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Keywords:

  • health surveillance;
  • spatial model;
  • exponentially weighted moving average (EWMA);
  • Bayesian method;
  • Markov chain Monte Carlo (MCMC)

Abstract

In this paper a novel method for the monitoring of disease maps over time in a surveillance setting is described. The approach relies upon the use of a spatial model that is fitted to current spatial data and is smoothed with historical spatial estimates. The method of smoothing is a vector exponentially weighted moving average procedure. A simulation study with a range of scenarios is presented and finally a case study of monitoring infectious disease spread is presented. Copyright © 2008 John Wiley & Sons, Ltd.