Low levels of viral suppression among refugees and host nationals accessing antiretroviral therapy in a Kenyan refugee camp
Bibliographic record
Abstract
Refugees and host nationals who accessed antiretroviral therapy (ART) in a remote refugee camp in Kakuma, Kenya (2011–2013) were compared on outcome measures that included viral suppression and adherence to ART. This study used a repeated cross-sectional design (Round One and Round Two). All adults (≥18 years) receiving care from the refugee camp clinic and taking antiretroviral therapy (ART) for ≥30 days were invited to participate. Adherence was measured by self-report and monthly pharmacy refills. Whole blood was measured on dried blood spots. HIV-1 RNA was quantified and treatment failures were submitted for drug resistance testing. A remedial intervention was implemented in response to baseline testing. The primary outcome was viral load <5000 copies/mL. The two study rounds took place in 2011-2013. Among eligible adults, 86% (73/85) of refugees and 84% (86/102) of Kenyan host nationals participated in the Round One survey; 60% (44/73) and 58% (50/86) of Round One participants were recruited for Round Two follow-up viral load testing. In Round One, refugees were older than host nationals (median age 36 years, interquartile range, IQR 31, 41 vs 32 years, IQR 27, 38); the groups had similar time on ART (median 147 weeks, IQR 38, 64 vs 139 weeks, IQR 39, 225). There was weak evidence for a difference in the proportion of refugees and host nationals who were virologically suppressed (<5000 copies/mL) after 25 weeks on ART (58% vs 43%, p = 0.10) and no difference in the proportions suppressed at Round Two (74% vs 70%, p = 0.66). Mean adherence within each group in Round One was similar. Refugee status was not associated with viral suppression in multivariable analysis (adjusted odds ratio: 1.69, 95% CI 0.79, 3.57; p = 0.17). Among those not suppressed at either timepoint, 69% (9/13) exhibited resistance mutations. Virologic outcomes among refugees and host nationals were similar but unacceptably low. Slight improvements were observed after a remedial intervention. Virologic monitoring was important for identifying an underperforming ART program in a remote facility that serves refugees alongside host nationals. This work highlights the importance of careful laboratory monitoring of vulnerable populations accessing ART in remote settings.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".