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The COVID-19 pandemic: prediction study based on machine learning models
COVID-19 was first discovered in Wuhan, China in December 2019. It is one of the worst pandemics in human history. Recent studies reported that COVID-19 is transmitted among humans by droplet infection or direct contact. COVID-19 pandemic has invaded more than 210 countries around the world and as o...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8035887/ https://www.ncbi.nlm.nih.gov/pubmed/33840016 http://dx.doi.org/10.1007/s11356-021-13824-7 |
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author | Malki, Zohair Atlam, El-Sayed Ewis, Ashraf Dagnew, Guesh Ghoneim, Osama A. Mohamed, Abdallah A. Abdel-Daim, Mohamed M. Gad, Ibrahim |
author_facet | Malki, Zohair Atlam, El-Sayed Ewis, Ashraf Dagnew, Guesh Ghoneim, Osama A. Mohamed, Abdallah A. Abdel-Daim, Mohamed M. Gad, Ibrahim |
author_sort | Malki, Zohair |
collection | PubMed |
description | COVID-19 was first discovered in Wuhan, China in December 2019. It is one of the worst pandemics in human history. Recent studies reported that COVID-19 is transmitted among humans by droplet infection or direct contact. COVID-19 pandemic has invaded more than 210 countries around the world and as of February 18(th), 2021, just after a year has passed, a total of 110,533,973 confirmed cases of COVID-19 were reported and its death toll reached about 2,443,091. COVID-19 is a new member of the family of corona viruses, its nature, behaviour, transmission, spread, prevention, and treatment are to be investigated. Generally, a huge amount of data is accumulating regarding the COVID-19 pandemic, which makes hot research topics for machine learning researchers. However, the panicked world’s population is asking when the COVID-19 will be over? This study considered machine learning approaches to predict the spread of the COVID-19 in many countries. The experimental results of the proposed model showed that the overall R2 is 0.99 from the perspective of confirmed cases. A machine learning model has been developed to predict the estimation of the spread of the COVID-19 infection in many countries and the expected period after which the virus can be stopped. Globally, our results forecasted that the COVID-19 infections will greatly decline during the first week of September 2021 when it will be going to an end shortly afterward. |
format | Online Article Text |
id | pubmed-8035887 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-80358872021-04-12 The COVID-19 pandemic: prediction study based on machine learning models Malki, Zohair Atlam, El-Sayed Ewis, Ashraf Dagnew, Guesh Ghoneim, Osama A. Mohamed, Abdallah A. Abdel-Daim, Mohamed M. Gad, Ibrahim Environ Sci Pollut Res Int Environmental Factors and the Epidemics of COVID-19 COVID-19 was first discovered in Wuhan, China in December 2019. It is one of the worst pandemics in human history. Recent studies reported that COVID-19 is transmitted among humans by droplet infection or direct contact. COVID-19 pandemic has invaded more than 210 countries around the world and as of February 18(th), 2021, just after a year has passed, a total of 110,533,973 confirmed cases of COVID-19 were reported and its death toll reached about 2,443,091. COVID-19 is a new member of the family of corona viruses, its nature, behaviour, transmission, spread, prevention, and treatment are to be investigated. Generally, a huge amount of data is accumulating regarding the COVID-19 pandemic, which makes hot research topics for machine learning researchers. However, the panicked world’s population is asking when the COVID-19 will be over? This study considered machine learning approaches to predict the spread of the COVID-19 in many countries. The experimental results of the proposed model showed that the overall R2 is 0.99 from the perspective of confirmed cases. A machine learning model has been developed to predict the estimation of the spread of the COVID-19 infection in many countries and the expected period after which the virus can be stopped. Globally, our results forecasted that the COVID-19 infections will greatly decline during the first week of September 2021 when it will be going to an end shortly afterward. Springer Berlin Heidelberg 2021-04-10 2021 /pmc/articles/PMC8035887/ /pubmed/33840016 http://dx.doi.org/10.1007/s11356-021-13824-7 Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Environmental Factors and the Epidemics of COVID-19 Malki, Zohair Atlam, El-Sayed Ewis, Ashraf Dagnew, Guesh Ghoneim, Osama A. Mohamed, Abdallah A. Abdel-Daim, Mohamed M. Gad, Ibrahim The COVID-19 pandemic: prediction study based on machine learning models |
title | The COVID-19 pandemic: prediction study based on machine learning models |
title_full | The COVID-19 pandemic: prediction study based on machine learning models |
title_fullStr | The COVID-19 pandemic: prediction study based on machine learning models |
title_full_unstemmed | The COVID-19 pandemic: prediction study based on machine learning models |
title_short | The COVID-19 pandemic: prediction study based on machine learning models |
title_sort | covid-19 pandemic: prediction study based on machine learning models |
topic | Environmental Factors and the Epidemics of COVID-19 |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8035887/ https://www.ncbi.nlm.nih.gov/pubmed/33840016 http://dx.doi.org/10.1007/s11356-021-13824-7 |
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