Mechanical and Industrial Engineering, University of Massachusetts Amherst, Amherst, MA, 01003, USA.
Health Care Manag Sci. 2021 Sep;24(3):623-639. doi: 10.1007/s10729-021-09558-0. Epub 2021 May 15.
Agent-based network modeling (ABNM) simulates each person at the individual-level as agents of the simulation, and uses network generation algorithms to generate the network of contacts between individuals. ABNM are suitable for simulating individual-level dynamics of infectious diseases, especially for diseases such as HIV that spread through close contacts within intricate contact networks. However, as ABNM simulates a scaled-version of the full population, consisting of all infected and susceptible persons, they are computationally infeasible for studying certain questions in low prevalence diseases such as HIV. We present a new simulation technique, agent-based evolving network modeling (ABENM), which includes a new network generation algorithm, Evolving Contact Network Algorithm (ECNA), for generating scale-free networks. ABENM simulates only infected persons and their immediate contacts at the individual-level as agents of the simulation, and uses the ECNA for generating the contact structures between these individuals. All other susceptible persons are modeled using a compartmental modeling structure. Thus, ABENM has a hybrid agent-based and compartmental modeling structure. The ECNA uses concepts from graph theory for generating scale-free networks. Multiple social networks, including sexual partnership networks and needle sharing networks among injecting drug-users, are known to follow a scale-free network structure. Numerical results comparing ABENM with ABNM estimations for disease trajectories of hypothetical diseases transmitted on scale-free contact networks are promising for application to low prevalence diseases.
基于代理的网络建模 (ABNM) 将模拟中的每个个体作为代理进行模拟，并使用网络生成算法生成个体之间的接触网络。ABNM 适用于模拟传染病的个体动态，特别是对于通过复杂接触网络中密切接触传播的疾病，如 HIV。然而，由于 ABNM 模拟了由所有感染者和易感者组成的全部人口的比例版本，因此对于研究 HIV 等低流行疾病中的某些问题，它们在计算上是不可行的。我们提出了一种新的仿真技术，基于代理的演化网络建模 (ABENM)，它包括一种新的网络生成算法，演化接触网络算法 (ECNA)，用于生成无标度网络。ABENM 仅模拟感染者及其个体层面的直接接触者作为模拟的代理，并使用 ECNA 生成这些个体之间的接触结构。所有其他易感者都使用房室建模结构进行建模。因此，ABENM 具有混合基于代理和房室建模结构。ECNA 使用图论的概念来生成无标度网络。包括性伙伴网络和注射吸毒者之间的共用针具网络在内的多个社交网络，都呈现出无标度网络结构。在无标度接触网络上传播的假设疾病的轨迹方面，将 ABENM 与 ABNM 估计值进行比较的数值结果对应用于低流行疾病很有希望。
