Research highlights

▶ Integration of empirical mobility networks in a computational epidemic model. ▶ Discrete stochastic epidemic model at the worldwide scale. ▶ Computational platform and algorithms that can be extended to other diseases.

Abstract

Here we present the Global Epidemic and Mobility (GLEaM) model that integrates sociodemographic and population mobility data in a spatially structured stochastic disease approach to simulate the spread of epidemics at the worldwide scale. We discuss the flexible structure of the model that is open to the inclusion of different disease structures and local intervention policies. This makes GLEaM suitable for the computational modeling and anticipation of the spatio-temporal patterns of global epidemic spreading, the understanding of historical epidemics, the assessment of the role of human mobility in shaping global epidemics, and the analysis of mitigation and containment scenarios.

中文翻译：

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传染病的空间传播建模：全球流行病和流动性计算模型。

 研究亮点

▶ 将经验流动网络整合到计算流行病模型中。 ▶ 全球范围内的离散随机流行病模型。 ▶ 可扩展到其他疾病的计算平台和算法。

 抽象的

在这里，我们提出了全球流行病和流动性（GLEaM）模型，该模型将社会人口学和人口流动性数据整合到空间结构化随机疾病方法中，以模拟流行病在全球范围内的传播。我们讨论了模型的灵活结构，该模型对不同的疾病结构和当地干预政策持开放态度。这使得 GLEaM 适用于对全球流行病传播的时空模式进行计算建模和预测、了解历史流行病、评估人员流动在塑造全球流行病中的作用以及分析缓解和遏制情景。