Dynamics of local epidemic COVID-19 outbreak through the prism of compartment modeling
V.F. Obesnyuk
The Southern Urals Biophysics Institute of the RF Federal Medical and Biological Agency, 19 Ozerskoe drive, Ozersk, 456780, Russian Federation
Our research goal was to tentatively assess necessary volumes and quality of statistic description necessary for describing coronavirus epidemic outbreak. We took COVID-19 epidemics development in Hubei (China) as an example and showed that an existing system of descriptive epidemiologic concepts based on lethality, mortality and the basic reproduction number can turn out to be insufficient for full-fledged description of an epidemic and prediction of its outcomes. The said province was chosen as an object for analysis at a period when the outbreak was just starting; during that period activities aimed at epidemiologic investigations and coercive limitations of contacts between people didn’t yet yield expected results.
Data and methods. We revealed that more qualitative statistic description given for infectious processes in a population could be gained with a relatively simple and well-known compartment-model; deviations of actual epidemiologic observations from its parameters can be interpreted as being purely stochastic ones.
Results. To improve prediction abilities, it is necessary to abandon a conventional epidemiologic approach as it is based on a mixture of effects produced by two completely different biological factors in one or two combined parameters. It is advisable to separately describe a process of epidemic spread and a retrospect relation between risks of death and risk factors spread among an infected part of a population over a period of epidemic.
Unsatisfactory insight into a mechanism of infection development in a population and absence of control over its dynamics can impede efforts aimed at suppressing it. A model of an epidemic process can be applied when individual medical insurance schemes are developed and utilized capacities of infectious hospitals and observators are predicted.
- V Kazakhstane nachali strakhovat' ot koronavirusa [Medical insurance against coronavirus is now being provided in Kazakhstan]. Forbes. Available at: https://forbes.kz/finances/insurance/v_kazahstane_nachali_strahovat_ot_k... (25.02.2020).
- Unterrichtung durch die Bundesregierung «Bericht zur Risikoanalyse im Bevölkerungsschutz 2012. Pandemie durch Virus Modi-SARS». Berlin, Deutscher Bundestag Publ., 2012, 88 p.
- Menachery V.D., Yount B.L., Debbink K. A SARS-like cluster of circulating bat coronaviruses shows potential for human emergence. Nature medicine, 2015, vol. 21, no. 12, pp. 1508–1514. DOI: 10.1038/nm.3985
- Wei-jie G., Ni Z., Hu Y., Liang W.-H., Ou C.-Q., He J.-X. [et al.]. Clinical characteristics of 2019 novel coronavirus infection in China. Preprint Med Rxiv, 2020. Available at: https://www.medrxiv.org/content/10.1101/2020.02.06.20020974v1.article-me... (25.02.2020).
- Wang W., Xu Y., Gao R., Lu R., Han K., Wu G., Tan W. Detection of SARS-CoV-2 in different types of clinical specimens. JAMA, 2020, vol. 11, no. 323 (18), pp. 1843‒1844. DOI: 10.1001/jama.2020.3786
- Rothe C., Schunk M., Sothmann P., Bretzel G., Froeschl G., Wallrauch C., Zimmer T., Thiel V., Janke C. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. The New England Journal of Medicine, 2020, vol. 382, pp. 970–971. DOI: 10.1056/NEJMc2001468
- Bai Y., Yao L., Wei T., Tian F., Jin D.-Y., Chen L., Wang M. Presumed asymptomatic carrier transmission of COVID-19. JAMA, 2020, vol. 21, no. 323 (14), pp. 1406‒1407. DOI: 10.1001/jama.2020.2565
- Wu C., Chen X., Cai Y., Xia J., Zhou X., Xu S., Huang H., Zhang L. [et al.]. Risk Factors Associated With Acute Respiratory Distress Syndrome and Death in Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China. JAMA, 2020, vol. 13, pp. E1‒E10. DOI: 10.1001/jamainternmed.2020.0994
- Informatsionnoe agentstvo «Sin'khua» [Xinhua News Agency]. Available at: http://russian.news.cn/ (25.02.2020).
- Sharfstein J.M., Becker S.J., Mello M.M. Diagnostic Testing for the Novel Coronavirus. JAMA, 2020, no. 9, pp. E1‒E2. DOI: 10.1001/jama.2020.3864
- Kermack W.O., McKendrick A.G. Contribution to Mathematical Theory of epidemics-1927. Bull Math Biol, 1991, vol. 53, no. 1‒2, pp. 33‒55. DOI: 10.1007/BF02464423
- Lekone P.E., Finkenstädt B.F. Statistical Inference in a Stochastic Epidemic SEIR Model with Control Intervention: Ebola as a Case Study. Biometrics, 2006, vol. 62, no. 4, pp. 1170–1177. DOI: 10.1111/j.1541-0420.2006.00609.x
- Brauer F., Castillo–Chavez C., Feng Zh. Mathematical models in epidemiology. New-York, Springer Publ., 2019, 619 p.
- Coronavirus disease (COVID-19) outbreak. World Health Organization. Available at: https://www.who.int/emergencies/diseases/novel-coronavirus-2019 (25.02.2020).
- Tracking the epidemic. China CDC Weekly. Available at: http://weekly.chinacdc.cn/news/TrackingtheEpidemic.htm (29.02.2020).
- Li Q., Guan X., Wu P., Wang X., Zhou L., Tong Y., Ren R., Leung K.S.M. [et al.]. Early Transmission Dynamics in Wuhan, China, of Novel Coronavirus-Infected Pneumonia. The New England journal of medicine, 2020, no. 26, pp. 1–9. DOI: 10.1056/NEJMoa2001316
- Read J.M., Bridgen J.R.E., Cummings D.A.T., Ho A., Jewell C.P. Novel coronavirus 2019-nCoV: early estimation of epidemiological parameters and epidemic predictions. Med Rxiv, 2020, no. 28, pp. 1–11. DOI: 10.1101/2020.01.23.20018549
- Iznanka. Epidemiolog [Inside. Epidemiologist]. Radio «Ekho Moskvy». Available at: https://echo.msk.ru/programs/iznanka/2581122-echo/ (29.02.2020).