Investigating Spatio-Temporal Pattern of Relative Risk of Tuberculosis in Kenya Using Bayesian Hierarchical Approaches

Proper understanding of global distribution of infectious diseases is an important part of disease management and policy making. However, data are subject to complexities caused by heterogeneities across host classes and space-time epidemic processes. This paper seeks to suggest or propose Bayesian spatio-temporal model for modeling and mapping tuberculosis relative risks in space and time as well identify risks factors associated with the tuberculosis and counties in Kenya with high tuberculosis relative risks. In this paper, we used spatio-temporal Bayesian hierarchical models to study the pattern of tuberculosis relative risks in Kenya. The Markov Chain Monte Carlo method via WinBUGS and R packages were used for simulations and estimation of the parameter estimates. The best fitting model is selected using the Deviance Information Criterion proposed by Spiegelhalter and colleagues. Among the spatio-temporal models used, the Knorr-Held model with space-time interaction type III and IV fit the data well but type IV appears better than type III. Variation in tuberculosis risk is observed among Kenya counties and clustering among counties with high tuberculosis relative risks. The prevalence of HIV is identified as the determinant of TB. We found clustering and heterogeneity of TB risk among high rate counties and the overall tuberculosis risk is slightly decreasing from 2002-2009. We proposed that the Knorr-Held model with interaction type IV should be used to model and map Kenyan tuberculosis relative risks. Interaction of TB relative risk in space and time increases among rural counties that share boundaries with urban counties with high tuberculosis risk. This is due to the ability of models to borrow strength from neighboring counties, such that nearby counties have similar risk. Although the approaches are less than ideal, we hope that our study provide a useful stepping stone in the development of spatial and spatio-temporal methodology for the statistical analysis of risk from tuberculosis in Kenya.

Correlates of Parental Choice of Child Discipline Methods in Ghana: A Multilevel Modeling Approach

This study applied multilevel modeling to investigate the impact of observed predictors and different levels or groups that households belong, on parents’ choice of discipline methods using data from 8156 households derived from a nationwide survey by the Ghana Statistical Service (GSS) in 2011. The aim of the study is to provide in-depth information on why parents choose particular discipline methods as corrective measures to reduce unwanted child behaviour in the present and to increase desirable ones in the future. The results of the study show that, religion and age-group of household heads have significant effect on household’s likelihood to choose physical discipline methods whereas the wealth index of a household and ethnicity of the household head, have significant effect on households’ likelihood to choose non-physical and psychological aggression methods. The results further show significant contextual effect on the differences in choices of parents at the household and regional levels. The choice of physical discipline methods by parents was consistent across households and regional levels unlike non-physical and psychological aggression methods whose application varied across the regions. Households in the Northern, Eastern and Volta regions mostly chose to apply physical discipline methods whereas in the Upper West, Western and Northern regions the most chosen discipline methods were non-physical discipline methods. Psychological aggression discipline methods were predominantly applied in the Upper East, Central and Northern regions of the country.