A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics

Abstract Computational models for large, resurgent epidemics are recognized as a crucial tool for predicting the spread of infectious diseases. It is widely agreed, that such models can be augmented with realistic multiscale population models and by incorporating human mobility patterns. Nevertheles...

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Autores principales:	Alexandru Topîrceanu, Radu-Emil Precup
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/ec6924d5ab8f4b91a2a9e41c10f0bd16
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spelling	oai:doaj.org-article:ec6924d5ab8f4b91a2a9e41c10f0bd162021-12-02T16:08:07ZA novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics10.1038/s41598-021-93810-82045-2322https://doaj.org/article/ec6924d5ab8f4b91a2a9e41c10f0bd162021-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-93810-8https://doaj.org/toc/2045-2322Abstract Computational models for large, resurgent epidemics are recognized as a crucial tool for predicting the spread of infectious diseases. It is widely agreed, that such models can be augmented with realistic multiscale population models and by incorporating human mobility patterns. Nevertheless, a large proportion of recent studies, aimed at better understanding global epidemics, like influenza, measles, H1N1, SARS, and COVID-19, underestimate the role of heterogeneous mixing in populations, characterized by strong social structures and geography. Motivated by the reduced tractability of studies employing homogeneous mixing, which make conclusions hard to deduce, we propose a new, very fine-grained model incorporating the spatial distribution of population into geographical settlements, with a hierarchical organization down to the level of households (inside which we assume homogeneous mixing). In addition, population is organized heterogeneously outside households, and we model the movement of individuals using travel distance and frequency parameters for inter- and intra-settlement movement. Discrete event simulation, employing an adapted SIR model with relapse, reproduces important qualitative characteristics of real epidemics, like high variation in size and temporal heterogeneity (e.g., waves), that are challenging to reproduce and to quantify with existing measures. Our results pinpoint an important aspect, that epidemic size is more sensitive to the increase in distance of travel, rather that the frequency of travel. Finally, we discuss implications for the control of epidemics by integrating human mobility restrictions, as well as progressive vaccination of individuals.Alexandru TopîrceanuRadu-Emil PrecupNature 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 Alexandru Topîrceanu Radu-Emil Precup A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
description	Abstract Computational models for large, resurgent epidemics are recognized as a crucial tool for predicting the spread of infectious diseases. It is widely agreed, that such models can be augmented with realistic multiscale population models and by incorporating human mobility patterns. Nevertheless, a large proportion of recent studies, aimed at better understanding global epidemics, like influenza, measles, H1N1, SARS, and COVID-19, underestimate the role of heterogeneous mixing in populations, characterized by strong social structures and geography. Motivated by the reduced tractability of studies employing homogeneous mixing, which make conclusions hard to deduce, we propose a new, very fine-grained model incorporating the spatial distribution of population into geographical settlements, with a hierarchical organization down to the level of households (inside which we assume homogeneous mixing). In addition, population is organized heterogeneously outside households, and we model the movement of individuals using travel distance and frequency parameters for inter- and intra-settlement movement. Discrete event simulation, employing an adapted SIR model with relapse, reproduces important qualitative characteristics of real epidemics, like high variation in size and temporal heterogeneity (e.g., waves), that are challenging to reproduce and to quantify with existing measures. Our results pinpoint an important aspect, that epidemic size is more sensitive to the increase in distance of travel, rather that the frequency of travel. Finally, we discuss implications for the control of epidemics by integrating human mobility restrictions, as well as progressive vaccination of individuals.
format	article
author	Alexandru Topîrceanu Radu-Emil Precup
author_facet	Alexandru Topîrceanu Radu-Emil Precup
author_sort	Alexandru Topîrceanu
title	A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
title_short	A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
title_full	A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
title_fullStr	A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
title_full_unstemmed	A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
title_sort	novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/ec6924d5ab8f4b91a2a9e41c10f0bd16
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A novel geo-hierarchical population mobility model for spatial spreading of resurgent epidemics

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