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Makale Tam Makale Uluslararası 2022

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

Sezer Uguz, Mete Yağanoğlu, Barış Özyer, Gülşah Tümüklü Özyer, Gül Tokdemir

CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE Cilt 34 · Sayı 6 · 01.03.2022
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Özet

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.

Anahtar kelimeler

COVID-19 ARIMA Coronavirus Visualization forecasting method visual data analysis

Sürdürülebilir Kalkınma Amaçları

  • SKA 3: Sağlıklı Bireyler
  • SKA 16: Barış, Adalet ve Güçlü Kurumlar

Atıf için künye

Uguz, S., Yağanoğlu, M., Özyer, B., Tümüklü Özyer, G., & Tokdemir, G. (2022). The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach. CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE, 34(6). https://doi.org/10.1002/cpe.6774

BibTeX
@article{uguz2022-177197,
  author = {Uguz, Sezer and Yağanoğlu, Mete and Özyer, Barış and Tümüklü Özyer, Gülşah and Tokdemir, Gül},
  title = {The effect of population and tourism factors on Covid-19 cases in Italy: Visual data analysis and forecasting approach},
  journal = {CONCURRENCY AND COMPUTATION-PRACTICE & EXPERIENCE},
  year = {2022},
  volume = {34},
  number = {6},
  issn = {1532-0626},
  doi = {10.1002/cpe.6774},
  url = {https://akademik.atauni.edu.tr/yayinlar/177197-the-effect-of-population-and-tourism-factors-on-covid-19-cases-in-italy-visual}
}