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Modelling disease outbreaks in realistic urban social networks

Modelling disease outbreaks in realistic urban social networks Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions1 or ad hoc models for the contact process2,3,4. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like5 graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free6, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Nature Springer Journals

Modelling disease outbreaks in realistic urban social networks

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References (56)

Publisher
Springer Journals
Copyright
Copyright © Macmillan Magazines Ltd. 2004
Subject
Science, Humanities and Social Sciences, multidisciplinary; Science, Humanities and Social Sciences, multidisciplinary; Science, multidisciplinary
ISSN
0028-0836
eISSN
1476-4687
DOI
10.1038/nature02541
Publisher site
See Article on Publisher Site

Abstract

Most mathematical models for the spread of disease use differential equations based on uniform mixing assumptions1 or ad hoc models for the contact process2,3,4. Here we explore the use of dynamic bipartite graphs to model the physical contact patterns that result from movements of individuals between specific locations. The graphs are generated by large-scale individual-based urban traffic simulations built on actual census, land-use and population-mobility data. We find that the contact network among people is a strongly connected small-world-like5 graph with a well-defined scale for the degree distribution. However, the locations graph is scale-free6, which allows highly efficient outbreak detection by placing sensors in the hubs of the locations network. Within this large-scale simulation framework, we then analyse the relative merits of several proposed mitigation strategies for smallpox spread. Our results suggest that outbreaks can be contained by a strategy of targeted vaccination combined with early detection without resorting to mass vaccination of a population.

Journal

NatureSpringer Journals

Published: May 13, 2004

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