Emergence of universality in the transmission dynamics of COVID-19

Abstract The complexities involved in modelling the transmission dynamics of COVID-19 has been a roadblock in achieving predictability in the spread and containment of the disease. In addition to understanding the modes of transmission, the effectiveness of the mitigation methods also needs to be bu...

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Autores principales:	Ayan Paul, Jayanta Kumar Bhattacharjee, Akshay Pal, Sagar Chakraborty
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/8495acbac6b1478b9e49fd38b8799911
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spelling	oai:doaj.org-article:8495acbac6b1478b9e49fd38b87999112021-12-02T17:27:19ZEmergence of universality in the transmission dynamics of COVID-1910.1038/s41598-021-98302-32045-2322https://doaj.org/article/8495acbac6b1478b9e49fd38b87999112021-09-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-98302-3https://doaj.org/toc/2045-2322Abstract The complexities involved in modelling the transmission dynamics of COVID-19 has been a roadblock in achieving predictability in the spread and containment of the disease. In addition to understanding the modes of transmission, the effectiveness of the mitigation methods also needs to be built into any effective model for making such predictions. We show that such complexities can be circumvented by appealing to scaling principles which lead to the emergence of universality in the transmission dynamics of the disease. The ensuing data collapse renders the transmission dynamics largely independent of geopolitical variations, the effectiveness of various mitigation strategies, population demographics, etc. We propose a simple two-parameter model—the Blue Sky model—and show that one class of transmission dynamics can be explained by a solution that lives at the edge of a blue sky bifurcation. In addition, the data collapse leads to an enhanced degree of predictability in the disease spread for several geographical scales which can also be realized in a model-independent manner as we show using a deep neural network. The methodology adopted in this work can potentially be applied to the transmission of other infectious diseases and new universality classes may be found. The predictability in transmission dynamics and the simplicity of our methodology can help in building policies for exit strategies and mitigation methods during a pandemic.Ayan PaulJayanta Kumar BhattacharjeeAkshay PalSagar ChakrabortyNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ayan Paul Jayanta Kumar Bhattacharjee Akshay Pal Sagar Chakraborty Emergence of universality in the transmission dynamics of COVID-19
description	Abstract The complexities involved in modelling the transmission dynamics of COVID-19 has been a roadblock in achieving predictability in the spread and containment of the disease. In addition to understanding the modes of transmission, the effectiveness of the mitigation methods also needs to be built into any effective model for making such predictions. We show that such complexities can be circumvented by appealing to scaling principles which lead to the emergence of universality in the transmission dynamics of the disease. The ensuing data collapse renders the transmission dynamics largely independent of geopolitical variations, the effectiveness of various mitigation strategies, population demographics, etc. We propose a simple two-parameter model—the Blue Sky model—and show that one class of transmission dynamics can be explained by a solution that lives at the edge of a blue sky bifurcation. In addition, the data collapse leads to an enhanced degree of predictability in the disease spread for several geographical scales which can also be realized in a model-independent manner as we show using a deep neural network. The methodology adopted in this work can potentially be applied to the transmission of other infectious diseases and new universality classes may be found. The predictability in transmission dynamics and the simplicity of our methodology can help in building policies for exit strategies and mitigation methods during a pandemic.
format	article
author	Ayan Paul Jayanta Kumar Bhattacharjee Akshay Pal Sagar Chakraborty
author_facet	Ayan Paul Jayanta Kumar Bhattacharjee Akshay Pal Sagar Chakraborty
author_sort	Ayan Paul
title	Emergence of universality in the transmission dynamics of COVID-19
title_short	Emergence of universality in the transmission dynamics of COVID-19
title_full	Emergence of universality in the transmission dynamics of COVID-19
title_fullStr	Emergence of universality in the transmission dynamics of COVID-19
title_full_unstemmed	Emergence of universality in the transmission dynamics of COVID-19
title_sort	emergence of universality in the transmission dynamics of covid-19
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8495acbac6b1478b9e49fd38b8799911
work_keys_str_mv	AT ayanpaul emergenceofuniversalityinthetransmissiondynamicsofcovid19 AT jayantakumarbhattacharjee emergenceofuniversalityinthetransmissiondynamicsofcovid19 AT akshaypal emergenceofuniversalityinthetransmissiondynamicsofcovid19 AT sagarchakraborty emergenceofuniversalityinthetransmissiondynamicsofcovid19
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Emergence of universality in the transmission dynamics of COVID-19

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