Mapping ordinarily increases our understanding of nontrivial spatial and temporal heterogeneities in disease rates. However, the large number of parameters required by the corresponding statistical models often complicates detailed analysis. This study investigates the feasibility of a fully Bayesian hierarchical regression approach to the problem and identifies how it outperforms two more popular methods: crude rate estimates (CRE) and empirical Bayes standardization (EBS).
View Article and Find Full Text PDFLyme disease (LD) occurrence in New York State (NYS) has not only increased over time but also spread throughout the state from the original disease focus in southeastern NYS. Few studies have investigated this epidemic and spatial dynamic in great detail. Using data from the NYS Department of Health Lyme Registry Surveillance System, we summarized epidemic and spatial characteristics of LD in NYS for the 11-yr time period from 1990 through 2000.
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