Modelling SARS data using threshold geometric process

Stat Med. 2006 Jun 15;25(11):1826-39. doi: 10.1002/sim.2376.

Abstract

During the outbreak of an epidemic disease, for example, the severe acute respiratory syndrome (SARS), the number of daily infected cases often exhibit multiple trends: monotone increasing during the growing stage, stationary during the stabilized stage and then decreasing during the declining stage. Lam first proposed modelling a monotone trend by a geometric process (GP) [X(i), i=1,2,...] directly such that [a(i-1)X(i), i=1,2,...] forms a renewal process for some ratio a>0 which measures the direction and strength of the trend. Parameters can be conveniently estimated using the LSE methods. Previous GP models limit to data with only a single trend. For data with multiple trends, we propose a moving window technique to locate the turning point(s). The threshold GP model is fitted to the SARS data from four regions in 2003.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Interpretation, Statistical
  • Disease Outbreaks*
  • Hong Kong / epidemiology
  • Humans
  • Incidence
  • Models, Biological*
  • Models, Statistical*
  • Numerical Analysis, Computer-Assisted
  • Ontario / epidemiology
  • Quarantine
  • SARS Virus / growth & development*
  • Severe Acute Respiratory Syndrome / epidemiology*
  • Singapore / epidemiology
  • Stochastic Processes
  • Taiwan / epidemiology