Diarrhea Morbidities in Small Areas : Accounting for Non-Stationarity in Sociodemographic Impacts using Bayesian Spatially Varying Coefcient Modelling - Osei, F.B. (2020)
Model-based estimation of diarrhea risk and understanding the dependency on sociodemographic factors is important for prioritizing interventions. It is unsuitable to calibrate regression model with a single set of coefcients, especially for large spatial domains. For this purpose, we developed a Bayesian hierarchical varying coefcient model to account for non-stationarity in the covariates. We used the integrated nested Laplace approximation for parameter estimation. Diarrhea morbidities in Ghana motivated our empirical study. Results indicated improvement regarding model ft and epidemiological benefts. The fndings highlighted substantial spatial, temporal, and spatio-temporal heterogeneities in both diarrhea risk and the coefcients of the sociodemographic factors. Diarrhea risk in periurban and urban districts were 13.2% and 10.8% higher than rural districts, respectively. The varying coefcient model indicated further details, as the coefcients varied across districts. A unit increase in the proportion of inhabitants with unsafe liquid waste disposal was found to increase diarrhea risk by 11.5%, with higher percentages within the south-central parts through to the south-western parts. Districts with safe and unsafe drinking water sources unexpectedly had a similar risk, as were districts with safe and unsafe toilets. The fndings show that site-specifc interventions need to consider the varying efects of sociodemographic factors.