Back to research feed

Journal of acquired immune deficiency syndromes (1999)

October 12, 2026 · via Europe PMC

Strengthening Panama's HIV Viral Load Testing Network through a Phased Optimization Strategy: A Retrospective Program Assessment, 2021-2025.

Juarez SI, Rugg AA, Gutierrez C, +5 more, Bhairavabhotla R

Journal ArticleAbstract only — full text under license

AI summary — for doctors, generated from the abstract only

Panama's stepwise reorganisation of its HIV viral load testing network was followed by much higher testing coverage and viral suppression, though the design cannot prove it caused the gains.

What was studied

Retrospective programme assessment of Panama's national HIV viral load network from 2021 to 2025, including a baseline review of two reference labs and 13 ART clinics, followed by redistribution of testing, regional capacity and GeneXpert for priority samples.

Key findings

  • Viral load coverage rose from 47% to 89% and viral suppression from 78% to 94%.
  • Tests performed rose from 6,967 to 15,897 while the ART cohort grew 25%.
  • Turnaround was about 1 week or 10 days for routine tests and about 24 hours for priority GeneXpert testing.

Clinical relevance

Timely, accessible viral load monitoring underpins ART programmes, and this shows decentralised capacity and point-of-care platforms can speed results in resource-limited settings.

Who should care

Infectious Disease

Limitations

Uncontrolled before-after programme data, so the improvements are trends and the authors explicitly caution against causal interpretation.

Where viral load access is limited, regional testing and rapid platforms for priority patients are worth considering, recognising the evidence is observational.

This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.

Abstract

BACKGROUND

In 2021, Panama identified structural and operational gaps in its national HIV viral load (HIV VL) testing network, in the context of low testing coverage. A phased strategy was implemented to strengthen testing capacity, quality, geographic access, and referral pathways.

SETTING

Panama's national HIV VL testing network.

METHODS

We conducted a retrospective program assessment of the national HIV VL network optimization strategy implemented from 2021-2025. A 2021 baseline assessment included two HIV VL reference laboratories and 13 antiretroviral therapy (ART) clinics representing 93% of the ART cohort reported in the programmatic data used for the assessment. Findings informed phased optimization, including redistribution of testing, establishment of regional capacity, and differentiated use of GeneXpert for priority HIV VL testing. Programmatic data were used to assess HIV VL coverage, viral suppression, testing distribution, and turnaround time.

RESULTS

HIV VL testing increased from 6,967 tests in 2021 to 15,897 in 2025, while the ART cohort increased 25%, from 14,560 to 18,200. HIV VL coverage increased from 47% to 89%, and viral suppression from 78% to 94%. Testing was redistributed across the laboratory network. Post-optimization routine turnaround time was approximately 1 week at the regional Veraguas laboratory and 10 days at ICGES; priority GeneXpert testing provided results in approximately 24 hours.

CONCLUSION

Panama's phased optimization was associated with expanded HIV VL testing access, increased coverage, redistributed testing capacity, and more timely testing pathways. These findings represent programmatic trends and should not be interpreted as causal effects of the strategy.

DOI

10.1097/QAI.0000000000003977

PMID

42863138

Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.

Want more like this?

Browse more from the feed. A free account unlocks the full feed, saving and communities.

Back to the research feed

Create a free account · Sign in