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Bayesian spatial modeling of HIV mortality via zero‐inflated Poisson models
Author(s) -
Musal Muzaffer,
Aktekin Tevfik
Publication year - 2012
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.5457
Subject(s) - poisson distribution , econometrics , statistics , covariate , poisson regression , bayesian probability , poverty , mathematics , geography , population , economics , medicine , environmental health , economic growth
In this paper, we investigate the effects of poverty and inequality on the number of HIV‐related deaths in 62 New York counties via Bayesian zero‐inflated Poisson models that exhibit spatial dependence. We quantify inequality via the Theil index and poverty via the ratios of two Census 2000 variables, the number of people under the poverty line and the number of people for whom poverty status is determined, in each Zip Code Tabulation Area. The purpose of this study was to investigate the effects of inequality and poverty in addition to spatial dependence between neighboring regions on HIV mortality rate, which can lead to improved health resource allocation decisions. In modeling county‐specific HIV counts, we propose Bayesian zero‐inflated Poisson models whose rates are functions of both covariate and spatial/random effects. To show how the proposed models work, we used three different publicly available data sets: TIGER Shapefiles, Census 2000, and mortality index files. In addition, we introduce parameter estimation issues of Bayesian zero‐inflated Poisson models and discuss MCMC method implications. Copyright © 2012 John Wiley & Sons, Ltd.