NDLI: Semiparametric space–time survival modeling of chronic wasting disease in deer

Content Provider	Springer Nature Link
Author	Lawson, Andrew Song, Hae Ryoung
Copyright Year	2009
Abstract	In this paper, we propose a semiparametric survival model to investigate the pattern of spatial and temporal variation in disease prevalence of chronic wasting disease (CWD) in wild deer in Wisconsin over the years 2002 and 2006. The semiparametric survival model we suggested allows to build a more flexible model than the parametric model with fewer parametric assumptions by modeling the baseline hazard using a Gamma process prior. Based on the proposed model, we investigate the geographical distribution of CWD, and assess the effect of sex on disease prevalence. We use a Bayesian hierarchical framework where latent parameters capture temporal and spatial trends in disease incidence, incorporating sex and spatially correlated random effects. We also propose bivariate baseline hazard which change over age and time simultaneously to adopt different effects of age and time on the baseline hazard. Inference is carried out by using MCMC simulation techniques in a fully Bayesian framework. Our results suggest that disease has been spreaded mainly in the disease eradication zone and male deer show a significantly higher infection probability than female deer.
Starting Page	559
Ending Page	571
Page Count	13
File Format	PDF
ISSN	13528505
Journal	Environmental and Ecological Statistics
Volume Number	17
Issue Number	4
e-ISSN	15733009
Language	English
Publisher	Springer US
Publisher Date	2009-07-19
Publisher Place	Boston
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Chronic wasting disease (CWD) Semiparametric model Survival analysis Bayesian hierarchical model Evolutionary Biology Statistics Mathematical Biology in General Ecology
Content Type	Text
Resource Type	Article
Subject	Statistics and Probability Environmental Science Statistics, Probability and Uncertainty

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