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Analyzing the Impact of COVID 19 on Global Trends and Predicting Future Cases

Received: 21 November 2020     Accepted: 22 December 2020     Published: 12 January 2021
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Abstract

COVID-19 is a highly contagious, potentially lethal respiratory disease caused by a strain of coronavirus. Utilizing sets of data collected by Johns Hopkins University, this research paper analyzes the global trends of COVID-19 and the pandemic’s effect on the global economy. The aim of this paper is to provide accurate information of COVID-19 through comparing the situation of the world before and after the pandemic. All visual representations have been created using python, a programming language, and each figure is accompanied with a thorough breakdown of its cumulative data. Its analysis shows the impact of COVID-19 globally and regionally. Machine learning is utilized to predict the future trends in the number of cases, from which it can be forecasted that the world will see a continuous increase in COVID-19 cases with an exception of a few countries where cases of COVID-19 have been declining consistently. Polynomial regression has been used to predict the future trend of COVID-19. Observing the numbers used in this paper such as card usage, job posts, and confirmed cases provides evidence to the fact that COVID-19 has negatively impacted the global economy. Statistics can show the relationship between COVID-19 and the global economy, nonetheless providing evidence on why certain events are occuring during this pandemic.

Published in American Journal of Theoretical and Applied Statistics (Volume 10, Issue 1)
DOI 10.11648/j.ajtas.20211001.11
Page(s) 1-8
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2021. Published by Science Publishing Group

Keywords

COVID-19, Disease, Analysis, Prediction

References
[1] Qiu, Y., Chen, X., & Shi, W. (2020). Impacts of Social and Economic Factors on the Transmission of Coronavirus Disease 2019 (COVID-19) in China (Working Paper 494 [pre.]). GLO Discussion Paper.
[2] “Novel Coronavirus (2019-nCoV) situation reports, World Health Organization, October 2020.
[3] Zhu, N., Zhang, D., Wang, W., Li, X., Yang, B., Song, J., Zhao, X., Huang, B., Shi, W., Lu, R., Niu, P., Zhan, F., Ma, X., Wang, D., Xu, W., Wu, G., Gao, G. F., Tan, W., & China Novel Coronavirus Investigating and Research Team. (2020). A Novel Coronavirus from Patients with Pneumonia in China, 2019.
[4] “Outbreak Notification”, National Health Commission (NHC) of the People’s Republic of China. September 20, 2020.
[5] N. Donthu, A. Gutafsson “Effects of COVID-19 on business and research, Journal of Business Research, September 2020.
[6] Nicola, Maria, Zaid Alsafi, Catrin Sohrabi, Ahmed Kerwan, Ahmed Al-Jabir, Christos Iosifidis, Maliha Agha, and Riaz Agha. “The Socio-Economic Implications of the Coronavirus Pandemic (COVID-19): A Review.” International journal of surgery (London, England). IJS Publishing Group Ltd. Published by Elsevier Ltd., April 17, 2020.
[7] Campbell, Charlie, and Alice Park. “Where Did Coronavirus Originate? Inside the Hunt to Find Out.” Time. Time, July 23, 2020.
[8] Abouk, R., & Heydari, B. (2020). The Immediate Effect of COVID-19 Policies on Social Distancing Behavior in the United States. MedRxiv, 2020.04.07.20057356.
[9] Baccini, L., & Brodeur, A. (2020). Explaining Governors’ Response to the Covid-19 Pandemic in the United States (SSRN Scholarly Paper ID 3579229). Social Science Research Network.
[10] Amy Dighe, Lo. Cattar, Steven Riley “Response to COVID-19 in South Korea and implications for lifting stringent interventions”, October 2020.
[11] Shin young Park “Coronavirus Disease Outbreak in Call Center”, Centers for Disease Control and prevention, August 2020.
[12] A. Brodeur, A. Islam, David Gray, and Suraiya Jabeen Bhuiyan “A Literature Review of the Economics of COVID-19”, IZA Institute of Labor Economics, 2020.
[13] Joanne Peng “An Introduction to Logistic Regression Analysis and Reporting”, The Journal of Educational Research, September 2020.
[14] Hsin-Hsiung Huang. “Nonlinear Regression Analysis.” Statistics By Jim, January, 2010.
[15] Tianfeng, Chai. “Root mean square error (RMSE) or mean absolute error (MAE)?” Geoscientific Model Development, June, 2014.
Cite This Article
  • APA Style

    Gyeongseung Han, Jeewon Han, Seungmin Han, Hyunkyung Jeong. (2021). Analyzing the Impact of COVID 19 on Global Trends and Predicting Future Cases. American Journal of Theoretical and Applied Statistics, 10(1), 1-8. https://doi.org/10.11648/j.ajtas.20211001.11

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    ACS Style

    Gyeongseung Han; Jeewon Han; Seungmin Han; Hyunkyung Jeong. Analyzing the Impact of COVID 19 on Global Trends and Predicting Future Cases. Am. J. Theor. Appl. Stat. 2021, 10(1), 1-8. doi: 10.11648/j.ajtas.20211001.11

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    AMA Style

    Gyeongseung Han, Jeewon Han, Seungmin Han, Hyunkyung Jeong. Analyzing the Impact of COVID 19 on Global Trends and Predicting Future Cases. Am J Theor Appl Stat. 2021;10(1):1-8. doi: 10.11648/j.ajtas.20211001.11

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  • @article{10.11648/j.ajtas.20211001.11,
      author = {Gyeongseung Han and Jeewon Han and Seungmin Han and Hyunkyung Jeong},
      title = {Analyzing the Impact of COVID 19 on Global Trends and Predicting Future Cases},
      journal = {American Journal of Theoretical and Applied Statistics},
      volume = {10},
      number = {1},
      pages = {1-8},
      doi = {10.11648/j.ajtas.20211001.11},
      url = {https://doi.org/10.11648/j.ajtas.20211001.11},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajtas.20211001.11},
      abstract = {COVID-19 is a highly contagious, potentially lethal respiratory disease caused by a strain of coronavirus. Utilizing sets of data collected by Johns Hopkins University, this research paper analyzes the global trends of COVID-19 and the pandemic’s effect on the global economy. The aim of this paper is to provide accurate information of COVID-19 through comparing the situation of the world before and after the pandemic. All visual representations have been created using python, a programming language, and each figure is accompanied with a thorough breakdown of its cumulative data. Its analysis shows the impact of COVID-19 globally and regionally. Machine learning is utilized to predict the future trends in the number of cases, from which it can be forecasted that the world will see a continuous increase in COVID-19 cases with an exception of a few countries where cases of COVID-19 have been declining consistently. Polynomial regression has been used to predict the future trend of COVID-19. Observing the numbers used in this paper such as card usage, job posts, and confirmed cases provides evidence to the fact that COVID-19 has negatively impacted the global economy. Statistics can show the relationship between COVID-19 and the global economy, nonetheless providing evidence on why certain events are occuring during this pandemic.},
     year = {2021}
    }
    

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    AB  - COVID-19 is a highly contagious, potentially lethal respiratory disease caused by a strain of coronavirus. Utilizing sets of data collected by Johns Hopkins University, this research paper analyzes the global trends of COVID-19 and the pandemic’s effect on the global economy. The aim of this paper is to provide accurate information of COVID-19 through comparing the situation of the world before and after the pandemic. All visual representations have been created using python, a programming language, and each figure is accompanied with a thorough breakdown of its cumulative data. Its analysis shows the impact of COVID-19 globally and regionally. Machine learning is utilized to predict the future trends in the number of cases, from which it can be forecasted that the world will see a continuous increase in COVID-19 cases with an exception of a few countries where cases of COVID-19 have been declining consistently. Polynomial regression has been used to predict the future trend of COVID-19. Observing the numbers used in this paper such as card usage, job posts, and confirmed cases provides evidence to the fact that COVID-19 has negatively impacted the global economy. Statistics can show the relationship between COVID-19 and the global economy, nonetheless providing evidence on why certain events are occuring during this pandemic.
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Author Information
  • Chadwick International, Incheon, South Korea

  • Cranbrook Kingswood Upper School, Bloomfield Hills, MI, United States

  • Korean Minjok Leadership Academy, Hoengseong, South Korea

  • Chadwick International, Incheon, South Korea

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