Applying Agent Model for Analysis and Forecasting of Epizootic Manifestations in Computer-Generated Simulation of a Natural Plague Focus

The aim of the study was to develop an agent-based model of the epizootic process based on the analysis of the interaction between the pathogen and its hosts at the population level in order to improve methods for predicting the spread of plague. Materials and methods . An analysis of the course of plague epizootics has been carried out, the main assumptions and simplifications of the model are formulated. The structure of a multi-level tree-like system of goals has been built and their coordination with the functions that ensure the achievement of goals provided. The types of agents, their number and characteristics, the mechanism of interaction with each other and with the external environment have been determined. Results and discussion . The experience of using the simulation model to analyze and predict epizootic manifestations in natural plague foci indicates its practical value for solving problems related to risk management arising from this infection. Simulation models allow us to take into account complex interactions between various factors and assess the impact of various intervention strategies on the development of the situation. An important advantage of agentbased modeling is the ability to reproduce the heterogeneity of the host population and take into account the individual characteristics of their behavior and susceptibility to infection. Simulation is a promising tool for improving the system of epidemiological surveillance and plague control. The developed model can be used to make informed managerial decisions aimed at reducing the risk of disease in the population. Further research will be aimed at expanding the model by including additional factors (for example, climatic and social ones) and adapting it for use in specific natural plague foci. The model can be scaled and applied not only to local outbreaks of plague, but also to simulate the spread of infection in wider areas.