title: Bayesian hierarchical modeling of latent period switching in small-area putative health hazard studies.
abstract: In recent years, small area risk assessment modelling and data analysis around putative hazard sources has become a fundamental part of public health and environmental sciences. In this study, we address a fundamental problem in the analysis of such data, when intermittent operation of facilities could lead to evidence for latent periods of risk. This study examines the development of Bayesian models for the latent switching operating period of putative hazard sources such as nuclear processing plants and waste disposal incinerators. The developed methodology is applied in a simulation study as well as to a real data example.
authors.affiliation: Department of Epidemiology and Biostatistics, Arnold School of Public Health, University of South Carolina, Columbia, SC, USA. ahmedysk@yahoo.com
authors.forename: Ahmed
authors.initials: A
authors.lastname: Al-Hadhrami
authors.forename: Andrew B
authors.initials: AB
authors.lastname: Lawson
mesh_terms: D001499:Bayes Theorem; D003198:Computer Simulation / Q000706:statistics & numerical data*; D006801:Humans; D017745:Incineration / Q000706:statistics & numerical data; D015233:Models, Statistical; D009820:Ohio / Q000453:epidemiology; D012037:Refuse Disposal / Q000379:methods / Q000706:statistics & numerical data; D012142:Respiratory Tract Neoplasms / Q000401:mortality; D018570:Risk Assessment / Q000706:statistics & numerical data; D017062:Small-Area Analysis