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

Gyeongseung Han; Jeewon Han; Seungmin Han; Hyunkyung Jeong

doi:doi:10.11648/j.ajtas.20211001.11

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

Gyeongseung Han, Jeewon Han, Seungmin Han, Hyunkyung Jeong

Published in American Journal of Theoretical and Applied Statistics (Volume 10, Issue 1)

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), 2024. Published by Science Publishing Group

Keywords

COVID-19, Disease, Analysis, Prediction

References

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[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.
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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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TY  - JOUR
T1  - Analyzing the Impact of COVID 19 on Global Trends and Predicting Future Cases
AU  - Gyeongseung Han
AU  - Jeewon Han
AU  - Seungmin Han
AU  - Hyunkyung Jeong
Y1  - 2021/01/12
PY  - 2021
N1  - https://doi.org/10.11648/j.ajtas.20211001.11
DO  - 10.11648/j.ajtas.20211001.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
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EP  - 8
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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.
VL  - 10
IS  - 1
ER  -

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Author Information

Gyeongseung Han

Chadwick International, Incheon, South Korea
Jeewon Han

Cranbrook Kingswood Upper School, Bloomfield Hills, MI, United States
Seungmin Han

Korean Minjok Leadership Academy, Hoengseong, South Korea
Hyunkyung Jeong

Chadwick International, Incheon, South Korea

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Plain Text BibTeX RIS

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

Copy | Download

@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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TY  - JOUR
T1  - Analyzing the Impact of COVID 19 on Global Trends and Predicting Future Cases
AU  - Gyeongseung Han
AU  - Jeewon Han
AU  - Seungmin Han
AU  - Hyunkyung Jeong
Y1  - 2021/01/12
PY  - 2021
N1  - https://doi.org/10.11648/j.ajtas.20211001.11
DO  - 10.11648/j.ajtas.20211001.11
T2  - American Journal of Theoretical and Applied Statistics
JF  - American Journal of Theoretical and Applied Statistics
JO  - American Journal of Theoretical and Applied Statistics
SP  - 1
EP  - 8
PB  - Science Publishing Group
SN  - 2326-9006
UR  - https://doi.org/10.11648/j.ajtas.20211001.11
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.
VL  - 10
IS  - 1
ER  -

Copy | Download