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Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions

In this paper, we make long-termed prediction for numbers of accumulative confirmed patients (NACPs) and numbers of accumulative death patients (NADPs) of COVID-19 in different countries and regions by fitting method. We use hyperbolic tangent functions as basic functions for the fitting method. The...

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Detalles Bibliográficos
Autores principales: Pei, Lijun, Zhang, Hongyang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7926199/
https://www.ncbi.nlm.nih.gov/pubmed/33680710
http://dx.doi.org/10.1007/s40435-021-00770-y
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author Pei, Lijun
Zhang, Hongyang
author_facet Pei, Lijun
Zhang, Hongyang
author_sort Pei, Lijun
collection PubMed
description In this paper, we make long-termed prediction for numbers of accumulative confirmed patients (NACPs) and numbers of accumulative death patients (NADPs) of COVID-19 in different countries and regions by fitting method. We use hyperbolic tangent functions as basic functions for the fitting method. The results indicate that it is possible to make long-termed prediction for NACPs and NADPs of COVID-19 by using a small amount of data. And we can estimate the arrival times of the plateau phases of COVID-19 in some countries and regions. It shows that our method is simple (model-free) and very effective in long-termed prediction of NACPs and NADPs with small data.
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spelling pubmed-79261992021-03-03 Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions Pei, Lijun Zhang, Hongyang Int J Dyn Control Article In this paper, we make long-termed prediction for numbers of accumulative confirmed patients (NACPs) and numbers of accumulative death patients (NADPs) of COVID-19 in different countries and regions by fitting method. We use hyperbolic tangent functions as basic functions for the fitting method. The results indicate that it is possible to make long-termed prediction for NACPs and NADPs of COVID-19 by using a small amount of data. And we can estimate the arrival times of the plateau phases of COVID-19 in some countries and regions. It shows that our method is simple (model-free) and very effective in long-termed prediction of NACPs and NADPs with small data. Springer Berlin Heidelberg 2021-03-03 2021 /pmc/articles/PMC7926199/ /pubmed/33680710 http://dx.doi.org/10.1007/s40435-021-00770-y Text en © The Author(s), under exclusive licence to Springer-Verlag GmbH, DE 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 Article
Pei, Lijun
Zhang, Hongyang
Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions
title Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions
title_full Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions
title_fullStr Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions
title_full_unstemmed Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions
title_short Possibility of long-termed prediction of NACPs and NADPs of COVID-19 in different countries and regions via tanh basic functions
title_sort possibility of long-termed prediction of nacps and nadps of covid-19 in different countries and regions via tanh basic functions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7926199/
https://www.ncbi.nlm.nih.gov/pubmed/33680710
http://dx.doi.org/10.1007/s40435-021-00770-y
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