.1016/S2213-2600(20)30066-7
Hethcote H, Zhien M, Shengbing L. Effects of quarantine in six endemic models for infectious diseases. Math Biosci 2002;180:141-60. DOI: https://doi.org/10.1016/S0025-5564(02)00111-6
Diekmann O, Heesterbeek H, Britton T. Mathematical tools for understanding infectious disease dynamics. Vol 7. Princeton University Press; 2012. DOI: https://doi.org/10.1515/9781400845620
Hethcote HW. The mathematics of infectious diseases. SIAM Review 2000;42:599-653. DOI: https://doi.org/10.1137/S0036144500371907
Chowell G, Hyman JM, Bettencourt LM, Castillo-Chavez C. Mathematical and statistical estimation approaches in epidemiology. Cham. Springer; 2009. DOI: https://doi.org/10.1007/978-90-481-2313-1
Sun K, Chen J, Viboud C. Early epidemiological analysis of the coronavirus disease 2019 outbreak based on crowdsourced data: A population-level observational study. Lancet Digital Health 2020;2:E201-8. DOI: https://doi.org/10.1016/S2589-7500(20)30026-1
World Health Organization. Report of the WHO-China joint mission on coronavirus disease 2019 (covid-19). 2020. Available from: https://www.who.int/docs/default-source/coronaviruse/who-china-joint-mission-on-covid-19-final-report.pdf
Geyer CJ, Thompson EA. Constrained Monte Carlo maximum likelihood for dependent data, J R Stat Soc Series B Stat Methodol 1992;54:657-83. DOI: https://doi.org/10.1111/j.2517-6161.1992.tb01443.x
Imai N, Dorigatti I, Cori A, et al. Report 2: Estimating the potential total number of novel Coronavirus cases in Wuhan City, China. Imperial College London 2020. Available from: https://www.imperial.ac.uk/mrc-global-infectious-disease-analysis/covid-19/report-2-update-case-estimates-covid-19/
Xinhua News [Internet]. With more than 11 million residents, Wuhan has become an attractive city. 26 March 2019. Available from: http://m.xinhuanet.com/hb/2019-03/26/c_1124281764.htm
China News [Internet]. There are 9 million people remain in Wuhan after the city lock-down. Every cell of them is fighting for defeating covid-19. 30 January 2020. Available from: https://china. huanqiu.com/article/9CaKrnKp7io
Xinhua Net [Internet]. Detecting novel coronavirus with fire eye. 6 February 2020. Available from: http://www.xinhuanet.com/2020-02/06/c_1125537855.htm
Changjiang Daily [Internet]. Wuhan’s transportation network: High speed railway connects to more than 100 cities, and the transportation volume of Wuhan metro accounts for 45% of daily residents travel. 27 October 2019. Available from: https://wh.leju.com/news/2019-10-27/ 07046593995599123889479.shtml
Wuhan Metro [Internet]. Detailed statistics of Wuhan metro (2019). Available from: https://iwuhan.org/ webapps/WuhanMetro/
Ma Z, Zhou Y, Wu J. Modeling and dynamics of infectious diseases. Vol.11. World Scientific Publishing; 2009.
Xinhua Net [Internet]. All 16 temporary hospitals in Wuhan closed. 10 March 2020. Available from:http://www. xinhuanet.com/english/2020-03/10/c_138863160.htm
Hubei Daily [Internet]. Wuhan speeds up the hospitalization for COVID-19 patients, and the number of available beds in hospitals is greatly increased (15 February 2020). Available from: https://m.chinanews.com/wap/detail/zw/gn/2020/02-15/9092013.shtml
Huang C, Wang Y, Li X, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet 2020;395:497-506. DOI: https://doi.org/10.1016/S0140-6736(20)30183-5
Edwards E. ‘A Slow Burn’: Coronavirus symptoms often linger before worsening. NBC News. 21 Mar 2020. Available from: https://www.nbcnews.com/health/health-news/slow-burn-coronavirus-symptoms-often-linger-worsening-n1164756
Chen N, Zhou M, Dong X, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: A descriptive study. Lancet 2020;395:507-13. DOI: https://doi.org/10.1016/S0140-6736(20)30211-7
Guan W, Ni Z, Hu Y, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med 2020;382:1708-20. DOI: https://doi.org/10.1056/NEJMoa2002032
Wu JT, Leung K, Bushman M, et al. Estimating clinical severity of COVID-19 from the transmission dynamics in Wuhan, China. Nat Med 2020;26:506-10. DOI: https://doi.org/10.1038/s41591-020-0822-7
- Abstract views: 166
- PDF: 103
- HTML: 0
Copyright (c) 2021 The Author(s)
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.