Evidence map›Paper›PMID 26230082›Full record

ArticlePloS one2015

Decreasing Proportion of Recent Infections among Newly Diagnosed HIV-1 Cases in Switzerland, 2008 to 2013 Based on Line-Immunoassay-Based Algorithms.

Jörg Schüpbach, Christoph Niederhauser, Sabine Yerly, Stephan Regenass, Meri Gorgievski, Vincent Aubert, Diana Ciardo, Thomas Klimkait, Günter Dollenmaier, Corinne Andreutti and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 48% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors at 11 institutions in 1 country.

Jörg SchüpbachUniversity of Zurich, Institute of Medical Virology, Swiss National Center for Retroviruses, Winterthurerstrasse 190, CH-8057, Zurich, Switzerland.
Christoph NiederhauserBlood Transfusion Service, Swiss Red Cross Berne, Berne, Switzerland.
Sabine YerlyGeneva University Hospitals, Laboratory of Virology, Genève, 14, Switzerland.
Stephan RegenassUniversity Hospital, Clinic for Immunology, Zurich, Switzerland.
Meri GorgievskiUniversity of Berne, Institute of Infectious Diseases, Berne, Switzerland.
Vincent AubertUniversity Hospital, Service of Immunology and Allergy, University Hospital Center, Lausanne, Switzerland.
Diana CiardoInstitut Dr. Viollier AG, Basel, Switzerland.
Thomas KlimkaitUniversity of Basel, Institute for Medical Microbiology, Basel, Switzerland.
Günter DollenmaierZentrum für Labormedizin St. Gallen, St. Gallen, Switzerland.
Corinne AndreuttiClinique de la Source, Laboratoire, Lausanne, Switzerland.
Gladys MartinettiEnte ospedaliero cantonale, Servizio di microbiologia, Bellinzona, Switzerland.
Marcel BrandenbergerLabor Synlab Luzern, Lucerne, Switzerland.
Martin D GebhardtSwiss Federal Office of Public Health, CH-3003, Berne, Switzerland.
Clinique de La Source · CHEnte Ospedaliero Cantonale · CHFederal Office of Public Health · CHSwiss Red Cross · CHUniversity Hospital of Zurich · CHUniversity of Basel · CHUniversity of Bern · CHUniversity of Geneva · CHUniversity of Teacher Education Lucerne · CHUniversity of Zurich · CHZentrum für Labormedizin · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHIV surveillance requires monitoring of new HIV diagnoses and differentiation of incident and older infections. In 2008, Switzerland implemented a system for monitoring incident HIV infections based on the results of a line immunoassay (Inno-Lia) mandatorily conducted for HIV confirmation and type differentiation (HIV-1, HIV-2) of all newly diagnosed patients. Based on this system, we assessed the proportion of incident HIV infection among newly diagnosed cases in Switzerland during 2008-2013. METHODS AND

resultsInno-Lia antibody reaction patterns recorded in anonymous HIV notifications to the federal health authority were classified by 10 published algorithms into incident (up to 12 months) or older infections. Utilizing these data, annual incident infection estimates were obtained in two ways, (i) based on the diagnostic performance of the algorithms and utilizing the relationship 'incident = true incident + false incident', (ii) based on the window-periods of the algorithms and utilizing the relationship 'Prevalence = Incidence x Duration'. From 2008-2013, 3'851 HIV notifications were received. Adult HIV-1 infections amounted to 3'809 cases, and 3'636 of them (95.5%) contained Inno-Lia data. Incident infection totals calculated were similar for the performance- and window-based methods, amounting on average to 1'755 (95% confidence interval, 1588-1923) and 1'790 cases (95% CI, 1679-1900), respectively. More than half of these were among men who had sex with men. Both methods showed a continuous decline of annual incident infections 2008-2013, totaling -59.5% and -50.2%, respectively. The decline of incident infections continued even in 2012, when a 15% increase in HIV notifications had been observed. This increase was entirely due to older infections. Overall declines 2008-2013 were of similar extent among the major transmission groups.

conclusionsInno-Lia based incident HIV-1 infection surveillance proved useful and reliable. It represents a free, additional public health benefit of the use of this relatively costly test for HIV confirmation and type differentiation.

Indexed as

Epidemiological MonitoringAdultAlgorithmsCross-Sectional StudiesFemaleHIV-1HIV-2HIV AntibodiesHIV InfectionsHumansImmunoassayMaleSwitzerlandHIV Antibodies

Identifiers

PMID26230082
PMCPMC4521810
OpenAlexW2151138053

What OpenQuestion holds

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Registered trials

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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.