Evidence map›Paper›PMID 41962558›Full record

ArticleAIDS (London, England)2026

Improving cohort coverage estimation using a data triangulation framework: the Swiss HIV Cohort Study example.

Jessy J Duran Ramirez, Roger D Kouyos, Irene Abela, Charles Beguelin, Marco Bongiovanni, Philip Bruggmann, Alexandra Calmy, Matthias Cavassini, Alexia Cusini, Mirjam de Roche and 20 more

Abstract read
In one paragraph

Article in AIDS (London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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0cells of the map it votes in
1citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

30 authors.

Jessy J Duran RamirezDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
Roger D KouyosDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
Irene AbelaDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
Charles BeguelinDepartment of Internal Medicine, Hospital Center of Bienne, Bienne.
Marco BongiovanniDivision of Infectious Diseases, Ente Ospedaliero Cantonale, Lugano.
Philip BruggmannArud Centre for Addiction Medicine, Zurich.
Alexandra CalmyHIV Unit, Department of Infectious Diseases, Geneva University Hospitals, Geneva.
Matthias CavassiniDepartment of Infectious Diseases, Lausanne University Hospital.
Alexia CusiniDivision of Infectious Diseases, Cantonal Hospital of Grisons, Chur.
Mirjam de RocheInfectious Diseases, Department of Internal Medicine, Spital STS AG, Thun.
Luigia ElziDivision of Infectious Diseases, Regional Hospital Bellinzona, Bellinzona.
Andrée FriedlDivision of Infectious Diseases and Infection Prevention, Cantonal Hospital Baden, Baden.
Rosamaria FulchiniKantonsspital Münsterlingen, Münsterlingen.
Chistoph FuxDepartment of Infectious Diseases and Infection Prevention, Kantonsspital Aarau.
David HaerryChair Positive Council.
Benjamin HampelDepartment of Public and Global Health, Epidemiology, Biostatistics and Prevention Institute, University of Zurich.
Markus HeroldMaihofpraxis, Lucerne.
Philipp KaiserDivision of Infectious Diseases and Infection Prevention, Cantonal Hospital Luzern, Luzern.
Helen KovariCenter for Infectious Diseases, Klinik im Park, Zurich.
Patrick SchmidDivision of Infectious Diseases, Infection Prevention and Travel Medicine, HOCH Health Ostschweiz, Cantonal Hospital St. Gallen, University Teaching and Research Hospital, St. Gallen.
Delphine SculierPrivate Practice Office, Geneva.
Marcel StöckleDivision of Infectious Diseases and Hospital Epidemiology, University Hospital Basel, University of Basel, Basel.
Philip E TarrUniversity Center for Internal Medicine, Infectious Diseases and Hospital Epidemiology Service, Kantonsspital Baselland, University of Basel, Bruderholz.
Frédéric TissotPrivate Practice, Lausanne, Switzerland.
Jonathan TschoppPrivate Practice, Lausanne, Switzerland.
Gilles WandelerDepartment of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern.
Andri RauchDepartment of Infectious Diseases, Inselspital, Bern University Hospital, University of Bern, Bern.
Huldrych F GünthardDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
Katharina KusejkoDepartment of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich.
Swiss HIV Cohort Study (SHCS)

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo improve estimation of cohort coverage in the Swiss HIV Cohort Study (SHCS) using a data triangulation framework that compares SHCS data with multiple external data sources.

designRetrospective longitudinal analysis of the SHCS.

methodsCohort coverage of HIV diagnoses, AIDS diagnoses, and antiretroviral therapy (ART) uptake was triangulated across SHCS data (1985-2023), national HIV/AIDS surveillance (1985-2023), longitudinal antiretroviral therapy (ART) sales data (2017-2024), and a targeted literature comparison. Temporal trends in cohort coverage were assessed, and demographic representativeness was evaluated by sex, age, HIV acquisition mode, and region. Mean cohort coverage estimates were calculated for three outcomes: HIV and AIDS diagnoses (Step 1) and ART uptake (Step 2).

resultsOver 38 years, mean SHCS coverage was 62.4% for HIV diagnoses, 74.0% for AIDS, and 64.9% for ART uptake, consistent with literature-based estimates. Coverage of HIV diagnoses declined in recent years, and geographical heterogeneity was observed. The SHCS remained broadly representative across most subgroups; however, females, older adults, and people with heterosexually acquired HIV or using psychoactive substances were underrepresented, while people on single-tablet and salvage ART regimens were overrepresented.

conclusionsA data triangulation framework provides a practical approach for monitoring cohort coverage and representativeness. While the SHCS captures a broadly representative sample of diagnosed individuals, tailored strategies are needed to improve inclusion of underrepresented subgroups and maintain cohort coverage. Sustained monitoring is essential to ensure that cohort-based research remains generalizable and continues to inform clinical care and public health responses in Switzerland and beyond.

Indexed as

HIV InfectionsAdolescentAdultAgedAnti-Retroviral AgentsFemaleHumansLongitudinal StudiesMaleMiddle AgedRetrospective StudiesSwitzerlandYoung AdultAnti-Retroviral Agentscohort coveragecohort studydata triangulationHIV epidemicHIV surveillancerepresentativeness

Identifiers

PMID41962558
PMCPMC13566368

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.