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Modelling disease spread through random and regular contacts in clustered populations

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  • Eames, K.T.D.

Abstract

An epidemic spreading through a network of regular, repeated, contacts behaves differently from one that is spread by random interactions: regular contacts serve to reduce the speed and eventual size of an epidemic. This paper uses a mathematical model to explore the difference between regular and random contacts, considering particularly the effect of clustering within the contact network. In a clustered population random contacts have a much greater impact, allowing infection to reach parts of the network that would otherwise be inaccessible. When all contacts are regular, clustering greatly reduces the spread of infection; this effect is negated by a small number of random contacts.

Suggested Citation

  • Eames, K.T.D., 2008. "Modelling disease spread through random and regular contacts in clustered populations," Theoretical Population Biology, Elsevier, vol. 73(1), pages 104-111.
  • Handle: RePEc:eee:thpobi:v:73:y:2008:i:1:p:104-111
    DOI: 10.1016/j.tpb.2007.09.007
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    References listed on IDEAS

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    1. Neil M. Ferguson & Derek A. T. Cummings & Christophe Fraser & James C. Cajka & Philip C. Cooley & Donald S. Burke, 2006. "Strategies for mitigating an influenza pandemic," Nature, Nature, vol. 442(7101), pages 448-452, July.
    2. Tsimring, Lev S & Huerta, Ramón, 2003. "Modeling of contact tracing in social networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 325(1), pages 33-39.
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    Cited by:

    1. Shanshan Chen & Yijun Ran & Hebo Huang & Zhenzhen Wang & Ke-ke Shang, 2022. "Epidemic Dynamics of Two-Pathogen Spreading for Pairwise Models," Mathematics, MDPI, vol. 10(11), pages 1-18, June.
    2. Marcel Salathé & James H Jones, 2010. "Dynamics and Control of Diseases in Networks with Community Structure," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-11, April.
    3. Duncan, A.J. & Gunn, G.J. & Umstatter, C. & Humphry, R.W., 2014. "Replicating disease spread in empirical cattle networks by adjusting the probability of infection in random networks," Theoretical Population Biology, Elsevier, vol. 98(C), pages 11-18.

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