A0871
Title: Causal structural learning and application in epidemiology
Authors: Changcheng Li - Dalian University of Technology (China) [presenting]
Abstract: The Population-based HIV Impact Assessment (PHIA) is an ongoing project that conducts nationally representative HIV-focused surveys for measuring national and regional progress toward UNAIDS 90-90-90 targets, the primary strategy to end the HIV epidemic. The PHIA survey offers a unique opportunity to better understand the key factors that drive the HIV epidemics in the most affected countries in sub-Saharan Africa. A novel causal structural learning algorithm is proposed to discover important covariates and potential causal pathways for 90-90-90 targets. Existing constrained-based causal structural learning algorithms are quite aggressive in edge removal. The proposed algorithm preserves more information about important features and potential causal pathways. It is applied to the Malawi PHIA (MPHIA) data set and leads to interesting results. The proposed algorithm is further compared and validated using BIC and using Monte Carlo simulations, and it is shown that it achieves improvement in true positive rates in important feature discovery over existing algorithms.
