Highlights•Machine learning is increasingly used to predict and understand drug resistance
in HIV.•Phylogenetics helps to track the emergence and spread of HIV drug resistance …

Background Resistance to antiretroviral therapy (ART) among people living with human
immunodeficiency virus (HIV) compromises treatment effectiveness, often leading to …

Background Combination antiretroviral therapy (cART) has significantly reduced HIV
morbidity and mortality in both developed and developing countries. However, the …

Drug resistance mutations (DRMs) appear in HIV under treatment pressure. DRMs are
commonly transmitted to naive patients. The standard approach to reveal new DRMs is to …

Background The impact and cost-effectiveness of couples' voluntary HIV counselling and
testing (CVCT) has not been quantified in real-world settings. We quantify cost-per-HIV …

ABSTRACT A betulinic acid-based compound, bevirimat (BVM), inhibits HIV-1 maturation by
blocking a late step in protease-mediated Gag processing: the cleavage of the capsid …

Background Deep sequencing could improve understanding of HIV treatment failure and
viral population dynamics. However, this tool is often inaccessible in low-and middle-income …

The global intensification of antiretroviral therapy (ART) can lead to increased rates of HIV
drug resistance (HIVDR) mutations in treated and also in ART-naive patients. ART-naive HIV …

Background Antiretroviral therapy has led to AIDS being a chronic disease. Nevertheless,
the presence of constantly emerging drug resistance mutations poses a challenge to clinical …

HIV continues to spread among vulnerable heterosexual (HET), Men-having-Sex with Men
(MSM) and intravenous drug user (IDU) populations, influenced by a complex array of …