A bivariate method for spatio-temporal syndromic surveillance (article published in proceedings)

Introduction: Statistical analysis of syndromic data has typically focused on univariate test statistics for spatial, temporal, or spatio-temporal surveillance. However, this approach does not take full advantage of the information available in the data. Objectives: A bivariate method is proposed that uses both temporal and spatial data information. Methods: Using upper respiratory syndromic data from an eastern Massachusetts health-care provider, this paper illustrates a bivariate method and examines the power of this method to detect simulated clusters. Results: Use of the bivariate method increases detection power. Conclusions: Syndromic surveillance systems should use all available information, including both spatial and temporal information.