Strong dependence of infection profiles on grouping dynamics during epidemiological spreading

Zhenyuan Zhao, Guannan Zhao, Chen Xu, Pak Ming Hui, Neil F Johnson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The spreading of an epidemic depends on the connectivity of the underlying host population. Because of the inherent difficulties in addressing such a problem, research to date on epidemics in networks has focused either on static networks, or networks with relatively few rewirings per timestep. Here we employ a simple, yet highly non-trivial, model of dynamical grouping to investigate the extent to which the underlying dynamics of tightly-knit communities can affect the resulting infection profile. Individual realizations of the spreading tend to be dominated by large peaks corresponding to infection resurgence, and a generally slow decay of the outbreak. In addition to our simulation results, we provide an analytical analysis of the run-averaged behaviour in the regime of fast grouping dynamics. We show that the true run-averaged infection profile can be closely mimicked by employing a suitably weighted static network, thereby dramatically simplifying the level of difficulty.

Original languageEnglish (US)
Title of host publicationLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Pages960-970
Number of pages11
Volume4 LNICST
EditionPART 1
DOIs
StatePublished - 2009
Event1st International Conference on Complex Sciences: Theory and Applications, Complex 2009 - Shanghai, China
Duration: Feb 23 2009Feb 25 2009

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
NumberPART 1
Volume4 LNICST
ISSN (Print)18678211

Other

Other1st International Conference on Complex Sciences: Theory and Applications, Complex 2009
CountryChina
CityShanghai
Period2/23/092/25/09

Keywords

  • Complex systems
  • Epidemics
  • Group dynamics
  • Networks

ASJC Scopus subject areas

  • Computer Networks and Communications

Cite this

Zhao, Z., Zhao, G., Xu, C., Hui, P. M., & Johnson, N. F. (2009). Strong dependence of infection profiles on grouping dynamics during epidemiological spreading. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering (PART 1 ed., Vol. 4 LNICST, pp. 960-970). (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; Vol. 4 LNICST, No. PART 1). https://doi.org/10.1007/978-3-642-02466-5_96

Strong dependence of infection profiles on grouping dynamics during epidemiological spreading. / Zhao, Zhenyuan; Zhao, Guannan; Xu, Chen; Hui, Pak Ming; Johnson, Neil F.

Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering. Vol. 4 LNICST PART 1. ed. 2009. p. 960-970 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; Vol. 4 LNICST, No. PART 1).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Zhao, Z, Zhao, G, Xu, C, Hui, PM & Johnson, NF 2009, Strong dependence of infection profiles on grouping dynamics during epidemiological spreading. in Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering. PART 1 edn, vol. 4 LNICST, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, no. PART 1, vol. 4 LNICST, pp. 960-970, 1st International Conference on Complex Sciences: Theory and Applications, Complex 2009, Shanghai, China, 2/23/09. https://doi.org/10.1007/978-3-642-02466-5_96
Zhao Z, Zhao G, Xu C, Hui PM, Johnson NF. Strong dependence of infection profiles on grouping dynamics during epidemiological spreading. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering. PART 1 ed. Vol. 4 LNICST. 2009. p. 960-970. (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; PART 1). https://doi.org/10.1007/978-3-642-02466-5_96
Zhao, Zhenyuan ; Zhao, Guannan ; Xu, Chen ; Hui, Pak Ming ; Johnson, Neil F. / Strong dependence of infection profiles on grouping dynamics during epidemiological spreading. Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering. Vol. 4 LNICST PART 1. ed. 2009. pp. 960-970 (Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering; PART 1).
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