Department of Medicine-RMH, University of Melbourne, VIC 3010, Australia.
J Theor Biol. 2012 Mar 21;297:73-87. doi: 10.1016/j.jtbi.2011.12.008. Epub 2011 Dec 16.
Hepatitis C virus (HCV) is a blood-borne virus that disproportionately affects people who inject drugs (PWIDs). Based on extensive interview and blood test data from a longitudinal study in Melbourne, Australia, we describe an individual-based transmission model for HCV spread amongst PWID. We use this model to simulate the transmission of HCV on an empirical social network of PWID. A feature of our model is that sources of infection can be both network neighbours and non-neighbours via "importing". Data-driven estimates of sharing frequency and rate of importing are provided. Compared to an appropriately calibrated fully connected network, the empirical network provides some protective effect on the time to primary infection. We also illustrate heterogeneities in incidence rate of infection, both across and within node degrees (i.e., number of network partners). We explore the reduced risk of infection from spontaneously clearing cutpoint nodes whose infection status oscillates, both in theory and in simulation. Further, we show our model-based estimate of per-event transmission probability largely agrees with previous estimates at the lower end of the range 1-3% commonly cited.
丙型肝炎病毒 (HCV) 是一种血源性病原体，在注射毒品者（PWID）中比例过高。基于澳大利亚墨尔本一项纵向研究的广泛访谈和血液检测数据，我们描述了一个针对 PWID 中 HCV 传播的个体传播模型。我们使用该模型来模拟 PWID 实证社交网络中的 HCV 传播。我们模型的一个特点是，感染源既可以是网络邻居，也可以是通过“输入”的非邻居。我们提供了基于数据的共享频率和输入率的估计值。与适当校准的全连通网络相比，实证网络对原发性感染的时间提供了一定的保护作用。我们还说明了感染发生率的异质性，包括节点度（即网络伙伴的数量）的跨节点和节点内异质性。我们从理论和模拟两方面说明了从自发清除的具有波动感染状态的切点节点感染的风险降低，这些切点节点的感染状态在理论和模拟中都发生了波动。此外，我们的基于模型的事件传播概率估计值与先前的估计值基本一致，先前的估计值通常在 1-3%范围内，位于较低端。
