摘要
当前如何通过模型的构建来揭示新型冠状病毒肺炎(Corona Virus Disease 2019,COVID-19)的传播机制,提高对疫情传播的时空预测预警能力仍面临很大挑战.为充分发挥SEIRD模型和CA模型各自在时间和空间仿真方面的优势,依据空间现象的地理相似性原理,构建了一种基于SEIRD-GEOCA的传染病时空耦合模型,并在模型中融入了蔓延扩散和随机迁移扩散策略,采用重庆市2020年1月21日到2020年2月29日的感染者轨迹数据和相关驱动因子数据实现了对重庆市COVID-19感染者时空分布的情景模拟.情景模拟结果显示,在空间上将呈现出爆发式扩散和局域扩散的明显差别;且实施不同强度的干预,COVID-19呈现出了不同的时空扩散效应.研究表明,SEIRD-GEOCA模型能揭示传染病的传播机制,并能较好地模拟COVID-19疫情的时空扩散规律;面对COVID-19疫情,政府是否采取干预措施以及实施干预的强度都将对疫情的时空扩散产生较大影响.
At present,how to construct the models to reveal the transmission mechanism of Corona Virus Disease 2019(COVID-19),and improve the spatio-temporal prediction and early warning capabilities of the epidemic spread is still facing great challenges.In order to fully use the respective advantages of the SEIRD model and the CA model in temporal and spatial simulation,based on the principle of geographic similarity of spatial phenomena,a SEIRD-GEOCA based infectious disease spatio-temporal coupled model was constructed,and strategies of contact diffusion and random migration were incorporated into the model.Using the data of the infected persons in Chongqing from January 21,2020 to February 28,2020 and related driving factor data,the scenario simulation of the temporal and spatial distribution of COVID-19 infected persons in Chongqing was realized.The scenario simulation results show that obvious differences in the spatial distribution between outbreak and local spread.In addition,the implementation of different intervention intensities showed different spatio-temporal diffusion effects.Studies have shown that the SEIRD-GEOCA model can reveal the transmission mechanism of infectious diseases and better simulate the spatio-temporal spread of COVID-19.In the face of the epidemic,whether the government takes intervention measures and the intensity of the intervention will affect the spatio-temporal spread of the epidemic.
作者
荆磊
刘明皓
陈春
曹逸凡
刘天林
JING Lei;LIU Minghao;CHEN Chun;CAO Yifan;LIU Tianlin(School of Computer Science and Technology,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;Spatial Information Research Center,Chongqing University of Posts and Telecommunications,Chongqing 400065,China;School of Architecture and Urban planning,Chongqing Jiaotong University,Chongqing 400074,China;Ecological Habitat and Green Transportation Research Center,Chongqing Jiaotong University,Chongqing 400074,China)
出处
《西南大学学报（自然科学版）》
CAS
CSCD
北大核心
2022年第2期207-218,共12页
Journal of Southwest University(Natural Science Edition)
基金
国家自然科学基金资助项目(42071218)
重庆市自然科学基金资助项目(cstc2019jcyj-msxmX0139).
