Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics

Abstract As the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. The momentary reproduction ratio r(t) of an epidemic is used as a public health guiding tool to evaluate the course...

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Autores principales:	Maíra Aguiar, Joseba Bidaurrazaga Van-Dierdonck, Javier Mar, Nicole Cusimano, Damián Knopoff, Vizda Anam, Nico Stollenwerk
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/b8b02e8111c04669b07aa5bb5e842999
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spelling	oai:doaj.org-article:b8b02e8111c04669b07aa5bb5e8429992021-12-02T15:23:17ZCritical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics10.1038/s41598-021-93366-72045-2322https://doaj.org/article/b8b02e8111c04669b07aa5bb5e8429992021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93366-7https://doaj.org/toc/2045-2322Abstract As the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. The momentary reproduction ratio r(t) of an epidemic is used as a public health guiding tool to evaluate the course of the epidemic, with the evolution of r(t) being the reasoning behind tightening and relaxing control measures over time. Here we investigate critical fluctuations around the epidemiological threshold, resembling new waves, even when the community disease transmission rate $$\beta$$ β is not significantly changing. Without loss of generality, we use simple models that can be treated analytically and results are applied to more complex models describing COVID-19 epidemics. Our analysis shows that, rather than the supercritical regime (infectivity larger than a critical value, $$\beta > \beta _c$$ β > β c ) leading to new exponential growth of infection, the subcritical regime (infectivity smaller than a critical value, $$\beta < \beta _c$$ β < β c ) with small import is able to explain the dynamic behaviour of COVID-19 spreading after a lockdown lifting, with $$r(t) \approx 1$$ r ( t ) ≈ 1 hovering around its threshold value.Maíra AguiarJoseba Bidaurrazaga Van-DierdonckJavier MarNicole CusimanoDamián KnopoffVizda AnamNico StollenwerkNature 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 Maíra Aguiar Joseba Bidaurrazaga Van-Dierdonck Javier Mar Nicole Cusimano Damián Knopoff Vizda Anam Nico Stollenwerk Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics
description	Abstract As the COVID-19 pandemic progressed, research on mathematical modeling became imperative and very influential to understand the epidemiological dynamics of disease spreading. The momentary reproduction ratio r(t) of an epidemic is used as a public health guiding tool to evaluate the course of the epidemic, with the evolution of r(t) being the reasoning behind tightening and relaxing control measures over time. Here we investigate critical fluctuations around the epidemiological threshold, resembling new waves, even when the community disease transmission rate $$\beta$$ β is not significantly changing. Without loss of generality, we use simple models that can be treated analytically and results are applied to more complex models describing COVID-19 epidemics. Our analysis shows that, rather than the supercritical regime (infectivity larger than a critical value, $$\beta > \beta _c$$ β > β c ) leading to new exponential growth of infection, the subcritical regime (infectivity smaller than a critical value, $$\beta < \beta _c$$ β < β c ) with small import is able to explain the dynamic behaviour of COVID-19 spreading after a lockdown lifting, with $$r(t) \approx 1$$ r ( t ) ≈ 1 hovering around its threshold value.
format	article
author	Maíra Aguiar Joseba Bidaurrazaga Van-Dierdonck Javier Mar Nicole Cusimano Damián Knopoff Vizda Anam Nico Stollenwerk
author_facet	Maíra Aguiar Joseba Bidaurrazaga Van-Dierdonck Javier Mar Nicole Cusimano Damián Knopoff Vizda Anam Nico Stollenwerk
author_sort	Maíra Aguiar
title	Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics
title_short	Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics
title_full	Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics
title_fullStr	Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics
title_full_unstemmed	Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics
title_sort	critical fluctuations in epidemic models explain covid-19 post-lockdown dynamics
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/b8b02e8111c04669b07aa5bb5e842999
work_keys_str_mv	AT mairaaguiar criticalfluctuationsinepidemicmodelsexplaincovid19postlockdowndynamics AT josebabidaurrazagavandierdonck criticalfluctuationsinepidemicmodelsexplaincovid19postlockdowndynamics AT javiermar criticalfluctuationsinepidemicmodelsexplaincovid19postlockdowndynamics AT nicolecusimano criticalfluctuationsinepidemicmodelsexplaincovid19postlockdowndynamics AT damianknopoff criticalfluctuationsinepidemicmodelsexplaincovid19postlockdowndynamics AT vizdaanam criticalfluctuationsinepidemicmodelsexplaincovid19postlockdowndynamics AT nicostollenwerk criticalfluctuationsinepidemicmodelsexplaincovid19postlockdowndynamics
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Critical fluctuations in epidemic models explain COVID-19 post-lockdown dynamics

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