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Prediction of global spread of COVID-19 pandemic: a review and research challenges
Since the initial reports of the Coronavirus surfacing in Wuhan, China, the novel virus currently without a cure has spread like wildfire across the globe, the virus spread exponentially across all inhabited continent, catching local governments by surprise in many cases and bringing the world econo...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285044/ https://www.ncbi.nlm.nih.gov/pubmed/34305251 http://dx.doi.org/10.1007/s10462-021-09988-w |
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author | Shah, Saloni Mulahuwaish, Aos Ghafoor, Kayhan Zrar Maghdid, Halgurd S. |
author_facet | Shah, Saloni Mulahuwaish, Aos Ghafoor, Kayhan Zrar Maghdid, Halgurd S. |
author_sort | Shah, Saloni |
collection | PubMed |
description | Since the initial reports of the Coronavirus surfacing in Wuhan, China, the novel virus currently without a cure has spread like wildfire across the globe, the virus spread exponentially across all inhabited continent, catching local governments by surprise in many cases and bringing the world economy to a standstill. As local authorities work on a response to deal with the virus, the scientific community has stepped in to help analyze and predict the pattern and conditions that would influence the spread of this unforgiving virus. Using existing statistical modeling tools to the latest artificial intelligence technology, the scientific community has used public and privately available data to help with predictions. A lot of this data research has enabled local authorities to plan their response—whether that is to deploy tightly available medical resources like ventilators or how and when to enforce policies to social distance, including lockdowns. On the one hand, this paper shows what accuracy of research brings to enable fighting this disease; while on the other hand, it also shows what lack of response from local authorities can do in spreading this virus. This is our attempt to compile different research methods and comparing their accuracy in predicting the spread of COVID-19. |
format | Online Article Text |
id | pubmed-8285044 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-82850442021-07-19 Prediction of global spread of COVID-19 pandemic: a review and research challenges Shah, Saloni Mulahuwaish, Aos Ghafoor, Kayhan Zrar Maghdid, Halgurd S. Artif Intell Rev Article Since the initial reports of the Coronavirus surfacing in Wuhan, China, the novel virus currently without a cure has spread like wildfire across the globe, the virus spread exponentially across all inhabited continent, catching local governments by surprise in many cases and bringing the world economy to a standstill. As local authorities work on a response to deal with the virus, the scientific community has stepped in to help analyze and predict the pattern and conditions that would influence the spread of this unforgiving virus. Using existing statistical modeling tools to the latest artificial intelligence technology, the scientific community has used public and privately available data to help with predictions. A lot of this data research has enabled local authorities to plan their response—whether that is to deploy tightly available medical resources like ventilators or how and when to enforce policies to social distance, including lockdowns. On the one hand, this paper shows what accuracy of research brings to enable fighting this disease; while on the other hand, it also shows what lack of response from local authorities can do in spreading this virus. This is our attempt to compile different research methods and comparing their accuracy in predicting the spread of COVID-19. Springer Netherlands 2021-07-16 2022 /pmc/articles/PMC8285044/ /pubmed/34305251 http://dx.doi.org/10.1007/s10462-021-09988-w Text en © The Author(s), under exclusive licence to Springer Nature B.V. 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 | Article Shah, Saloni Mulahuwaish, Aos Ghafoor, Kayhan Zrar Maghdid, Halgurd S. Prediction of global spread of COVID-19 pandemic: a review and research challenges |
title | Prediction of global spread of COVID-19 pandemic: a review and research challenges |
title_full | Prediction of global spread of COVID-19 pandemic: a review and research challenges |
title_fullStr | Prediction of global spread of COVID-19 pandemic: a review and research challenges |
title_full_unstemmed | Prediction of global spread of COVID-19 pandemic: a review and research challenges |
title_short | Prediction of global spread of COVID-19 pandemic: a review and research challenges |
title_sort | prediction of global spread of covid-19 pandemic: a review and research challenges |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8285044/ https://www.ncbi.nlm.nih.gov/pubmed/34305251 http://dx.doi.org/10.1007/s10462-021-09988-w |
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