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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.As an increasing quantity of HIV/AIDS surveillance data becomes available, methods need to be developed to combine forecasting and surveillance activities to effectively use such data with an eye to improving the validity of projections and guiding where interventions are targeted. A model is described which uses simple empirical inputs to forecast the incidence and prevalence of HIV infection, number of AIDS cases, and mortality by age, sex, and sentinel group. The model can be used to produce HIV infection curves, based upon past and present data, which are then projected into the short-term future. The approach allows a closer relationship between forecasting and surveillance activities, and more accurate estimates validated to data. The model inputs are an estimate of the HIV prevalence, country demographic data, and a profile of the sexual risk of HIV infection by age. These inputs are then used to project HIV incidence, prevalence, the 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; modeling mixed risk behavior HIV epidemics in southeast Asia; demographic indicators; and targeting a preventive vaccine by age group. |
