Low-Beer D, Stoneburner R L
Department of Geography, University of Cambridge, England.
Bull World Health Organ. 1997;75(3):213-21.
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.
在对人类免疫缺陷病毒(HIV)/获得性免疫缺陷综合征(AIDS)疫情进行建模时,一个重要挑战是利用日益增多的疾病监测数据来验证估计值和预测结果。本文介绍了一种新颖的模型,用于按年龄、性别以及在有可用数据的哨点人群中预测HIV发病率。这种方法使得预测与监测活动之间的关系更为紧密,并且能根据数据对估计值进行更精确的验证。该模型将HIV流行率估计值、国家人口数据以及按年龄划分的HIV感染性风险概况作为输入,以预测HIV发病率、流行率、艾滋病病例数和人口数。以下是该模型的应用示例:按年龄、性别以及在孕妇中预测东非的HIV发病率;对HIV发病率进行3至5年的预测;对东南亚混合风险行为的HIV疫情进行建模;人口指标;以及按年龄组确定预防性疫苗的目标人群。