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Mathematic modeling of COVID-19 in the United States
COVID-19, the worst pandemic in 100 years, has rapidly spread to the entire world in 2 months since its early report in January 2020. Based on the publicly available data sources, we developed a simple mathematic modeling approach to track the outbreaks of COVID-19 in the US and three selected state...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Taylor & Francis
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241447/ https://www.ncbi.nlm.nih.gov/pubmed/32338150 http://dx.doi.org/10.1080/22221751.2020.1760146 |
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author | Tang, Yuanji Wang, Shixia |
author_facet | Tang, Yuanji Wang, Shixia |
author_sort | Tang, Yuanji |
collection | PubMed |
description | COVID-19, the worst pandemic in 100 years, has rapidly spread to the entire world in 2 months since its early report in January 2020. Based on the publicly available data sources, we developed a simple mathematic modeling approach to track the outbreaks of COVID-19 in the US and three selected states: New York, Michigan and California. The same approach is applicable to other regions or countries. We hope our work can stimulate more effort in understanding how an outbreak is developing and how big a scope it can be and in what kind of time framework. Such information is critical for outbreak control, resource utilization and re-opening of the normal daily life to citizens in the affected community. |
format | Online Article Text |
id | pubmed-7241447 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Taylor & Francis |
record_format | MEDLINE/PubMed |
spelling | pubmed-72414472020-06-01 Mathematic modeling of COVID-19 in the United States Tang, Yuanji Wang, Shixia Emerg Microbes Infect Letter COVID-19, the worst pandemic in 100 years, has rapidly spread to the entire world in 2 months since its early report in January 2020. Based on the publicly available data sources, we developed a simple mathematic modeling approach to track the outbreaks of COVID-19 in the US and three selected states: New York, Michigan and California. The same approach is applicable to other regions or countries. We hope our work can stimulate more effort in understanding how an outbreak is developing and how big a scope it can be and in what kind of time framework. Such information is critical for outbreak control, resource utilization and re-opening of the normal daily life to citizens in the affected community. Taylor & Francis 2020-04-30 /pmc/articles/PMC7241447/ /pubmed/32338150 http://dx.doi.org/10.1080/22221751.2020.1760146 Text en © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group, on behalf of Shanghai Shangyixun Cultural Communication Co., Ltd https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Letter Tang, Yuanji Wang, Shixia Mathematic modeling of COVID-19 in the United States |
title | Mathematic modeling of COVID-19 in the United States |
title_full | Mathematic modeling of COVID-19 in the United States |
title_fullStr | Mathematic modeling of COVID-19 in the United States |
title_full_unstemmed | Mathematic modeling of COVID-19 in the United States |
title_short | Mathematic modeling of COVID-19 in the United States |
title_sort | mathematic modeling of covid-19 in the united states |
topic | Letter |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7241447/ https://www.ncbi.nlm.nih.gov/pubmed/32338150 http://dx.doi.org/10.1080/22221751.2020.1760146 |
work_keys_str_mv | AT tangyuanji mathematicmodelingofcovid19intheunitedstates AT wangshixia mathematicmodelingofcovid19intheunitedstates |