Evaluating the impact of COVID-19 on the HIV care continuum across global income levels: a mixed-methods systematic review
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic caused significant disruptions to global healthcare systems, including essential services along the HIV care continuum (HCC). While several studies have examined these impacts in specific countries or populations, limited evidence exists on cross-country differences in service disruptions, barriers, and facilitators stratified by national income levels. METHODS: We conducted a mixed-methods systematic review following the Joanna Briggs Institute methodology and PRISMA 2020 guidelines. We searched CINAHL, MEDLINE, Embase, and CAB Direct for quantitative and qualitative studies published between March 2020 and January 2024. Eligible studies assessed the pandemic's impact on one or more stages of the HIV care continuum, including prevention, testing, linkage to care, treatment engagement, antiretroviral therapy (ART) adherence, and viral suppression. Data were extracted, appraised, and synthesized using a convergent integrated approach across low-, middle-, and high-income countries as defined by the World Bank. RESULTS: A total of 200 studies were included. The most frequently disrupted services were HIV testing, prevention (including pre-exposure prophylaxis [PrEP] use), and medical appointments, particularly in high- and middle-income countries. ART adherence and viral suppression showed greater resilience across all settings. Structural barriers, such as lockdowns, healthcare repurposing, and transportation limitations, were widespread, while digital exclusion, stigma, and socioeconomic inequities disproportionately affected marginalized populations. Key facilitators included telemedicine, multi-month dispensing of ART and PrEP, community-based service delivery, and national-level adaptations. The extent of disruption and success of mitigation strategies varied by income level, reflecting differences in health system preparedness and flexibility. CONCLUSIONS: The COVID-19 pandemic disrupted HIV care globally, with variation across income levels and care continuum stages. Health system resilience, equity in access, and pre-existing adaptive infrastructure significantly shaped outcomes. Findings highlight the need to institutionalize flexible, decentralized, and equity-informed service models to strengthen routine HIV care and pandemic preparedness.
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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 | 0.032 | 0.117 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.012 | 0.011 |
| Bibliometrics | 0.019 | 0.020 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".