Recommendation Rules Mining for Reducing the Spread of COVID-19 Cases Vitaliy Yakovyna a,b , Natalya Shakhovska b , Khrystyna Shakhovska b and Jaime Campos c a University of Warmia and Mazury in Olsztyn, 2 Michała Oczapowskiego str., Olsztyn, 10-719, Poland b Lviv Polytechnic National University, 12 Bandera str., Lviv, 79013, Ukraine c Linnaeus University, PG Vejdes 6 & 7, Växjö, SE-35195, Sweden Abstract The COVID-19 pandemic is having an unprecedented impact on society and the economy, affecting virtually every aspect of people's daily life and all sectors of the economy. In this situation, society and the health care system need help from modern technologies such as Artificial Intelligence, Big Data, and Machine Learning, which intended to help governments to choose and implement an adequate strategy to combat the spread of the disease by balancing between human safety and the constraints of social and economic life. This paper considers the recommendation rules extracted from the novel ensemble of machine learning methods such as regression tree and clustering. The merged Oxford COVID-19 Government Response Tracker and European Centre for Disease Prevention and Control Covid-19 Cases datasets have been used with the data ranged from January 01 to October 04, 2020. The conclusions and findings of the study could be helpful for decision making on appropriated state policy for reducing the spread of new Covid-19 cases. Keywords 1 COVID-19, Machine Learning, Regression Tree, Clustering, Prediction 1. Introduction A new species of coronavirus (COVID-19) was first discovered in late 2019 in Wuhan, China and has since spread almost worldwide. Currently, the total number of reports of the spread of this viral disease covers 215 countries and territories [1]. Due to the rapid spread of cases, their wide territorial coverage and potentially serious consequences that threaten human life, the World Health Organization has declared the spread of COVID-19 a pandemic [2]. As of October 26, 2020, 43,694,475 confirmed cases of infection were identified, which led to 1,162,999 deaths [1]. The pandemic is having an unprecedented impact on society and the economy, affecting virtually every aspect of people's daily life and all sectors of the economy. According to some estimates, about 4 billion people, or about half the world's population, suffer from severe restrictions on mobility and restrictions on social communications. The COVID-19 pandemic has triggered a global economic crisis that is different from the global economic crises of previous decades and may have more severe and lasting consequences. Epidemiological constraints have led to significant changes in people's daily lives, their habits, social and economic ties, methods and forms of communication, production processes, and social and political life. Due to such a significant impact on day-to-day people's lives and the world economy, the most important issues of concern to society and governments include: (i) when the spread of COVID-19 will reach its maximum, both at national and worldwide scales; (ii) how long the pandemic will last; IDDM’2020: 3rd International Conference on Informatics & Data-Driven Medicine, November 19–21, 2020, Växjö, Sweden EMAIL: yakovyna@matman.uwm.edu.pl (V. Yakovyna); nataliya.b.shakhovska@lpnu.ua (N. Shakhovska); kristin.shakhovska@gmail.com (K. Shakhovska); jaime.campos@lnu.se (J. Campos) ORCID: 0000-0003-0133-8591 (V. Yakovyna); 0000-0002-6875-8534 (N. Shakhovska); 0000-0002-9914-229X (K. Shakhovska); 0000- 0001-7048-8089 (J. Campos) © 2020 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0). CEUR Workshop Proceedings (CEUR-WS.org)