Modeling and analysis of different scenarios for the spread of COVID-19 by using the modified multi-agent systems – Evidence from the selected countries

Abstract

Currently, there is a global pandemic of COVID-19. To assess its prevalence, it is necessary to have adequate models that allow real-time modeling of the impact of various quarantine measures by the state. The SIR model, which is implemented using a multi-agent system based on mobile cellular automata, was improved. The paper suggests ways to improve the rules of the interaction and behavior of agents. Methods of comparing the parameters of the SIR model with real geographical, social and medical indicators have been developed. That allows the modeling of the spatial distribution of COVID-19 as a single location and as the whole country consisting of individual regions that interact with each other by transport, taking into account factors such as public transport, supermarkets, schools, universities, gyms, churches, parks. The developed model also allows us to assess the impact of quarantine, restrictions on transport connections between regions, to take into account such factors as the incubation period, the mask regime, maintaining a safe distance between people, and so on. A number of experiments were conducted in the work, which made it possible to assess both the impact of individual measures to stop the pandemic and their comprehensive application. A method of comparing computer-time and dynamic parameters of the model with real data is proposed, which allowed assessing the effectiveness of the government in stopping the pandemic in the Chernivtsi region, Ukraine. A simulation of the pandemic spread in countries such as Slovakia, Turkey and Serbia was also conducted. The calculations showed the high-accuracy matching of the forecast model with real data.

Scenarios for the Development of Polish Passenger Transport Services in Pandemic Conditions

“…Many tools and methods were used by researchers in these scenarios, including predictions based on the Bayesian model [52,53], SIR models [54,55], an agent-based model and a deterministic compartmental model [56], fractional models [57], and a modified SEIR compartmental model [58].…”

"Fuzzy Multi-Agent Simulation of COVID-19 Pandemic Spreading"

“…Obviously, this classification does not consider comorbidities. We introduced in our model the variants of this virus, delta, which is at least 50% more contagious than the "classic" COVID-19 [22,23]. Therefore, we defined in our MAS simulation a zone of transmissibility.…”

Optimize Data-Driven Multi-Agent Simulation for COVID-19 Transmission

“…Castro et al [13] analyze the spread processes of COVID-19 epidemics in open regions by considering effects from different environments. Vyklyuk et al [14] propose modeling its spread in large regions by simulating a set of autonomous multi-agent systems. Nanna et al [15] extend MAS to dynamically verify influences on diseases spread from government strategies.…”