title: Spatial Bayesian surveillance for small area case event data.
abstract: There has been little development of surveillance procedures for epidemiological data with fine spatial resolution such as case events at residential address locations. This is often due to difficulties of access when confidentiality of medical records is an issue. However, when such data are available, it is important to be able to affect an appropriate analysis strategy. We propose a model for point events in the context of prospective surveillance based on conditional logistic modeling. A weighted conditional autoregressive model is developed for irregular lattices to account for distance effects, and a Dirichlet tessellation is adopted to define the neighborhood structure. Localized clustering diagnostics are compared including the proposed local Kullback-Leibler information criterion. A simulation study is conducted to examine the surveillance and detection methods, and a data example is provided of non-Hodgkin's lymphoma data in South Carolina.
authors: Department of Public Health sciences, Medical University of South Carolina, USA chawarat.rot@biotec.or.th.
authors: Chawarat
authors: C
authors: Rotejanaprasert
authors: Department of Public Health sciences, Medical University of South Carolina, USA.
authors: Andrew
authors: A
authors: Lawson
authors: South Carolina Central Cancer Registry, South Carolina Department of Health and Environmental Control, USA.
authors: Susan
authors: S
authors: Bolick-Aldrich
authors: South Carolina Central Cancer Registry, South Carolina Department of Health and Environmental Control, USA.
authors: Deborah
authors: D
authors: Hurley
mesh_terms: D001499:Bayes Theorem; D016000:Cluster Analysis; D003198:Computer Simulation; D062665:Epidemiological Monitoring; D006801:Humans; D016015:Logistic Models; D008228:Lymphoma, Non-Hodgkin / Q000175:diagnosis* / Q000453:epidemiology*; D011446:Prospective Studies; D012372:ROC Curve; D013022:South Carolina / Q000453:epidemiology; D062211:Spatio-Temporal Analysis
keywords: Bayesian; Kullback–Leibler; case event data; spatial; surveillance