Analyzing the Еffects of Мobility and Season on COVID-19 Cases Using Negative Binomial Regression: A European Case Study

Authors:	Janković, Radmila Amelio, Alessia Ćosović, Marijana
Affiliations:	Computer Science Mathematical Institute of the Serbian Academy of Sciences and Arts
Title:	Analyzing the Еffects of Мobility and Season on COVID-19 Cases Using Negative Binomial Regression: A European Case Study
Journal:	Proceedings of the 20th International Symposium INFOTEH-JAHORINA, INFOTEH 2021
First page:	Art. no. 9400665
Conference:	20th International Symposium INFOTEH-JAHORINA, INFOTEH 2021; East Sarajevo; Bosnia and Herzegovina; 17 March 2021 through 19 March 2021
Issue Date:	17-Mar-2021
Rank:	M33
ISBN:	978-172818229-2
DOI:	10.1109/INFOTEH51037.2021.9400665
Abstract:	This paper develops a Generalized Linear Model using the Negative Binomial Regression with log link function to analyze the effects of mobility trends and seasons on COVID-19 cases. The data of four European countries was used, namely Austria, Greece, Italy, and Czech Republic. The dataset includes daily observations of registered COVID-19 cases, and the data of six types of mobility trends: retail and recreation, grocery and pharmacy, parks, transit stations, workplaces, and residential mobility for the period Feb 15 - Nov 15, 2020. The results suggest that the number of COVID-19 cases differs between seasons and different mobility trends.
Keywords:	COVID-19 \| mobility trends \| negative binomial regression \| seasons \| statistical analysis
Publisher:	IEEE

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