Fu Rui, Gutfraind Alexander, Brandeau Margaret L
Department of Management Science and Engineering, Stanford University, United States.
Division of Epidemiology and Biostatistics, University of Illinois at Chicago, United States.
Math Biosci. 2016 Mar;273:102-13. doi: 10.1016/j.mbs.2016.01.003. Epub 2016 Jan 14.
Injection drug users (IDUs) are at high risk of acquiring and spreading various blood-borne infections including human immunodeficiency virus (HIV), hepatitis C virus (HCV), hepatitis B virus (HBV) and a number of sexually transmitted infections. These infections can spread among IDUs via risky sexual and needle-sharing contacts. To accurately model the spread of such contagions among IDUs, we build a bi-layer network that captures both types of risky contacts. We present methodology for inferring important model parameters, such as those governing network structure and dynamics, from readily available data sources (e.g., epidemiological surveys). Such a model can be used to evaluate the efficacy of various programs that aim to combat drug addiction and contain blood-borne diseases among IDUs. The model is especially useful for evaluating interventions that exploit the structure of the contact network. To illustrate, we instantiate a network model with data collected by a needle and syringe program in Chicago. We model sexual and needle-sharing contacts and the consequent spread of HIV and HCV. We use the model to evaluate the potential effects of a peer education (PE) program under different targeting strategies. We show that a targeted PE program would avert significantly more HIV and HCV infections than an untargeted program, highlighting the importance of reaching individuals who are centrally located in contact networks when instituting prevention programs.
注射吸毒者(IDUs)面临感染和传播各种血源性感染的高风险,包括人类免疫缺陷病毒(HIV)、丙型肝炎病毒(HCV)、乙型肝炎病毒(HBV)以及多种性传播感染。这些感染可通过危险的性行为和共用针头在注射吸毒者之间传播。为了准确模拟此类传染病在注射吸毒者中的传播情况,我们构建了一个双层网络,该网络捕捉了这两种危险接触类型。我们提出了从现成数据源(如流行病学调查)推断重要模型参数(如控制网络结构和动态的参数)的方法。这样的模型可用于评估旨在打击药物成瘾和控制注射吸毒者中血源性疾病的各种项目的效果。该模型对于评估利用接触网络结构的干预措施特别有用。为了说明这一点,我们用芝加哥一个针头和注射器项目收集的数据实例化了一个网络模型。我们对性行为和共用针头接触以及随之而来的HIV和HCV传播进行建模。我们使用该模型评估同伴教育(PE)项目在不同目标策略下的潜在效果。我们表明,有针对性的同伴教育项目比无针对性的项目能显著避免更多的HIV和HCV感染,突出了在制定预防项目时接触处于接触网络中心位置个体的重要性。