  Group testing, a method that screens subjects in pooled samples rather than
individually, has been employed as a cost-effective strategy for chlamydia
screening among Iowa residents. In efforts to deepen our understanding of
chlamydia epidemiology in Iowa, several group testing regression models have
been proposed. Different than previous approaches, we expand upon the varying
coefficient model to capture potential age-varying associations with chlamydia
infection risk. In general, our model operates within a Bayesian framework,
allowing regression associations to vary with a covariate of key interest. We
employ a stochastic search variable selection process for regularization in
estimation. Additionally, our model can integrate random effects to consider
potential geographical factors and estimate unknown assay accuracy
probabilities. The performance of our model is assessed through comprehensive
simulation studies. Upon application to the Iowa group testing dataset, we
reveal a significant age-varying racial disparity in chlamydia infections. We
believe this discovery has the potential to inform the enhancement of
interventions and prevention strategies, leading to more effective chlamydia
control and management, thereby promoting health equity across all populations.
