Bilgilendirme: Kurulum ve veri kapsamındaki çalışmalar devam etmektedir. Göstereceğiniz anlayış için teşekkür ederiz.
 

The Effect of Population and Tourism Factors on Covid-19 Cases in Italy: Visual Data Analysis and Forecasting Approach

Loading...
Publication Logo

Date

2022

Journal Title

Journal ISSN

Volume Title

Publisher

Wiley

Open Access Color

BRONZE

Green Open Access

No

OpenAIRE Downloads

OpenAIRE Views

Publicly Funded

No
Impulse
Average
Influence
Average
Popularity
Average

Research Projects

Journal Issue

Abstract

At the beginning of 2020, the new coronavirus disease (Covid-19), a deadly viral illness, is declared as a public health emergency situation by WHO. Consequently, it is accepted as pandemic that affected millions of people worldwide. Italy is one of the most affected countries by Covid-19 disease among the world. In this article, our main goal is to investigate the effect of intensity of Covid-19 cases based on the population size and tourism factors in certain regions of Italy by visual data analysis. The regions of Lombardia, Veneto, Campania, Emilia-Romagna, Piemonte are the top five regions covering 58.50% of the total Covid-19 cases diagnosed in Italy. It has been shown by visual data analysis that population and tourism factors play an important role in the spread of Covid-19 cases in these five regions. In addition, a prediction model was created using Bi-LSTM and ARIMA algorithms to forecast the number of Covid-19 cases occurring in these five regions in order to take early action. We can conclude that these northern regions have been affected mostly by Covid-19 and the distribution of the resident population and tourist flow factors affected the number of Covid-19 cases in Italy.

Description

Yaganoglu, Mete/0000-0003-3045-169X; Ozyer, Baris/0000-0003-0117-6983; Tokdemir, Gul/0000-0003-2441-3056; Uguz, Sezer/0000-0001-6492-2846

Keywords

Coronavirus, Covid-19, Forecasting Method, Visual Data Analysis

Fields of Science

03 medical and health sciences, 0302 clinical medicine, 0101 mathematics, 01 natural sciences

Citation

Uğuz, Sezer...et.al. (2022). "The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach", Concurrency and Computation: Practice and Experience, Vol.34, No.6.

WoS Q

Q3

Scopus Q

Q2
OpenCitations Logo
OpenCitations Citation Count
1

Source

Concurrency and Computation: Practice and Experience

Volume

34

Issue

6

Start Page

End Page

PlumX Metrics
Citations

Scopus : 0

Captures

Mendeley Readers : 8

Web of Science™ Citations

2

checked on Feb 24, 2026

Page Views

4

checked on Feb 24, 2026

Google Scholar Logo
Google Scholar™
OpenAlex Logo
OpenAlex FWCI
0.1817345

Sustainable Development Goals

SDG data is not available