COVID-19 pandemic and chaos theory

The dynamics of COVID-19 is investigated with regard to complex contributions of the omitted factors. For this purpose, we use a fractional order SEIR model which allows us to calculate the number of infections considering the chaotic contributions into susceptible, exposed, infectious and removed n...

Descripción completa

Detalles Bibliográficos
Autores principales: Postavaru, O., Anton, S.R., Toma, A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2021
Materias:
Original Articles
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532837/
https://www.ncbi.nlm.nih.gov/pubmed/33041473
http://dx.doi.org/10.1016/j.matcom.2020.09.029
_version_ 1783590008033116160
author Postavaru, O.
Anton, S.R.
Toma, A.
author_facet Postavaru, O.
Anton, S.R.
Toma, A.
author_sort Postavaru, O.
collection PubMed
description The dynamics of COVID-19 is investigated with regard to complex contributions of the omitted factors. For this purpose, we use a fractional order SEIR model which allows us to calculate the number of infections considering the chaotic contributions into susceptible, exposed, infectious and removed number of individuals. We check our model on Wuhan, China-2019 and South Korea underlying the importance of the chaotic contribution, and then we extend it to Italy and the USA. Results are of great guiding significance to promote evidence-based decisions and policy.
format Online
Article
Text
id pubmed-7532837
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V.
record_format MEDLINE/PubMed
spelling pubmed-75328372020-10-05 COVID-19 pandemic and chaos theory Postavaru, O. Anton, S.R. Toma, A. Math Comput Simul Original Articles The dynamics of COVID-19 is investigated with regard to complex contributions of the omitted factors. For this purpose, we use a fractional order SEIR model which allows us to calculate the number of infections considering the chaotic contributions into susceptible, exposed, infectious and removed number of individuals. We check our model on Wuhan, China-2019 and South Korea underlying the importance of the chaotic contribution, and then we extend it to Italy and the USA. Results are of great guiding significance to promote evidence-based decisions and policy. International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. 2021-03 2020-10-03 /pmc/articles/PMC7532837/ /pubmed/33041473 http://dx.doi.org/10.1016/j.matcom.2020.09.029 Text en © 2020 International Association for Mathematics and Computers in Simulation (IMACS). Published by Elsevier B.V. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Original Articles
Postavaru, O.
Anton, S.R.
Toma, A.
COVID-19 pandemic and chaos theory
title COVID-19 pandemic and chaos theory
title_full COVID-19 pandemic and chaos theory
title_fullStr COVID-19 pandemic and chaos theory
title_full_unstemmed COVID-19 pandemic and chaos theory
title_short COVID-19 pandemic and chaos theory
title_sort covid-19 pandemic and chaos theory
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7532837/
https://www.ncbi.nlm.nih.gov/pubmed/33041473
http://dx.doi.org/10.1016/j.matcom.2020.09.029
work_keys_str_mv AT postavaruo covid19pandemicandchaostheory
AT antonsr covid19pandemicandchaostheory
AT tomaa covid19pandemicandchaostheory

Ejemplares similares