We describe a general framework for modeling and stochastic simulation of epidemics in realistic dynamic social networks, which incorporates heterogeneity in the types of individuals, types of interconnecting risk-bearing relationships, and types of pathogens transmitted across them. Dynamism is supported through arrival and departure processes, continuous restructuring of risk relationships, and changes to pathogen infectiousness, as mandated by natural history; dynamism is regulated through constraints on the local agency of individual nodes and their risk behaviors, while simulation trajectories are validated using system-wide metrics. To illustrate its utility, we present a case study that applies the proposed framework towards a simulation of HIV in artificial networks of intravenous drug users (IDUs) modeled using data collected in the Social Factors for HIV Risk survey.

中文翻译：

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动态多关系社交网络中基于随机代理的病原体传播模型

我们描述了在现实动态社交网络中对流行病进行建模和随机模拟的一般框架，该框架结合了个体类型、相互关联的风险承担关系类型以及通过它们传播的病原体类型的异质性。根据自然历史的要求，通过到达和离开过程、风险关系的持续重组以及病原体传染性的变化来支持活力；动态是通过对单个节点的本地代理及其风险行为的约束来调节的，而模拟轨迹则使用系统范围的指标进行验证。为了说明它的效用，