An age- and sex-structured HIV epidemiological model: features and applications.
An important challenge in modelling the human immunodeficiency virus (HIV)/acquired immunodeficiency syndrome (AIDS) epidemic is to use the increasing quantity of disease surveillance data to validate estimates and forecasts. Presented is a novel model for forecasting HIV incidence by age and sex and among sentinel groups for which data are available. This approach permits a closer relationship between forecasting and surveillance activities, and more accurate estimates validated to data. As inputs the model uses an estimate of the HIV prevalence, country demographic data, and a profile of the sexual risk of HIV infection by age, to project HIV incidence, prevalence, number of AIDS cases and population. The following examples of the use of the model are given: forecasting HIV incidence in East Africa, by age, sex, and among pregnant women; 3-5-year forecasts of HIV incidence; modelling mixed risk behaviour HIV epidemics in South-east Asia; demographic indicators; and targeting a preventive vaccine by age group.
Low-Beer
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Department of Geography, University of Cambridge, England.
Stoneburner
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RL
D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D002648:Child; D002675:Child, Preschool; D005260:Female; D005544:Forecasting; D015658:HIV Infections / Q000453:epidemiology*; D006801:Humans; D007223:Infant; D007231:Infant, Newborn; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D011159:Population Surveillance / Q000379:methods*; D011247:Pregnancy; D015203:Reproducibility of Results; D017678:Sex Distribution; D013785:Thailand / Q000453:epidemiology; D014454:Uganda / Q000453:epidemiology