Assessment of the effectiveness of restrictive epidemic control measures using original models of cellular automaton

Abstract

Background. The ongoing COVID-19 pandemic, the human casualties caused by it, and the possibility of new epidemical threats make the search for effective countermeasures actual. One of the most effective tools, as the experience of the COVID-19 pandemic has shown, is restrictive measures of various types, which are especially significant with medical countermeasures being unavailable or insufficient. At the same time, the topic of restrictive measures and their mathematical modeling, especially given its importance, is not sufficiently disclosed in the scientific literature.The aim. To determine the possibility of assessing the effectiveness of restrictive epidemic control measures using original models of cellular automaton with intercellular boundaries.Methods. To determine the impact of restrictive measures on the dynamics of the daily increase in infected people, an original cellular automaton with intercellular boundaries was developed, which makes it possible to simulate epidemic control measures of varying stringency. In the simulations carried out using the Monte Carlo method with subsequent statistical processing, we studied the impact of restrictive measures of varying stringency on the number of infected people, the duration of the epidemic, and the quality of forecasting. The final series of experiments simulated the spread of the COVID-19 virus in Germany in the first half of 2020.The results show that even a simple cellular automaton model with boundaries successfully describes the course of the epidemic and allows us to assess the effectiveness of restrictive measures. The dependence of the daily increase in infected people on the stringency of measures is presented; it is shown what characteristics of the population can influence this dependence. It was found that the measures of medium stringency (40–50 % according to the Stringency Index) have the least predictable effect; they can cause both rapid localization of the focus and the spread of the epidemic to a large part of the population. Weak and strong measures give a more predictable effect.Conclusion. Cellular automaton models with intercellular boundaries have great potential for modeling the impact of restrictive measures on the course of an epidemic, making it possible to predict the dynamics of infected people based on the population data and the restrictive measures being introduced.