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Spatial Modeling of Influenza Outbreaks in Saint Petersburg Using Synthetic Populations

机译:利用合成种群在圣彼得堡爆发流感的空间模型

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In this paper, we model influenza propagation in the Russian setting using a spatially explicit model and a detailed human agent database as its input. The aim of the research is to assess the applicability of this modeling method using influenza incidence data for 2010-2011 epidemic outbreak in Saint Petersburg and to compare the simulation results with the output of the compart mental SEIR model for the same outbreak. For this purpose, a synthetic population of Saint Petersburg was built and used for the simulation via FRED open source modeling framework. The parameters related to the outbreak (background immunity level and effective contact rate) are assessed by calibrating the com-partmental model to incidence data. We show that the current version of synthetic population allows the agent-based model to reproduce real disease incidence.
机译:在本文中,我们使用空间显式模型和详细的人类病原体数据库作为输入来模拟在俄罗斯环境中的流感传播。本研究的目的是使用圣彼得堡2010-2011年流行病暴发的流感发病率数据评估该建模方法的适用性,并将模拟结果与相同爆发的Compart mental SEIR模型的输出进行比较。为此,建立了圣彼得堡的人工种群,并通过FRED开源建模框架将其用于仿真。与爆发相关的参数(背景免疫水平和有效接触率)通过将隔离模型校正为发病数据进行评估。我们表明,当前版本的合成种群允许基于代理的模型重现真实的疾病发病率。

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