Shocking gaps in Colombia’s HIV data are hiding who’s most at risk; activists and health experts say better, disaggregated statistics are essential so services actually reach trans and gender-diverse people where stigma, violence and discrimination still block access.

Essential Takeaways

  • High reported prevalence: UNAIDS data from 2019 indicate very high HIV prevalence among trans people in Colombia, around 21.4%, versus 17.0% in men who have sex with men.
  • Data blind spots: National surveillance lacks representative, disaggregated data for trans men, non-binary people and many gender-diverse groups.
  • Barriers beyond biology: Stigma, discrimination, violence and unequal access to health services increase vulnerability and reduce testing and treatment uptake.
  • Practical fix: Collect routine, group-specific data, invest in community-led surveys and protect confidentiality to rebuild trust.
  • Why it matters: Without solid numbers, programmes risk missing the people who need prevention, testing and treatment most urgently.

Why the current figures feel incomplete and worrying

The headline numbers , 21.4% HIV prevalence among trans people reported by UNAIDS in 2019 , are alarming and emotionally heavy, but they’re also partial. Public-health reporting in Colombia still treats trans and gender-diverse populations as invisible in many official data sets, which creates a false sense of certainty. According to UNAIDS and other international reports, the data that do exist point to a serious burden, yet major groups like trans men and non-binary people are often left out of surveys and routine surveillance.

That gap matters because numbers drive budgets and services. If health ministries and funders only see aggregated statistics, programmes may keep targeting the same groups while leaving others under-served. So the first step is simple and practical: measure better.

How stigma, violence and health-system barriers skew the picture

Qualitative research from Colombia and the region makes the rest of the story clear: the drivers of HIV risk here are social and institutional as much as biomedical. People who face discrimination in clinics, who’ve been subject to violence or who fear being outed will avoid testing and treatment, and that avoidance warps prevalence estimates. WHO guidance on transgender health emphasises that health systems must be safe and welcoming; otherwise people slip through the net.

Policy-makers should read this as a systems failure rather than an individual choice problem. Training for health staff, anti-discrimination policies and secure, confidential routes to testing and care can make services accessible and, crucially, make the data collected more reliable.

What better data collection looks like, in practice

Good surveillance doesn’t mean bureaucratic complexity; it means asking the right questions in the right way. That includes routinely recording gender identity options beyond binary choices in national surveys and clinic intake forms, and ensuring sample sizes are sufficient to produce representative estimates for subgroups such as trans men, trans women and non-binary people.

Community-led surveys and respondent-driven sampling have worked elsewhere in Latin America to reach hidden networks, and participatory methods improve trust and response rates. Colombia could combine routine health information with periodic, well-designed mapping and behavioural surveys to get both breadth and depth.

Privacy, ethics and community trust , non-negotiables for useful data

Collecting more granular data raises real concerns about confidentiality and misuse. That’s why any expansion of surveillance must be paired with clear privacy safeguards and transparent data governance. International bodies including WHO and UNAIDS stress community engagement and leadership in how data are collected, interpreted and used.

Practical steps include anonymising records, training staff on sensitive handling of identity data, and giving communities control over how findings are reported. When people trust the process, they’re more likely to test and to remain in care , which in turn gives decision-makers the evidence they need.

Why better numbers will change lives, not just reports

When you can see who’s most affected and why, you can tailor prevention, testing and treatment to real needs: mobile testing in areas people actually use, hormone-compatible care pathways, mental-health support and anti-violence interventions. International experience shows that targeted services built with communities improve outcomes and reduce new infections.

Colombia has advocates, researchers and international partners ready to help. The missing piece is political will to invest in disaggregated, ethical data and the community-led programmes those data would unlock.

It's a small change that can make every service safer and more effective.

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