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
2020 Analiz Riska Zdorovʹû  
Our research goal was to tentatively assess necessary volumes and quality of statistic description necessary for describing coronavirus epidemic outbreak. We took 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
more » ... 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.
doi:10.21668/health.risk/2020.2.09.eng fatcat:jjvi5ysqbbdd5ovfmih4zsybyu