Mapping projects for expanding rapid HIV testing in key populations, Brazil, 2004-2021.
Lidiane da Silveira Gouvea ToledoAna Isabella Sousa AlmeidaFrancisco Inácio BastosPublished in: Cadernos de saude publica (2024)
The HIV/AIDS epidemic remains a persistent and real issue, especially in key populations such as men who have sex with men (MSM), travestis and transgender persons. Projects for expanding rapid HIV testing are strategic initiatives aimed at the earliest possible identification of individuals' serological status and thus early treatment, screening of sex partners, and upscaling of preventive actions to interrupt the transmission chain. This study thus maps, describes, and systematizes the projects for expanding rapid HIV testing implemented from 2004 to 2021 in Brazil, highlighting the on-going contribution of civil society organizations and discussing the interoperability and cooperation resulting from public governance processes. We selected 67 documents for analysis, including 30 scientific publications retrieved from electronic databases and 37 documents produced by government institutions and nongovernmental organizations (NGOs). Find Out (Fique Sabendo), I Want to Get Tested (Quero Fazer), The Time is Now (A Hora É Agora), Live Better Knowing (Viva Melhor Sabendo), and Live Better Knowing Young (Viva Melhor Sabendo Jovem) were the projects mapped. Results show that the projects have used strategies adapted to the key population, such as mobile testing units, peer education, and innovative community engagement approaches. Such actions were enabled by effective cooperation and interoperability between participating stakeholders, especially NGOs.
Keyphrases
- hiv testing
- men who have sex with men
- quality improvement
- hiv positive
- hiv aids
- healthcare
- loop mediated isothermal amplification
- mental health
- electronic health record
- human immunodeficiency virus
- antiretroviral therapy
- social media
- mass spectrometry
- genetic diversity
- combination therapy
- high density
- middle aged
- deep learning