Assessing transmission attribution risk from simulated sequencing data in HIV molecular epidemiology.

ABSTRACT:

Background

HIV molecular epidemiology (ME) is the analysis of sequence data together with individual-level clinical, demographic, and behavioral data to understand HIV epidemiology. The use of ME has raised concerns regarding identification of the putative source in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. Here we assessed the risks of ME using simulated HIV genetic sequencing data.

Methods

We simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying direct transmissions using different HIV sequence lengths, and population samp

SUBMITTER: Nascimento FF 

PROVIDER: S-EPMC10994139 | biostudies-literature | 2024 May

REPOSITORIES: biostudies-literature