The effect of population and tourism factors on Covid‐19 cases in Italy: Visual data analysis and forecasting approach

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 am...

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Bibliographic Details
Published in:Concurrency and Computation: Practice and Experience 2022-03, Vol.34 (6), p.n/a
Main Authors: Uğuz, Sezer, Yağanoğlu, Mete, Özyer, Barış, Özyer, Gülşah Tümüklü, Tokdemir, Gül
Format: Article
Language:English
Subjects:
Algorithms
coronavirus
COVID-19
Data analysis
forecasting method
Population
Prediction models
Public health
Tourism
visual data analysis
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Summary: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.
ISSN:1532-0626
1532-0634
DOI:10.1002/cpe.6774