title: Bayesian spatio-temporal random coefficient time series (BaST-RCTS) model of infectious disease.
abstract: This paper proposes a new method, using Bayesian approach, to analyze time series data of infectious diseases which have both temporal and spatial variational structures. Standard ways to model heteroscedastic time series are the ARCH-type models. However, from an empirical standpoint, there is a need to include spatial effect into time series analysis to make allowance for confounder and ecological biases. On the basis of random coefficient autoregressive model, our model takes account of spatial correlated/uncorrelated heterogeneity. To assure the applicability of our model, we set up hypothesis framework before analyzing. It was proved that our model could provide the first two conditional moments of ARCH-type models. The empirical study of bacillary dysentery data also illustrated that our model could make accurate and precise approximations.
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu 610041, China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
authors.affiliation: School of Medical Science, University of Auckland, Auckland 1123, New Zealand.
authors.forename: Xingyu
authors.initials: X
authors.lastname: Zhang
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu 610041, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Ma
authors.affiliation: Department of Biostatistics, School of Public Health, University of Washington, Seattle 98195, USA.
authors.forename: Xiaohua Andrew
authors.initials: XA
authors.lastname: Zhou
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu 610041, China.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Disease Control and Emergency Response Office, Chinese Center for Disease Control and Prevention, Beijing 102206, China.
authors.forename: Zijian
authors.initials: Z
authors.lastname: Feng
authors.affiliation: West China School of Public Health, Sichuan University, Chengdu 610041, China. Electronic address: lixiaosong1101@126.com.
authors.forename: Xiaosong
authors.initials: X
authors.lastname: Li
mesh_terms: D001499:Bayes Theorem; D003141:Communicable Diseases / Q000453:epidemiology*; D004403:Dysentery / Q000453:epidemiology*; D006801:Humans; D008954:Models, Biological
keywords: ARCH-type model; Bayesian analysis; Infectious disease; Spatial effect; Time series analysis