Ensuring equitable access to quality HIV care for affected populations in complex sociocultural settings: Lessons from Nigeria
Bibliographic record
Abstract
BACKGROUND: HIV infection remains one of the major diseases of public health importance globally with an estimated 40.4 million deaths and 39 million people living with the virus by 2022. About 40 countries are on track to achieve a 95% reduction in AIDS-related mortality by 2030. This progress is however challenged by sub-optimal progress among affected populations (AP), also known as key populations (AP). Society for Family Health (SFH), with about 3 decades of experiences in AP program present in this paper an account of key strategies and innovations in adapting its service provisioning efforts to rapidly changing socio-cultural and political barriers to service delivery among AP in northern Nigeria. METHODS: SFH is an indigenous nonprofit, non-political, non-governmental organization in Nigeria that has pioneered HIV interventions among AP across most parts of Nigeria. SFH has successfully tailored its interventions to the unique cultural and religious diversity of Nigeria. The predominantly Islamic-orientated population in the northern part of the country and the Christian-oriented population in the southern part, which is culturally inclined to Western orientations, have all been considered in SFH's comprehensive approach instilling confidence in the effectiveness of its strategies. SFH implemented 3 key strategies to circumvent pervasive socio-cultural and political barriers that hindered successful AP program implementation in northern Nigeria by addressing structural barriers, systems barriers (service-provider and client-related barriers) and by deployment of innovations to optimize program performance. For the purposes of this retrospective cross-sectional study, deidentified routine aggregate program data was utilized to conduct secondary data analysis. RESULTS: Between 2019 - 2023, SFH tested a total of 324,391 AP of whom 30,581 were found to be HIV positives yielding overall positivity rate of 9.4%. People who inject drugs (PWID) demonstrated sustained high positivity rate over the 5 years. About 80% of those initiated on treatment were female sex workers (FSW) and men who have sex with men (MSM) contributing to 41.8% and 38.5% respectively. Year on year, the number of AP receiving ART more than doubled in 2020 and grew by 85%, 43% and 30% in 2021, 2022 and 2023 respectively. There was progressive increase in VL testing coverage between Year 1 - Year 3 across all the three AP typologies and then steady decline between Year 4 - Year 5. Between Year 1 - Year 2 the viral load suppression was at 91% with remarkable improvement to 97% in Year 3 and Year 4 and at 99% in Year 5. CONCLUSION: The implementation of people-centered, evidence-driven, culturally, and religiously sensitive program enabled SFH to reach a high number of AP in northern Nigeria. This helps improve equity in access to care by AP. There are specific program areas that need continuous improvement including strategies to reach MSM to avoid the evolution of new structural barriers; expansion of PWID programming to optimize all aspects of harm reduction; and sustained sensitization, education, and awareness creation among AP to improve uptake of PrEP and other prevention and care services.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".