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Background:

Estimates of the size of the undiagnosed HIV-infected population are important to understand the HIV epidemic and to plan interventions, including “test-and-treat” strategies.

Methods:

We developed a multi-state back-calculation model to estimate HIV incidence, time between infection and diagnosis, and the undiagnosed population by CD4 count strata, using surveillance data on new HIV and AIDS diagnoses. The HIV incidence curve was modelled using cubic splines. The model was tested on simulated data and applied to surveillance data on men who have sex with men in The Netherlands.

Results:

The number of HIV infections could be estimated accurately using simulated data, with most values within the 95% confidence intervals of model predictions. When applying the model to Dutch surveillance data, 15,400 (95% confidence interval [CI]= 15,000, 16,000) men who have sex with men were …