BARRIERS OF COVID-19 VACCINATION IN UKRAINE DURING THE WAR: THE SIMULATION STUDY USING ARIMA MODEL

The COVID-19 pandemic has become a challenge to public health systems worldwide. As of June 2022, more than 545 million cases have been registered worldwide, more than 6.34 million of which have died. The gratui-tous and bloody war launched by Russia in Ukraine has affected the public health system, including disruptions to COVID-19 vaccination plans. The use of simulation models to estimate the necessary coverage of COVID-19 vaccination in Ukraine will make it possible to rapidly change the policy to combat the pandemic in the wartime. This study aims to develop a COVID-19 vaccination model in Ukraine and to study the impact of war on this process. The study is multidisciplinary and includes a sociological study of the attitude of the population of Ukraine toward COVID-19 vaccination before the escalation of the war, the modeling of the vaccine campaign, forecasting the required number of doses administered after the start of the war, epidemiological analysis of the simulation results. This research targeted the COVID-19 epidemic process during the war. The research sub-jects are the methods and models of epidemic process simulation based on statistical machine learning. Socio-logical analysis methods were applied to achieve this goal, and an ARIMA model was developed to assess COVID-19 vaccination coverage As a result of the study, the population of Ukraine was clustered in attitude to COVID-19 vaccination. As a result of a sociological study of 437 donors and 797 medical workers, four classes were distinguished: supporters, loyalists, conformists, and skeptics. An ARIMA model was built to simulate the daily coverage of COVID-19 vaccinations. A retrospective forecast verified the model's accuracy for the period 01/25/22 - 02/23/22 in Ukraine. The forecast accuracy for 30 days was 98.79%. The model was applied to esti-mate the required vaccination coverage in Ukraine for the period 02/24/22 – 03/25/22. Conclusions. A multi-disciplinary study made it possible to assess the adherence of the population of Ukraine to COVID-19 vaccina-tion and develop an ARIMA model to assess the necessary COVID-19 vaccination coverage in Ukraine. The model developed is highly accurate and can be used by public health agencies to adjust vaccine policies in wartime. Given the barriers to vaccination acceptance, despite the hostilities, it is necessary to continue to per-form awareness-raising work in the media, covering not only the events of the war but also setting the population on the need to receive the first and second doses of the COVID-19 vaccine for previously unvaccinated people, and a booster dose for those who have previously received two doses of the vaccine, involving opinion leaders in such works © Dmytro Chumachenko, Tetyana Chumachenko, Nataliia Kirinovych, Ievgen Meniailov, Olena Muradyan, Olga Salun, 2022

Forecasting of COVID-19 Epidemic Process by Lasso Regression

The coronavirus epidemic has changed the life of the whole world. Containment of the further development of the pandemic requires the implementation of effective evidencebased control measures. For this, it is advisable to use mathematical modeling. The most accurate predictions are shown by machine learning methods. The article discusses a lasso regression model for predicting the dynamics of a new coronavirus in Ukraine, Great Britain, Germany and Japan. The model shows high accuracy. The disadvantage of this approach is the impossibility of identifying the factors influencing the dynamics of morbidity. © 2021 UkrMiCo 2021 - 2021 IEEE International Conference on Information and Telecommunication Technologies and Radio Electronics, Proceedings. All rights reserved.

Toward Reference Architecture of Control System Socio-Epidemic Processes of Emergent Infections

The pandemic of COVID-19 showed the humanity is vulnerable to threats of epidemic emergent infections. Hence, the challenge of creating a safety system of the population from these threats at territory, national and international levels. The challenge poses a problem in the area of ICT consisting of that developing principles and techniques for engineering flexible decision-making systems. The paper presents a vision of an approach to solving the problem

The concept of decisions support system to mitigate the COVID-19 pandemic consequences based on social and epidemic processes intelligent analysis

The study is aimed at interdisciplinary analysis of social barriers and barriers to overcoming the consequences of epidemics and the development of programs for sociological support of anti-epidemic measures in the context of the COVID-19 pandemic. The goal is to solve the problem of increasing the biosafety of the population as a component of national security through the formation of directions and tools for preparatory work with the public conscience with use of social attitude investigation to ensure the effectiveness of vaccination and minimize the negative non-medical consequences of various measures to combat the COVID-19 pandemic. The concept of comprehensive methodology for analyzing the crisis behavior of the masses with a combination of sociological and mathematical methods has been developed. It is planned to obtain scientifically substantiated information on the social factors of the spread of the virus, the social effects of a sense of hopelessness, social barriers to vaccination and the role of social networks in these processes;a practical task for the project is the development of models of crisis mass behavior and a system of targeted measures for managing the social atmosphere during a prolonged pandemic with uncertain prospects for an exit. It is expected to receive a concept of sociological support for pandemic measures to determine the optimal strategies of media, information and educational and socio-political influence on the state of mass consciousness in the context of the COVID-19 pandemic. © 2021 CEUR-WS. All rights reserved.