Combining biomarker and virus phylogenetic models improves HIV-1 epidemiological source identification.

ABSTRACT: To identify and stop active HIV transmission chains new epidemiological techniques are needed. Here, we describe the development of a multi-biomarker augmentation to phylogenetic inference of the underlying transmission history in a local population. HIV biomarkers are measurable biological quantities that have some relationship to the amount of time someone has been infected with HIV. To train our model, we used five biomarkers based on real data from serological assays, HIV sequence data, and target cell counts in longitudinally followed, untreated patients with known infection times. The biomarkers were modeled with a mixed effects framework to allow for patient specific variation and general trends, and fit to patient data using Markov Chain Monte Carlo (MCMC) methods. Subsequently, th

SUBMITTER: Lundgren E 

PROVIDER: S-EPMC9455879 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature