Discriminating Between Premigration and Postmigration HIV Acquisition Using Surveillance Data. (1st October 2021) - Pantazis, Nikos; Rosinska, Magdalena; van Sighem, Ard; Quinten, Chantal; Noori, Teymur; Burns, Fiona; Cortes Martins, Helena; Kirwan, Peter D.; O'Donnell, Kate; Paraskevis, Dimitrios; Sommen, Cécile; Zenner, Dominik; et al.
Abstract : Background: Migrant populations are overrepresented among persons diagnosed with HIV in the European Union and the European Economic Area. Understanding the timing of HIV acquisition (premigration or postmigration) is crucial for developing public health interventions and for producing reliable estimates of HIV incidence and the number of people living with undiagnosed HIV infection. We summarize a recently proposed method for determining the timing of HIV acquisition and apply it to both real and simulated data. Methods: The considered method combines estimates from a mixed model, applied to data from a large seroconverters' cohort, with biomarker measurements and individual characteristics to derive probabilities of premigration HIV acquisition within a Bayesian framework. The method is applied to a subset of data from the European Surveillance System (TESSy) and simulated data. Findings: Simulation study results showed good performance with the probabilities of correctly classifying a premigration case or a postmigration case being 87.4% and 80.4%, respectively. Applying the method to TESSy data, we estimated the proportions of migrants who acquired HIV in the destination country were 31.9%, 37.1%, 45.3%, and 45.2% for those originating from Africa, Europe, Asia, and other regions, respectively. Conclusions: Although the considered method was initially developed for cases with multiple biomarkers' measurements, its performance, when applied to data where only one CD4 count per individual is available, remains satisfactory. Application of the method to TESSy data, estimated that a substantial proportion of HIV acquisition among migrants occurs in destination countries, having important implications for public health policy and programs.