Romero-Severson E O, Volz E, Koopman J S, Leitner T, Ionides E L
Am J Epidemiol. 2015 Aug 1;182(3):255-62. doi: 10.1093/aje/kwv044. Epub 2015 May 20.
Human immunodeficiency virus (HIV) transmission models that include variability in sexual behavior over time have shown increased incidence, prevalence, and acute-state transmission rates for a given population risk profile. This raises the question of whether dynamic variation in individual sexual behavior is a real phenomenon that can be observed and measured. To study this dynamic variation, we developed a model incorporating heterogeneity in both between-person and within-person sexual contact patterns. Using novel methodology that we call iterated filtering for longitudinal data, we fitted this model by maximum likelihood to longitudinal survey data from the Centers for Disease Control and Prevention's Collaborative HIV Seroincidence Study (1992-1995). We found evidence for individual heterogeneity in sexual behavior over time. We simulated an epidemic process and found that inclusion of empirically measured levels of dynamic variation in individual-level sexual behavior brought the theoretical predictions of HIV incidence into closer alignment with reality given the measured per-act probabilities of transmission. The methods developed here provide a framework for quantifying variation in sexual behaviors that helps in understanding the HIV epidemic among gay men.
包含性行为随时间变化的人类免疫缺陷病毒(HIV)传播模型显示,对于给定的人群风险概况,发病率、患病率和急性期传播率均有所上升。这就引出了一个问题,即个体性行为的动态变化是否是一种可观察和测量的真实现象。为了研究这种动态变化,我们开发了一个模型,该模型纳入了人与人之间以及个体内部性行为接触模式的异质性。我们使用一种称为纵向数据迭代滤波的新方法,通过最大似然法将该模型拟合到疾病控制与预防中心的HIV血清发病率协作研究(1992 - 1995年)的纵向调查数据中。我们发现了性行为随时间存在个体异质性的证据。我们模拟了一个流行过程,发现纳入个体层面性行为动态变化的经验测量水平后,在考虑到所测量的每次行为传播概率的情况下,HIV发病率的理论预测与实际情况更为吻合。这里开发的方法提供了一个量化性行为变化的框架,有助于理解男同性恋者中的HIV流行情况。