title: Semi-parametric spatial joint modeling of HIV and HSV-2 among women in Kenya.
abstract: Several diseases have common risk factors. The joint modeling of disease outcomes within a spatial statistical context may provide more insight on the interaction of diseases both at individual and at regional level. Spatial joint modeling allows for studying of the relationship between diseases and also between regions under study. One major approach for joint spatial modeling is the multivariate conditional autoregressive approach. In this approach, it is assumed that all the covariates in the study have linear effects on the multiple response variables. In this study, we relax this linearity assumption and allow some covariates to have nonlinear effects using the penalized regression splines. This model was used to jointly model the spatial variation of human immunodeficiency virus (HIV) and herpes simplex virus-type 2 (HSV-2) among women in Kenya. The model was applied to HIV and HSV-2 prevalence data among women aged 15-49 years in Kenya, derived from the 2007 Kenya AIDS indicator survey. A full Bayesian approach was used and the models were implemented in WinBUGS software. Both diseases showed significant spatial variation with highest disease burdens occurring around the Lake Victoria region. There was a nonlinear association between age of an individual and HIV and HSV-2 infection. The peak age for HIV was around 30 years while that of HSV-2 was about 40 years. A positive significant spatial correlation between HIV and HSV-2 was observed with a correlation of 0.6831(95% CI: 0.3859, 0.871).
authors.affiliation: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, 3201 Pietermaritzburg, South Africa.
authors.forename: Elphas
authors.initials: E
authors.lastname: Okango
authors.affiliation: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, 3201 Pietermaritzburg, South Africa.
authors.forename: Henry
authors.initials: H
authors.lastname: Mwambi
authors.affiliation: School of Mathematics, Statistics and Computer Science, University of KwaZulu-Natal, Private Bag X01, 3201 Pietermaritzburg, South Africa; Mathematics and Informatics Department, Taita Taveta University College, P.O Box 635-80300, Voi, Kenya.
authors.forename: Oscar
authors.initials: O
authors.lastname: Ngesa
authors.affiliation: Division of Epidemiology and Biostatistics, School of Public Health, University of Witwatersrand, 27 St Andrews Road, 2193 Parktown, South Africa.
authors.forename: Thomas
authors.initials: T
authors.lastname: Achia
mesh_terms: D000293:Adolescent; D000328:Adult; D001499:Bayes Theorem; D060085:Coinfection; D005260:Female; D015658:HIV Infections / Q000453:epidemiology* / Q000523:psychology / Q000821:virology; D015497:HIV-1 / Q000502:physiology*; D006558:Herpes Genitalis / Q000453:epidemiology* / Q000523:psychology / Q000821:virology; D018258:Herpesvirus 2, Human / Q000502:physiology*; D006801:Humans; D007630:Kenya / Q000453:epidemiology; D008875:Middle Aged; D015233:Models, Statistical; D015995:Prevalence; D012307:Risk Factors; D012725:Sexual Behavior / Q000523:psychology; D012923:Social Class