基于人群移动大数据的重大传染病爆发态势分析及防控效用研究——以COVID-19为例

自2019年12月以来，新型冠状病毒肺炎(COVID-19)在武汉出现，并迅速在全国各省市，亚洲，欧洲，美洲乃至全球相继爆发，对全球的公共生命安全构成了严重威胁。该传染病的爆发规模，传播速度都超出现有科学认知，而大规模人群流动，也进一步加剧了疫情的爆发态势和防控难度，对传统的重大传染病研究方法提出了挑战，因此，急需要在传统传染病模型基础上结合人群移动大数据构建传染病态势的动态分析模型。然而现有研究主要关注人群移动模式及其与传染病动态关系，并不足以解析传染病的影响机制和传播机理，必须全面、多角度深入其变化机理与对人群移动的响应机制。对此，本项目拟从重大传染病的时空分布及其人群流动模式关系出发，构建一个重大传染病的多维特征描述模型，解析其对人群移动的响应机制；并以COVID-19疫情为实例，分析不同人群限流政策下的防控效用，为如COVID-19此类重大传染病的科学防控提供支撑。

Since December 2019, the new coronavirus pneumonia (COVID-19) has appeared in Wuhan, and rapidly outbreak in cities and provinces across the country. So far, COVID-19 has invaded in Asia, Europe, the Americas and even the world, posing a serious threat to global public health. Since the outbreak scale and speed of the epidemic are far beyond current scientific knowledge, and even the large-scale population movement has further exacerbated the outbreak situation and increased the difficulty of prevention and control, it is a great challenge for traditional transmission models to predict the epidemic dynamics and put forward effective prevention and control measures. Therefore, there is an urgent need to build a dynamic model of epidemic combining with human mobility. However, existing research mainly focuses on the movement patterns and their relationships with epidemic, which can hardly provide an insight into the influence and transmission mechanism of the epidemic. It is necessary to explore the essential changes and responses mechanism to the dynamic human movement. In this regard, this project intends to build a multi-dimensional description model for major epidemic based on the relationship between the spatial and temporal characteristics of epidemic and the human movement patterns, and analyze its essential mechanism. Taking the COVID-19 epidemic as an example, we aim to simulate the effectiveness of prevention and control under different population restriction policies scenarios and provide support for the scientific prevention and control for COVID-19.