Drug resistance mutations (DRM) emerge in HIV-1 viruses through selective pressure during antiviral treatment (ART). Acquired drug resistance rates vary depending on duration of ART and type of prescribed regimen. Drug resistance can then be transmitted and reduces the chances of long-lasting successful ART. The rate at which transmitted drug resistance (TDR) mutations persist is likely to be multifactorial and have been shown to vary considerably for individual mutations (Castro et al. 2013). In case of the UK population infected by HIV-1 it is known (Mourad et al. 2015) that the majority of DRMs are transmitted by treatment-naive patients. Having a deeper understanding of virus transmission and drug resistance mechanisms is important as it will lead to improvements of current treatment policies.
In this study we develop mathematical models of DRM transmissions in HIV-1, and detect new potential DRMs. We collaborate with the The UK HIV Drug Resistance Database team to apply our models and obtain predictions for the HIV-1 sequence data in the UK.