COVID-19: Analytics of contagion on inhomogeneous random social networks

Motivated by the need for robust models of the Covid-19 epidemic that adequately reflect the extreme heterogeneity of humans and society, this paper presents a novel framework that treats a population of N individuals as an inhomogeneous random social network (IRSN). The nodes of the network represe...

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Detalles Bibliográficos
Autor principal: Hurd, T.R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: KeAi Publishing 2020
Materias:
Special issue on Modelling and Forecasting the 2019 Novel Coronavirus (2019-nCoV) Transmission; Edited by Prof. Carlos Castillo-Chavez, Prof. Gerardo Chowell-Puente, Prof. Ping Yan, Prof. Jianhong Wu
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711301/
https://www.ncbi.nlm.nih.gov/pubmed/33313455
http://dx.doi.org/10.1016/j.idm.2020.11.001

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7711301/
https://www.ncbi.nlm.nih.gov/pubmed/33313455
http://dx.doi.org/10.1016/j.idm.2020.11.001

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