Clustering model for transmission of the SARS virus: Application to epidemic control and risk assessment

Michael Small, Chi Kong Tse

Research output: Journal article publicationJournal articleAcademic researchpeer-review

52 Citations (Scopus)

Abstract

We propose a new four state model for disease transmission and illustrate the model with data from the 2003 SARS epidemic in Hong Kong. The critical feature of this model is that the community is modelled as a small-world network of interconnected nodes. Each node is linked to a fixed number of immediate neighbors and a random number of geographically remote nodes. Transmission can only propagate between linked nodes. This model exhibits two features typical of SARS transmission: geographically localized outbreaks and "super- spreaders". Neither of these features are evident in standard susceptible-infected-removed models of disease transmission. Our analysis indicates that "super-spreaders" may occur even if the infectiousness of all infected individuals is constant. Moreover, we find that nosocomial transmission in Hong Kong directly contributed to the severity of the outbreak and that by limiting individual exposure time to 3-5 days the extent of the SARS epidemic would have been minimal.
Original languageEnglish
Pages (from-to)499-511
Number of pages13
JournalPhysica A: Statistical Mechanics and its Applications
Volume351
Issue number2-4
DOIs
Publication statusPublished - 15 Jun 2005

Keywords

  • Disease transmission
  • Epidemiological methods
  • Nonlinear dynamics
  • Severe acute respiratory syndrome
  • Small world networks

ASJC Scopus subject areas

  • Statistics and Probability
  • Condensed Matter Physics

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