Analyzing the Effects of Mobility and Season on COVID-19 Cases Using Negative Binomial Regression: a European Case Study

被引：0

作者：

Jankovic, Radmila ^{[1
]}

Amelio, Alessia

Cosovic, Marijana ^{[2
]}

机构：

[1] Serbian Acad Arts & Sci, Math Inst, Belgrade, Serbia

[2] Univ East Sarajevo, Fac Elect Engn, East Sarajevo, Bosnia & Herceg

来源：

2021 20TH INTERNATIONAL SYMPOSIUM INFOTEH-JAHORINA (INFOTEH) | 2020年

关键词：

negative binomial regression; COVID-19; statistical analysis; mobility trends; seasons;

D O I：

10.1109/INFOTEH51037.2021.9400665

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

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.

引用

页数：6

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