Bayesian Hierarchical Spatial Modeling of COVID-19 Cases in Bangladesh

This research aimed to investigate the spatial autocorrelation and heterogeneity throughout Bangladesh’s 64 districts. Moran I Geary C are used measure autocorrelation. Different conventional models, such as Poisson-Gamma Poisson-Lognormal, Conditional Autoregressive (CAR) Model, Convolution modified CAR have been employed detect heterogeneity. Bayesian hierarchical methods via Gibbs sampling implement these models. The best model is selected using Deviance Information Criterion. Results revealed Dhaka has highest relative risk due city’s high population density growth rate. study identifies which district districts adjacent that also a risk, allows for appropriate actions be taken by government agencies communities mitigate effect.