Analyzing the Еffects of Мobility and Season on COVID-19 Cases Using Negative Binomial Regression: A European Case Study
Int. Symp. INFOTEH-JAHORINA, INFOTEH - Proc.
; 2021.
Article
in English
| Scopus | ID: covidwho-1214736
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. © 2021 IEEE.
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Case report
Language:
English
Journal:
Int. Symp. INFOTEH-JAHORINA, INFOTEH - Proc.
Year:
2021
Document Type:
Article
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