The Last-Mile HIV Monitoring Gap: What Happened When the Funding Stopped
For two decades, Uganda’s HIV response leaned heavily on a quiet, community-level workforce: the mentor mothers and community health workers who traced patients, supported adherence, and kept people on treatment. In early 2025, a sudden shift in donor funding pulled much of that layer away almost overnight. What it exposed was a fragile truth — the last mile of HIV care depended on people and monitoring systems that were never institutionalised. This brief examines the gap that opened, and the data question at its centre.
We write about this carefully. This is a live, serious public-health situation affecting real patients. Our focus is narrow and specific: the monitoring and adherence-tracking gap — the part of the problem that is fundamentally about data and community reach, where a data-infrastructure partner can genuinely help.
What happened
Following the January 2025 funding freeze, community-based HIV services in Uganda came under acute strain. Reporting documented that community-led monitoring programmes dropped from three to one — roughly a 67% reduction in monitoring capacity. Community health workers and “mentor mothers,” who had been paid modest allowances to provide adherence support and trace patients lost to follow-up, could no longer afford to do the work. As one health worker described it, the mentor mothers stopped coming, follow-ups stopped, and a gap opened in services.
The clinical facilities largely kept running. What frayed was the connective tissue — the community-level tracing, adherence support and monitoring that keeps patients engaged with care between clinic visits. That is the last mile, and it is exactly where data and follow-up matter most.
Why community monitoring is a data problem
Effective adherence support rests on knowing, in near-real time: who is enrolled, who is due for a refill, who has missed one, and who has fallen out of care and needs tracing. Historically much of this ran on paper and on the memory and relationships of individual community workers. When those workers left, the knowledge left with them. A resilient system would hold that information in a structured, transferable data layer — so that continuity does not depend entirely on one funded individual.
The evidence and infrastructure gap
- How many patients lost community-level adherence support, and what happened to their engagement with care?
- Can a lightweight digital monitoring layer sustain adherence tracking at lower cost than the model that just collapsed?
- Where communities or government step in to fill the gap, what actually works?
These are questions that matter enormously to health funders, the Ministry of Health, and the organisations trying to hold the response together — and answering them requires exactly the kind of community-level data infrastructure that was missing in the first place.
Basket builds resilient community-monitoring infrastructure
Basket Advisory builds registration and field-monitoring systems that hold patient-engagement data in a structured, transferable layer — so adherence monitoring does not collapse when one funded worker leaves. We partner with health organisations as the data-infrastructure instrument, never as a clinical provider.
Discuss a research partnership →How Basket Advisory contributes
- Structured community-monitoring data — enrolment, refills, follow-up status — that survives staff turnover.
- Field tools for community health workers to record and act on adherence data.
- Tracing workflows that flag patients who need re-engagement.
- Aggregate reporting for the health system and funders — anonymised and consented.
Rebuilding community HIV monitoring?
We partner as the data-infrastructure layer for community health monitoring — helping make adherence tracking resilient, low-cost and transferable. Let’s talk about how Basket fits your programme.
Start a conversation →Related reading
- Donation traceability in health outreach
- Mental health in Uganda’s informal economy
- Uganda’s invisible workforce: the data gap
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Working through it
Errors to avoid
The business case
How Basket Advisory helps
Breaking down what you need
Costs and timing
Investing in the future
The short version
Details people miss
Applying this to your situation
A note on doing this well
Making it work for you
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