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 individuals involved in direct transmission events. This could result in harm ranging from stigma to criminal prosecution in some jurisdictions. In this study, we simulated social networks of men-who-have-sex-with-men, calibrating the simulations to data from San Diego, USA. We used these networks to simulate consensus and next-generation sequence (NGS) data to evaluate the risks of identifying the source of HIV transmissions at the individual level using different source attribution methods. We showed that source attribution using consensus sequences rarely infers transmission pairs with high confidence, but is still useful for population studies. In contrast, source attribution using NGS data was much more accurate in identifying the source of a direct transmission event, but for only a small percentage of transmission pairs.

About Fabrícia

Fabricia has a Bachelor of Microbiology and Immunology from the Federal University of Rio de Janeiro and a Masters in Molecular and Cell Biology from the Oswaldo Cruz Foundation, Rio de Janeiro. She did her PhD at the University of Sydney, Australia, on the evolution of endogenous retroviruses (ERVs). After that, she did her postdoctoral research at the National Evolutionary Center, USA; and she was a Newton International Fellow from the Royal Society and carried out her research on ERVs at the University of Oxford, UK. She is currently a Research Associate at Imperial College London, UK, working on molecular epidemiology of SARS-CoV-2 and HIV. Her currently work is on quantifying the risks and benefits of HIV molecular epidemiology.