Getting to 90-90-90: Experiences from the MaxART Early Access to ART for All (EAAA) Trial in Eswatini.
Fiona WalshShaukat KhanTill BärnighausenAnita HettemaCharlotte LejeuneSikhathele MazibukoCharmaine Khudzie MlamboRia ReisYvette FlemingGavin KhumaloMandisa ZwaneVelephi OkelloDonna SpiegelmanPublished in: Current HIV/AIDS reports (2020)
The MaxART Consortium demonstrated that "Fast Track," a problem-solving approach, was effective at increasing testing coverage in the community. Compared with baseline data at 3 months prior to the start of the Fast Track, there was a 273% proportional increase in HIV tests conducted among adolescent males, adolescent females, and adult men, and 722% over baseline for adolescent males. The MaxART EAAA trial further showed that implementation of the Treat All policy was associated with significant two-fold shorter time from enrollment into care to ART initiation than under the standard CD4+ cell threshold-based treatment guidelines. Finally, through the MaxART trial, Eswatini was able to identify areas for further investment, including addressing the system-side barriers to routine viral load monitoring, and designing and implementing innovative community-based approaches to reach individuals who were not more routinely accessing HIV testing and counseling services. As low- and middle-income countries adopt the Treat All approach in their national HIV care and treatment guidelines, further implementation science research is needed to understand and address the system-level barriers to achieving the benefits of Treat All for HIV-infected individuals and those at risk.
Keyphrases
- hiv infected
- hiv testing
- mental health
- healthcare
- antiretroviral therapy
- men who have sex with men
- quality improvement
- young adults
- primary care
- study protocol
- clinical trial
- clinical practice
- phase iii
- hiv positive
- public health
- phase ii
- human immunodeficiency virus
- affordable care act
- palliative care
- hepatitis c virus
- childhood cancer
- stem cells
- big data
- hiv aids
- chronic pain
- cell therapy
- artificial intelligence
- pain management
- deep learning
- machine learning
- smoking cessation