Inference of direction, diversity, and frequency of HIV-1 transmission using approximate Bayesian computation
Ethan O. Romero-Severson, Ingo Bulla, Nick Hengartner, Inês Bártolo, Ana Abecasis, José M. Azevedo-Pereira, Nuno Taveira, Thomas Leitner
This study uses approximate Bayesian computation to infer HIV-1 transmission direction, diversity, and frequency, finding that a single transmission model better explains the data than ongoing transmission.
bioRxiv · Aug 24, 2016 · PreprintEpidemiology