Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2015 Jul 31;10(7):e0131828.
doi: 10.1371/journal.pone.0131828. eCollection 2015.

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

Affiliations

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

Jörg Schüpbach et al. PLoS One. .

Abstract

Background: HIV 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 results: Inno-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.

Conclusions: Inno-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.

PubMed Disclaimer

Conflict of interest statement

Competing Interests: DC is an employee of Institut Dr. Viollier AG. CA is an employee of Clinique de la Source. MB is an employee of Labor Synlab Luzern. There are no patents, products in development or marketed products to declare. This does not alter the authors' adherence to all the PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Number of HIV notifications and incident HIV infections over time, as obtained by performance-based and window-based incident infection estimates.
Panels on top labeled “All” show the data for all patients, lower panels show the data per risk category (MSM, men who have sex with men; HET, heterosexual transmission; IDU, intravenous drug use; UNK, unknown transmission pathway). In all panels, the blue curve with the circle symbols denotes the annual number of HIV notifications, and the black curve without symbols shows the estimated number of incident infections (means and their 95% confidence intervals). The top panels also show the results obtained with the 10 individual algorithms (grey lines in the background).
Fig 2
Fig 2. Incident infection estimates based on models adjusting for possible selection bias.
S1, no adjustment; S2, model with adjustment for selection bias exerted by seeking early testing after a suspected exposure; S3, model with adjustment for seeking medical attention due to symptoms of acute HIV infection. Refer to Methods for further explanations. The blue curve without symbols on top in each panel shows the number of HIV notifications.

References

    1. Anonymous (2014) HIV and AIDS estimates (2012). UNAIDS.
    1. Anonymous (2014) HIV- und STI-Fallzahlen 2013: Berichterstattung, Analysen und Trends BAG Bulletin: 351–380.
    1. Janssen RS, Satten GA, Stramer SL, Rawal BD, O'Brien TR, Weiblen BJ, et al. (1998) New testing strategy to detect early HIV-1 infection for use in incidence estimates and for clinical and prevention purposes. Jama 280: 42–48. - PubMed
    1. Murphy G, Parry JV (2008) Assays for the detection of recent infections with human immunodeficiency virus type 1. Euro Surveill 13. - PubMed
    1. Le Vu S, Pillonel J, Semaille C, Bernillon P, Le Strat Y, Meyer L, et al. (2008) Principles and uses of HIV incidence estimation from recent infection testing—a review. Euro Surveill 13. - PubMed

Publication types