Шляхи подолання асиметричної інформації під час побудови точних моделей пандемій

Abstract

The article substantiates the objective need to improve the existing models for predicting pandemic models, identifies the main factors for solving asymmetry problems. A relationship was revealed between the level of concern, the number of Internet requests on the Internet and non-compliance with quarantine restrictions. The authors have proven the danger of uncoordinated and unhurried actions on the historical example of a pandemic called "Spanish flu". For a general understanding of the topic, the action of the mechanism of artificial neural networks is schematically reflected, a model for predicting the SIR epidemic is built. The practical significance of the work lies in the fact that more accurate models for predicting the course of pandemics can save millions of lives and provide stable systems for the economic, social and political life of the population. Overcoming the incompleteness and inaccuracies of information will allow the leaders of states to avoid mistakes when making important decisions. Further research in the chosen topic will make it possible to obtain accurate data on the course of epidemics, and in the future, will help to overcome the problem of information asymmetry.