Bivariate method for spatio-temporal syndromic surveillance.

Al Ozonoff; L Forsberg; M Bonetti; M Pagano

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PubMed · 15714631

Bivariate method for spatio-temporal syndromic surveillance.

Al Ozonoff·L Forsberg·M Bonetti·M Pagano

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Abstract

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.

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Cluster Analysis Demography Disease Outbreaks Epidemiologic Measurements Humans Models, Statistical Population Surveillance Journal Article Research Support, U.S. Gov't, P.H.S.

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Al Ozonoff, L Forsberg, M Bonetti, M Pagano. 2004-09-24. Bivariate method for spatio-temporal syndromic surveillance.. https://pubmed.ncbi.nlm.nih.gov/15714631/

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