Nikos Pantazis1, Magdalena Rosinska2, Ard van Sighem3, Chantal Quinten4, Teymur Noori4, Fiona Burns5, Helena Cortes Martins6, Peter D Kirwan7,8, Kate O'Donnell9, Dimitrios Paraskevis1, Cécile Sommen10, Dominik Zenner11, Anastasia Pharris4. 1. Department of Hygiene, Epidemiology and Medical Statistics, National and Kapodistrian University of Athens, Medical School, Athens, Greece. 2. Department of Epidemiology of Infectious Diseases and Surveillance, National Institute of Public Health-National Institute of Hygiene, Warsaw, Poland. 3. Stichting HIV Monitoring, Amsterdam, the Netherlands. 4. European Centre for Disease Prevention and Control, Stockholm, Sweden. 5. Institute for Global Health, University College London, London, United Kingdom. 6. National Institute of Health, Lisbon, Portugal. 7. Medical Research Council Biostatistics Unit, University of Cambridge, Cambridge, United Kingdom. 8. Blood Safety, Hepatitis, Sexually Transmitted Infections and HIV Division, Public Health England, London, United Kingdom. 9. HSE-Health Protection Surveillance Centre, Dublin, Ireland. 10. Santé Publique France, Saint-Maurice, France; and. 11. Centre for Global Public Health, Institute for Population Health Sciences, Queen Mary University London, London, United Kingdom.
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.
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.