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A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany
Early forecasting of COVID-19 virus spread is crucial to decision making on lockdown or closure of cities, states or countries. In this paper we design a recursive bifurcation model for analyzing COVID-19 virus spread in different countries. The bifurcation facilitates recursive processing of infect...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Nature Publishing Group UK
2020
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695842/ https://www.ncbi.nlm.nih.gov/pubmed/33247187 http://dx.doi.org/10.1038/s41598-020-77457-5 |
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author | Shen, Julia |
author_facet | Shen, Julia |
author_sort | Shen, Julia |
collection | PubMed |
description | Early forecasting of COVID-19 virus spread is crucial to decision making on lockdown or closure of cities, states or countries. In this paper we design a recursive bifurcation model for analyzing COVID-19 virus spread in different countries. The bifurcation facilitates recursive processing of infected population through linear least-squares fitting. In addition, a nonlinear least-squares fitting procedure is utilized to predict the future values of infected populations. Numerical results on the data from two countries (South Korea and Germany) indicate the effectiveness of our approach, compared to a logistic growth model and a Richards model in the context of early forecast. The limitation of our approach and future research are also mentioned at the end of this paper. |
format | Online Article Text |
id | pubmed-7695842 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-76958422020-11-30 A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany Shen, Julia Sci Rep Article Early forecasting of COVID-19 virus spread is crucial to decision making on lockdown or closure of cities, states or countries. In this paper we design a recursive bifurcation model for analyzing COVID-19 virus spread in different countries. The bifurcation facilitates recursive processing of infected population through linear least-squares fitting. In addition, a nonlinear least-squares fitting procedure is utilized to predict the future values of infected populations. Numerical results on the data from two countries (South Korea and Germany) indicate the effectiveness of our approach, compared to a logistic growth model and a Richards model in the context of early forecast. The limitation of our approach and future research are also mentioned at the end of this paper. Nature Publishing Group UK 2020-11-27 /pmc/articles/PMC7695842/ /pubmed/33247187 http://dx.doi.org/10.1038/s41598-020-77457-5 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Shen, Julia A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany |
title | A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany |
title_full | A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany |
title_fullStr | A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany |
title_full_unstemmed | A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany |
title_short | A recursive bifurcation model for early forecasting of COVID-19 virus spread in South Korea and Germany |
title_sort | recursive bifurcation model for early forecasting of covid-19 virus spread in south korea and germany |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7695842/ https://www.ncbi.nlm.nih.gov/pubmed/33247187 http://dx.doi.org/10.1038/s41598-020-77457-5 |
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