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The Systems That Watch Us
- Dec 5, 2025
- 7 min read
by Rynn Myles
In the first two installments, I explored the quieter, everyday forms of HIV stigma — the kinds that slip into how we talk about responsibility, compliance, and worthiness without ever naming themselves as stigma. Those pieces centered what happens between people and within programs. This installment steps further back to look at something harder to confront: how stigma is baked into the very architecture of our systems. It is embedded in the policies we defend, the research we fund, and the institutional habits we excuse as “standard practice.”
These structures reflect not only our public health priorities but our anxieties, misunderstandings, and unspoken fears. When those fears guide decision-making, they shape outcomes long before anyone walks into a clinic.
This installment examines how HIV stigma becomes institutional — subtle enough to pass as logic, professional enough to pass as neutral, but powerful enough to steer the entire field.
Anxiety Rather Than Evidence
Public health loves to claim the authority of data. But if you trace the history of HIV policy, you will find that anxiety is the real foundation. Long before there was reliable data on HIV transmission, prevention, or treatment, policies were created out of fear: fear of queer liberation, fear of drug use, fear of Black and brown communities, fear of sexuality itself. These fears drove early surveillance laws, mandatory testing proposals, criminal statutes, and disclosure requirements. They justified intrusive data collection and police involvement under the banner of “prevention.” Look at the earliest HIV surveillance laws: states began requiring name-based reporting of people diagnosed with HIV before they even understood how HIV was transmitted. These systems weren’t designed for care; they were designed for tracking. Some states built registries accessible to law enforcement, allowing police to use a person’s HIV status as evidence of “intent” in prostitution or drug-related
cases.
Mandatory testing proposals followed the same logic. In the late 1980s and early 1990s, lawmakers across the country pushed for mandatory testing for people in carceral settings, pregnant people, sex workers, and even entire neighborhoods deemed “high risk,” all without evidence that these measures reduced transmission. Criminal statutes emerged from the same panic. By the mid-90s, more than 30
states had HIV-specific criminal laws that punished activities posing no real risk of transmission, such as spitting or biting. People were charged with felonies for not disclosing their status during consensual sex, even when they used protection or had an undetectable viral load.
Disclosure requirements (policies forcing people to reveal their HIV status to partners, employers, housing authorities, or the state) were treated as “common sense,” even though they were rooted in the belief that people living with HIV were inherently dangerous unless managed. This is what it looks like when anxiety becomes policy. The fears that built these systems didn’t fade once better science arrived. They hardened. Many modern HIV policies still operate on the assumption that increased monitoring automatically improves outcomes, even though the evidence for this is thin.
Funding and Institutional Priorities
Research agendas tell the truth about what institutions value. And the truth is that the most necessary questions rarely receive funding. Instead, money flows toward questions that can be answered quickly, quantified neatly, or fit into familiar biomedical frames.
A study tracking PrEP adherence? Funded.
A project measuring viral suppression over twelve months? Funded.
A behavioral intervention trial where success is measured by appointment attendance? Funded again.
These questions are not unimportant. But they are easy. They are familiar. They privilege individual behavior over structural change.
Now imagine submitting a proposal that asks:
● What does long-term engagement look like for someone who is unhoused, uninsured, and regularly displaced by policing?
● How does HIV criminalization impact mental health, community trust, and clinical outcomes?
● How does institutional racism within healthcare shape treatment access and mortality rates?
These questions are messy. They require time, community leadership, and a willingness to document answers that challenge institutional comfort. They rarely receive funding — not because they lack value, but because they threaten the field.
Documenting Risk Without Challenging It
Even when research claims to focus on improving outcomes, it often ends up documenting disparities rather than addressing what creates them. This is one of the most persistent patterns in HIV literature. Studies measure “risk behaviors” but not the conditions that shape those behaviors. Reports detail which populations are least likely to be virally suppressed, but not the structural forces that make sustained suppression difficult. Entire communities are framed as “high risk,” while the systems
that destabilize their lives remain invisible.
Researchers can publish paper after paper about disparities while ignoring the inequities that produce them. Institutions can say they are “following the data,” even though the data was generated by systems that consistently undercount, misclassify, or overlook marginalized people.
To understand how that happens, you have to look at how the data is built. Most public health datasets begin with who gets counted. Surveillance systems often rely on people who access medical care, which means anyone who avoids clinics because of cost, mistrust, or stigma disappears from the numbers. Black trans women who avoid hospitals after discriminatory experiences. Undocumented people who fear their information being shared with law enforcement. People who use drugs who know a clinic visit can put them on a registry they never agreed to. When entire communities are systematically pushed out of data collection, the disparities researchers report later are already predetermined.
Then there is misclassification, which sounds technical but is really about whose identities are flattened to fit what the system can measure. Trans people are often recorded based on sex assigned at birth. Latine and Afro-Latine communities are frequently lumped into broad ethnic categories that hide cultural and regional differences that matter for prevention and care. Multiracial people get placed in a single box. When the categories themselves fail, the resulting “data” becomes a distorted mirror of reality. Blurry where precision is needed, neat where complexity exists.
Even when communities do get counted accurately, the questions that researchers choose to ask shape the story long before the results appear in a journal. Questions that interrogate systems (housing discrimination, policing, medical racism, poverty-wage economies, anti-trans legislation) rarely get approved for major funding streams because they don’t promise a clean or convenient intervention. Instead, the questions that receive the most support are the ones that keep the focus on individual behavior. Asking why someone didn’t use a condom is easy to fund because it suggests the solution is to get them to try harder. Asking why a community lacks stable housing is harder because it points toward failures of policy, not individuals.
This creates an illusion of objectivity that shields institutions from accountability. A chart showing higher incidence in a Black neighborhood can be framed as a “risk profile,” even when the neighborhood’s lack of clinics, lack of transportation, history of over-policing, and decades of divestment are left out of the analysis. The data is treated as a neutral observation rather than evidence of structural neglect. When institutions claim neutrality, they erase the fact that these choices have real consequences for real people who become trapped in categories created by
someone else’s fear.
Once those categories are built, they get repeated everywhere: in grant proposals, program eligibility requirements, media talking points, and federal priority lists. A community that is coded as “high risk” doesn’t get resources to transform the conditions they live in. They get surveillance, behavioral interventions, or short-term pilot programs that measure their compliance. Meanwhile, the systems that created the conditions for HIV vulnerability in the first place remain untouched and unexamined, protected by the belief that the data itself is objective simply because it exists.
This is how a field can stay busy producing studies, publishing findings, drafting reports while leaving the underlying harm fully intact. The work appears rigorous and scientific, but it quietly maintains the very structures it claims to study.
Institutional Survival and the Quiet Erasure of Community Centered Work
Institutions have survival instincts just like people do. The difference is that institutional survival often comes at the expense of community survival. Many organizations publicly claim to serve community needs, yet their budgets show a very different set of priorities. Community-led programs, peer navigation, culturally specific initiatives, and grassroots partnerships are often the first things cut when funding tightens. Meanwhile, administrative salaries, branding budgets, and institutional partnerships remain untouched.
When community members raise concerns, the response is predictable. Leaders talk vaguely about “future planning.” They claim they have not received negative feedback, even though they have never created a meaningful process for feedback to begin with. They reassure everyone that decisions are made with “long term impact” in mind, even when the immediate harm is right in front of them.
This is the pattern: institutions protect their own legitimacy before protecting the people they claim to serve. They shrink the services that most directly meet community needs. They distance themselves from the programs that challenge the limits of their comfort. They over invest in their reputation and underinvest in the communities experiencing the epidemic most intensely.
This is how people become invisible inside the very structures created to support them. It is not overt. It is not loud. It is a quiet, bureaucratic erasure that treats marginalized communities as optional.
The Pattern We Can No Longer Pretend Not to See
When you step back, the pattern becomes unmistakable:
● Policies shaped by fear rather than evidence.
● Research shaped by convenience rather than courage.
● Data shaped by inequality rather than accuracy.
● Institutions shaped by self-preservation rather than community survival.
Together, these forces build a system that treats some lives as central and others as peripheral.
This is not a series of coincidences. It is a structure. A structure built by people who inherited fears and failed to question them. A structure that makes stigma feel natural because it has existed for so long.
Looking Ahead
The next installment will trace the cycle created by stigma: how it moves from belief to behavior to policy and back again, shaping both HIV care and everyday life. By connecting these patterns to education, mental health, housing, and criminal legal systems, the cycle becomes visible. From there, I will examine what it takes to interrupt that cycle — not only through program design but through cultural shifts, institutional accountability, and community-grounded practices. The fifth installment will imagine what HIV care and research could look like when stigma no longer shapes the blueprint.
References
Centers for Disease Control and Prevention (CDC): HIV Criminalization Laws in the
U.S.
Centers for Disease Control and Prevention (CDC): HIV Surveillance Overview
Positive Women’s Network – HIV Criminalization Resources
The Center for HIV Law & Policy – HIV Criminalization Laws & Policy Tracker
CDC: Health Disparities in HIV
National Institutes of Health (NIH): Structural Racism and Health
UNAIDS — HIV Stigma & Discrimination
HIV Justice Network — Policy, Criminalization, & Global Trends
