Pathogens, social networks, and the paradox of transmission scaling

Ferrari, Matthew, Perkins, Sarah E. ORCID: https://orcid.org/0000-0002-7457-2699, Pomeroy, Laura and Bjørnstad, Ottar 2011. Pathogens, social networks, and the paradox of transmission scaling. Interdisciplinary Perspectives on Infectious Diseases 2011 , 267049. 10.1155/2011/267049

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Abstract

Understanding the scaling of transmission is critical to predicting how infectious diseases will affect populations of different sizes and densities. The two classic “mean-field” epidemic models—either assuming density-dependent or frequency-dependent transmission—make predictions that are discordant with patterns seen in either within-population dynamics or across-population comparisons. In this paper, we propose that the source of this inconsistency lies in the greatly simplifying “mean-field” assumption of transmission within a fully-mixed population. Mixing in real populations is more accurately represented by a network of contacts, with interactions and infectious contacts confined to the local social neighborhood. We use network models to show that density-dependent transmission on heterogeneous networks often leads to apparent frequency dependency in the scaling of transmission across populations of different sizes. Network-methodology allows us to reconcile seemingly conflicting patterns of within- and across-population epidemiology.

Item Type:	Article
Date Type:	Publication
Status:	Published
Schools:	Biosciences
Subjects:	Q Science > Q Science (General)
Additional Information:	10 pp.
Publisher:	Hindawi
ISSN:	1687-708X
Date of First Compliant Deposit:	30 March 2016
Last Modified:	08 May 2023 02:03
URI:	https://orca.cardiff.ac.uk/id/eprint/25277

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