A versatile ODE approximation to a network model for the spread of sexually transmitted diseases
A versatile ODE approximation to a network model for the spread of sexually transmitted diseases
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DOI：
10.1007/s002850200153
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发表时间：
2002-11-01
影响因子：
1.9
通讯作者：
Bauch, CT
中科院分区：
文献类型：
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作者：
Bauch, CT
我们开发了一个时刻关闭近似（MCA）的网络模型的性传播疾病（STD）通过一个稳定/偶然的伙伴关系网络传播。MCA以前已被用来近似静态，规则的格子，而应用到动态，不规则的网络是一个新的努力，并没有尝试应用到社会学动机的网络模型。我们的目标是：1）调查有关的应用程序的时刻关闭近似的动态和不规则的网络问题，和2）了解并发的偶然的合作伙伴对性病传播的影响，通过人口主要是稳定的一夫一妻制的合作伙伴关系。我们能够推导出一个动态的不规则网络代表性伙伴关系的动态矩封闭近似，然而，我们被迫使用三重近似由于标准对近似的大误差。这个例子强调了对矩封闭近似进行误差分析的重要性。我们还发现，少数偶然的伴侣关系大大增加了这一流行病的流行程度和传播速度。最后，虽然近似是针对特定的网络模型推导的，但我们可以简单地通过改变控制动态网络结构的模型参数来恢复广泛的网络模型的近似。因此，我们的矩封闭近似在它可以近似的网络模型的种类上是非常灵活的。
We develop a moment closure approximation (MCA) to a network model of sexually transmitted disease (STD) spread through a steady/casual partnership network. MCA has been used previously to approximate static, regular lattices, whereas application to dynamic, irregular networks is a new endeavour, and application to sociologically-motivated network models has not been attempted. Our goals are 1) to investigate issues relating to the application of moment closure approximations to dynamic and irregular networks, and 2) to understand the impact of concurrent casual partnerships on STD transmission through a population of predominantly steady monogamous partnerships. We are able to derive a moment closure approximation for a dynamic irregular network representing sexual partnership dynamics, however, we are forced to use a triple approximation due to the large error of the standard pair approximation. This example underscores the importance of doing error analysis for moment closure approximations. We also find that a small number of casual partnerships drastically increases the prevalence and rate of spread of the epidemic. Finally, although the approximation is derived for a specific network model, we can recover approximations to a broad range of network models simply by varying model parameters which control the structure of the dynamic network. Thus our moment closure approximation is very flexible in the kinds of network models it can approximate.