Challenges in modelling the proportion of undiagnosed HIV infections in Sweden

Euro Surveill. 2019 Apr;24(14):1800203. doi: 10.2807/1560-7917.ES.2019.24.14.1800203.

Abstract

BackgroundSweden has a low HIV prevalence. However, among new HIV diagnoses in 2016, the proportion of late presenters and migrants was high (59% and 81%, respectively). This poses challenges in estimating the proportion of undiagnosed persons living with HIV (PLHIV).AimTo estimate the proportion of undiagnosed PLHIV in Sweden comparing two models with different demands on data availability and modelling expertise.MethodsAn individual-based stochastic simulation model of HIV positive populations (SSOPHIE) and the incidence method of the European Centre for Disease Prevention and Control (ECDC) HIV Modelling Tool were applied to clinical, surveillance and migration data from Sweden 1980-2016.ResultsSSOPHIE estimated that the proportion of undiagnosed PLHIV in 2013 was 26% (n = 2,100; 90% plausibility range (PR): 900-5,000) for all PLHIV, 17% (n = 600; 90% PR: 100-2,000) for men who have sex with men (MSM), 35% in male (n = 300; 90% PR: 200-700) and 34% in female (n = 400; 90% PR: 200-800) migrants from sub-Saharan Africa (SSA). The estimates for the ECDC model in 2013 were 21% (n = 2,013; 95% confidence interval (CI): 1,831-2,189) for all PLHIV, 15% (n = 369; 95% CI: 299-434) for MSM and 21% (n = 530; 95% CI: 436-632) for migrants from SSA.ConclusionsThe proportion of undiagnosed PLHIV in Sweden is uncertain. SSOPHIE estimates had wide PR. The ECDC model estimates were unreliable because migration was not accounted for. Better migration data and estimation methods are required to obtain reliable estimates of proportions of undiagnosed PLHIV in similar settings.

Keywords: HIV infection; MSM; epidemiology; men who have sex with men; migration; sexually transmitted infections.

MeSH terms

  • Adult
  • Africa South of the Sahara / ethnology
  • Female
  • HIV Infections / diagnosis
  • HIV Infections / epidemiology*
  • HIV Infections / transmission*
  • Homosexuality, Male / statistics & numerical data*
  • Humans
  • Incidence
  • Male
  • Models, Statistical
  • Prevalence
  • Risk Factors
  • Sweden / epidemiology
  • Transients and Migrants / statistics & numerical data*
  • Young Adult