Abstract

BackgroundIn line with the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 target, Norway aims for at least 90% of people living with HIV (PLHIV) to know their HIV-status. We produced current estimates of the number of PLHIV and undiagnosed population in Norway, overall and for six key subpopulations: Norwegian-born men who have sex with men (MSM), migrant MSM, Norwegian-born heterosexuals, migrant Sub-Saharan Africa (SSA)-born heterosexuals, migrant non-SSA-born heterosexuals and people who inject drugs.MethodsWe used the European Centre for Disease Prevention and Control (ECDC) HIV Modelling Tool on Norwegian HIV surveillance data through 2018 to estimate incidence, time from infection to diagnosis, PLHIV, and the number and proportion undiagnosed. As surveillance data on CD4 count at diagnosis were not collected in Norway, we ran two models; using default model CD4 assumptions, or a proxy for CD4 distribution based on Danish national surveillance data. We also generated alternative overall PLHIV estimates using the Spectrum AIDS Impact Model, to compare with those obtained from the ECDC tool.ResultsEstimates of the overall number of PLHIV in 2018 using different modelling approaches aligned at approximately 5000. In both ECDC models, the overall number undiagnosed decreased continuously from 2008. The proportion undiagnosed in 2018 was lower using default model CD4 assumptions (7.1% [95%CI: 5.3–8.9%]), than the Danish CD4 proxy (10.2% [8.3–12.1%]). This difference was driven by results for heterosexual migrants. Estimates for Norwegian-born MSM, migrant MSM and Norwegian-born heterosexuals were similar in both models. In these three subpopulations, incidence in 2018 was < 30 new infections, and the number undiagnosed had decreased in recent years. Norwegian-born MSM had the lowest estimated number of undiagnosed infections (45 [30–75], using default CD4 assumptions) and undiagnosed fraction (3.6% [2.4–5.7%], using default CD4 assumptions) in 2018.ConclusionsResults allow cautious confidence in concluding that Norway has achieved the first UNAIDS 90–90-90 target, and clearly highlight the success of prevention strategies among MSM. Estimates for subpopulations strongly influenced by migration remain less clear, and future modelling should appropriately account for all-cause mortality and out-migration, and adjust for time of in-migration.

Highlights

  • In line with the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 target, Norway aims for at least 90% of people living with HIV (PLHIV) to know their HIV-status

  • This provides the basis for the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90–90-90 target for ending the AIDS epidemic by 2030, the first of which aims for 90% of PLHIV to know their HIV status by 2020 [8]

  • There were an estimated 355 undiagnosed infections (259–449) in 2018 (Table 2, Fig. 3) which yields an undiagnosed fraction of 7.1% (5.3–8.9) (Table 2)

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Summary

Introduction

In line with the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90-90-90 target, Norway aims for at least 90% of people living with HIV (PLHIV) to know their HIV-status. While infection with HIV continues to be a major global public health issue [1], antiretroviral treatment (ART) has successfully reduced morbidity and mortality in people living with HIV (PLHIV) [2,3,4], and prevented onward transmission [5,6,7] This provides the basis for the Joint United Nations Programme on HIV/AIDS (UNAIDS) 90–90-90 target for ending the AIDS epidemic by 2030, the first of which aims for 90% of PLHIV to know their HIV status by 2020 [8]. The majority of countries in the European region of the World Health Organisation have produced national estimates using either the HIV modelling tool from the European Centre for Disease Prevention and Control (ECDC) [16], or the AIDS Impact Model in Spectrum (denoted as ‘Spectrum’) [12]. The ECDC modelling tool can model key subpopulations, in addition to the general epidemic [16]

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