Characterizing HIV Transmission Networks Through Sensitivity Analyses and Simulations
Improving HIV treatment and prevention efforts is enabled by characterizing the transmission network. Phylogenetic analyses are important for inferring these networks. However, there are no statistically grounded analysis methods for inferring transmission network structure from viral phylogenies, in addition to numerous analysis steps required to infer phylogenies from sequenced read data. My research uses sensitivity analyses and simulations to identify what features in the HIV phylogeny reliably correspond to features in the HIV transmission network, and how that is influenced by uncertainty generated during the analysis steps. This provides a quantitative measure of how well existing approaches approximate the transmission network.