Research of Epidemic Dynamics Model Considering Individual Movements and Urban Areas

Boxu Pan, Jie Yang, Yu Wang, Zehao Wang, Yuangeng Zhu, Zhiqiang Zhang
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Abstract

With the rapid spread of COVID-19, hundreds of millions of people worldwide have been infected. In order to cope with the epidemic, experts from various countries have carried out a lot of research works. Most of these works chose to use the traditional SEIR model, but the traditional model doesn't consider the individual's movement in the city. Based on the transmission characteristics of COVID-19, this paper optimized the traditional SEIR model by combining the in-depth mining and processed multiple data, such as the real epidemic data published by some official organizations, as well as data with certain credibility obtained from reference papers, journals or newspapers. Compared with the traditional SEIR model, the proposed model takes into account the impact of individuals' movement and the division of urban functional areas. The outcomes can play a certain role in the prediction and analysis of the spread of the epidemic in cities with regular individuals' movements and functions of urban areas.
考虑个体运动和城市区域的流行病动力学模型研究
随着COVID-19的迅速传播,全球有数亿人受到感染。为了应对这一流行病,各国专家进行了大量的研究工作。这些作品大多选择使用传统的SEIR模型,但是传统模型并没有考虑到个人在城市中的运动。本文根据COVID-19的传播特点,结合对多个数据的深度挖掘和处理,对传统的SEIR模型进行了优化,这些数据包括一些官方机构公布的真实疫情数据,以及从参考论文、期刊或报纸中获得的具有一定可信度的数据。与传统的SEIR模型相比,该模型考虑了个体迁移和城市功能区划分的影响。研究结果可对人群流动规律和城区功能规律的城市疫情传播进行预测和分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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