Boily M C, Mâsse B
Groupe de Recherche en Epidémiologie, Hôpital du St-Sacrement, Université Laval.
Can J Public Health. 1997 Jul-Aug;88(4):255-65. doi: 10.1007/BF03404793.
This paper is an introduction to the mathematical epidemiology of sexually transmitted diseases (STDs) and its application to public health. After a brief introduction to transmission dynamics models, the construction of a deterministic compartmental mathematical model of HIV transmission in a population is described. As a background to STD transmission dynamics, basic reproductive rate, intergroup mixing, rate of partner change, and duration of infectivity are discussed. Use of the models illustrates the effect of sexual mixing (proportionate to highly assortative), of preventive intervention campaigns, and of HIV-chlamydia interaction on HIV prevalence in the different population groups. In particular, planned prevention campaigns can benefit the targeted intervention group but surprisingly can be disadvantageous for the general population. Through examples, mathematical models are shown to be helpful in our understanding of disease transmission, in interpretation of observed trends, in planning of prevention strategies, and in guiding data collection.
本文介绍了性传播疾病（STD）的数学流行病学及其在公共卫生中的应用。在简要介绍传播动力学模型之后，描述了在人群中构建HIV传播的确定性分区数学模型。作为性传播疾病传播动力学的背景，讨论了基本繁殖率、群体间混合、性伴侣更换率和感染期。模型的应用说明了性混合（与高度 assortative 成比例）、预防干预活动以及HIV-衣原体相互作用对不同人群中HIV流行率的影响。特别是，有计划的预防活动可以使目标干预群体受益，但令人惊讶的是，对普通人群可能不利。通过实例表明，数学模型有助于我们理解疾病传播、解释观察到的趋势、规划预防策略以及指导数据收集。
