title: Estimating HIV incidence using dates of both HIV and AIDS diagnoses.
abstract: Knowledge of HIV incidence is important to formulate sensible strategies aimed at controlling the HIV/AIDS epidemic. Back-projection is one of the methods for reconstructing the HIV incidence curve from AIDS incidence data. However, because of the low risk of developing AIDS during the first few years after infection, precise estimates of HIV incidence for the recent past are unlikely if we use AIDS incidence data only. As a result there have been recent attempts to use, not only the date of AIDS diagnosis, but also to use the date of their first positive HIV test. The objective of this paper is to incorporate into back-projection the additional information provided by those individuals who have tested HIV positive but have not yet developed AIDS. This adds information on a very large number of other individuals, and provides the hope that the precision of back-projection is improved considerably. The date of a positive HIV test or an AIDS diagnosis of an individual, whichever comes first, is used in a generalized convolution equation for the purpose of back-projection. The method is illustrated by an application to Australian HIV and AIDS data. Study results show that dramatic improvement in precision is gained for estimates of HIV incidence in recent years when both HIV and AIDS diagnosis dates are used on all individuals.
authors.affiliation: Department of General Practice and Public Health, University of Melbourne, Carlton, VIC 3053, Australia. j.cui@gpph.unimelb.edu.au
authors.forename: J
authors.initials: J
authors.lastname: Cui
authors.forename: N G
authors.initials: NG
authors.lastname: Becker
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000175:diagnosis / Q000453:epidemiology*; D000328:Adult; D001315:Australia / Q000453:epidemiology; D005260:Female; D006678:HIV / Q000302:isolation & purification; D015658:HIV Infections / Q000175:diagnosis / Q000453:epidemiology*; D006801:Humans; D015994:Incidence; D008954:Models, Biological; D016016:Proportional Hazards Models; D013997:Time Factors