Evidence of health-system resilience in the uptake of antiretroviral therapy in Sierra Leone during the COVID-19 pandemic: a nationwide retrospective study
Bibliographic record
Abstract
Abstract Background Sustained access to and uptake of antiretroviral therapy (ART) among people living with HIV is a critical component of the HIV response. Limited data exist evaluating the extent to which the COVID-19 pandemic may have disrupted HIV treatment services in Sierra Leone. This study aims to describe differential patterns in the uptake of ART before, during, and after the COVID-19 emergency period in the country. Methods We conducted a retrospective cross-sectional study using aggregated secondary program data extracted from the national health information system to reflect the uptake of ART in three time periods: March 2019-February 2020 (pre-COVID-19); March 2020-February 2021 (during COVID-19) and March 2021- February 2022 (post COVID-19). Outcomes were compared across the three time periods and stratified by sex and by region. Results There was a steady increase in the overall ART uptake from 365,326 pre-COVID-19 to 416,069 during COVID-19 and 518, 426 post-COVID-19, which masks the more significant relative decline affecting new ART initiations due to COVID-19: pre-COVID-19 (8, 958), during COVID-19 (8,777), and post-COVID-19 (13, 996). A sharp decline in new ART initiation was consistent with the surge in COVID-19, reflected geographical variability, but showed no sex difference. Conclusion Variations on the impact of COVID-19 across regions underscores the need for targeted interventions to mitigate the impact of future structural shocks on HIV services. The steady increase in overall uptake of ART suggests resiliency to a significant disruption and reflects pre-emptive health systems adaptations. The notable increase in new initiations in the post-COVID-19 period could suggest catch-up of delayed new initiations or more also reflect increasing HIV incidence and the critical importance of sustained investments for resiliency.
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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 | 0.011 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".