Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas

Abstract We build on recent work to develop a fully mechanistic, activity-based and highly spatio-temporally resolved epidemiological model which leverages person-trajectories obtained from an activity-based model calibrated for two full-scale prototype cities, consisting of representative synthetic...

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Autores principales:	Nishant Kumar, Jimi Oke, Bat-hen Nahmias-Biran
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/292ae6798f904034a3f9ad3de6e9f8f1
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spelling	oai:doaj.org-article:292ae6798f904034a3f9ad3de6e9f8f12021-11-28T12:19:27ZActivity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas10.1038/s41598-021-01522-w2045-2322https://doaj.org/article/292ae6798f904034a3f9ad3de6e9f8f12021-11-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-01522-whttps://doaj.org/toc/2045-2322Abstract We build on recent work to develop a fully mechanistic, activity-based and highly spatio-temporally resolved epidemiological model which leverages person-trajectories obtained from an activity-based model calibrated for two full-scale prototype cities, consisting of representative synthetic populations and mobility networks for two contrasting auto-dependent city typologies. We simulate the propagation of the COVID-19 epidemic in both cities to analyze spreading patterns in urban networks across various activity types. Investigating the impact of the transit network, we find that its removal dampens disease propagation significantly, suggesting that transit restriction is more critical for mitigating post-peak disease spreading in transit dense cities. In the latter stages of disease spread, we find that the greatest share of infections occur at work locations. A statistical analysis of the resulting activity-based contact networks indicates that transit contacts are scale-free, work contacts are Weibull distributed, and shopping or leisure contacts are exponentially distributed. We validate our simulation results against existing case and mortality data across multiple cities in their respective typologies. Our framework demonstrates the potential for tracking epidemic propagation in urban networks, analyzing socio-demographic impacts and assessing activity- and mobility-specific implications of both non-pharmaceutical and pharmaceutical intervention strategies.Nishant KumarJimi OkeBat-hen Nahmias-BiranNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-14 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Nishant Kumar Jimi Oke Bat-hen Nahmias-Biran Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas
description	Abstract We build on recent work to develop a fully mechanistic, activity-based and highly spatio-temporally resolved epidemiological model which leverages person-trajectories obtained from an activity-based model calibrated for two full-scale prototype cities, consisting of representative synthetic populations and mobility networks for two contrasting auto-dependent city typologies. We simulate the propagation of the COVID-19 epidemic in both cities to analyze spreading patterns in urban networks across various activity types. Investigating the impact of the transit network, we find that its removal dampens disease propagation significantly, suggesting that transit restriction is more critical for mitigating post-peak disease spreading in transit dense cities. In the latter stages of disease spread, we find that the greatest share of infections occur at work locations. A statistical analysis of the resulting activity-based contact networks indicates that transit contacts are scale-free, work contacts are Weibull distributed, and shopping or leisure contacts are exponentially distributed. We validate our simulation results against existing case and mortality data across multiple cities in their respective typologies. Our framework demonstrates the potential for tracking epidemic propagation in urban networks, analyzing socio-demographic impacts and assessing activity- and mobility-specific implications of both non-pharmaceutical and pharmaceutical intervention strategies.
format	article
author	Nishant Kumar Jimi Oke Bat-hen Nahmias-Biran
author_facet	Nishant Kumar Jimi Oke Bat-hen Nahmias-Biran
author_sort	Nishant Kumar
title	Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas
title_short	Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas
title_full	Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas
title_fullStr	Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas
title_full_unstemmed	Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas
title_sort	activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/292ae6798f904034a3f9ad3de6e9f8f1
work_keys_str_mv	AT nishantkumar activitybasedepidemicpropagationandcontactnetworkscalinginautodependentmetropolitanareas AT jimioke activitybasedepidemicpropagationandcontactnetworkscalinginautodependentmetropolitanareas AT bathennahmiasbiran activitybasedepidemicpropagationandcontactnetworkscalinginautodependentmetropolitanareas
_version_	1718408065728905216

Activity-based epidemic propagation and contact network scaling in auto-dependent metropolitan areas

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