Influence of selected formation rules for finite population networks with fixed macrostructures: implications for individual-based model of infectious diseases

Boily, M. C. and Asghar, Z. and Garske, T. and Ghani, A. and Poulin, R. (2007) Influence of selected formation rules for finite population networks with fixed macrostructures: implications for individual-based model of infectious diseases. Mathematical Population Studies: An International Journal of Mathematical Demography, 14 (4). pp. 237-267. ISSN 0889-8480

Full content URL: http://dx.doi.org/10.1080/08898480701612873

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Item Type:Article
Item Status:Live Archive

Abstract

Individual-based network models are increasingly being applied to understand the transmission dynamics of infectious diseases. Research in this area has mostly focused on networks defined under a limited set of rules (e.g., preferential attachment, sexual partner formation and dissolution) that are supposed to mimic the real world but are often defined heuristically due to lack of empirical knowledge. Here, two different mechanisms (M- and λ2-rules) were used to generate a wide range of networks and to show the extent to which microstructures such as the mean component size, the size of the giant component and the cumulative nomination centrality index may vary between networks with fixed predetermined macrostructure characteristics (size, node degree distribution and mixing pattern) and influence disease transmission. It is important to carefully consider the limitations of network models and to appreciate the extent to which a given degree distribution and mixing pattern will be consistent with a wide range of underlying network microstructures.

Additional Information:Special Issue: Networks in Epidemiology
Keywords:infectious diseases, networks, scale-free
Subjects:G Mathematical and Computer Sciences > G330 Stochastic Processes
C Biological Sciences > C170 Population Biology
G Mathematical and Computer Sciences > G140 Numerical Analysis
G Mathematical and Computer Sciences > G150 Mathematical Modelling
G Mathematical and Computer Sciences > G620 Programming
Divisions:College of Social Science > School of Health & Social Care
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ID Code:13718
Deposited On:02 Apr 2014 16:34

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