Category Archives: Prevention

INTRODUCTION: HIV remains a global health challenge with a reported 39 million people living with HIV (PLHIV) in 2022. Sub-Saharan Africa, Asia and the Pacific are home to 82% of...

INTRODUCTION: Mobility-from overnight travel to permanent migration-can reduce service access and increase HIV risk, driving the epidemic in sub-Saharan Africa (SSA). This scoping review described mobility measures used in HIV...

OBJECTIVES: The aim of this systematic review was to analyse, synthesise and review existing research on body image among people living with HIV (PLWH). Specifically, the review investigated the relationship...

BACKGROUND: Despite increasing backlash against harm reduction efforts and the need to understand the risk environments encountered by people who inject drugs (PWID), a quantitative systematic review on public injecting...

BACKGROUND: Adolescents living with HIV face unique challenges as they gain greater independence while transitioning into adulthood. They must adjust their self-management activities and take primary responsibility for their health,...

OBJECTIVES: To explore how artificial intelligence (AI) can enhance infodemiology, which distributes and scans information in the electronic medium, to process social media posts for HIV preexposure prophylaxis (PrEP). DESIGN:...

OBJECTIVE: to analyze clinical trials that assessed the effectiveness of technologies for healthy lifestyles in people with HIV. METHOD: A systematic review, conducted in five databases, with association of controlled...

Transporting and driving long distances might be associated with an increased risk of contracting HIV in truck drivers, which is recognized as a link to network transmission of HIV among...

Background: Adolescents and young adults (AYA) make up a significant share of the world’s burden of HIV and other sexually transmitted infections (STI). Self-testing can increase testing coverage and strengthen the...

Background Although a growing body of evidence supports zero risk of sexual HIV transmission from a person with sustained virological suppression, known as U=U (undetectable equals untransmittable), data have been...

Background Machine learning (ML) shows promise for sexually transmitted infection (STI) risk prediction, but systematic evidence of its effectiveness remains fragmented. Methods We systematically searched six electronic databases, three preprint...

The Undetectable = Untransmittable (U=U) message is a cornerstone of HIV-related public health communication, yet global levels of awareness and acceptance remain unclear across key populations. This study aimed to...