基于时空位置大数据的新冠疫情传播风险控制模型

Risk Control Model of COVID-19 Transmission Based on Spatio-temporal Location Big Data

提出基于时空位置大数据的新冠疫情传播风险控制模型。以时空位置大数据、控制关系链以及时空位置为基础,结合新冠疫情的自身特点、控制目标以及控制工作内容,构建新冠疫情传播风险控制模型。模型在疫情控制前期和中期时,通过疫情跟踪分析疫情的特征,并依据传播风险评估模型,整合时空位置大数据;结合疫情特征和数据整合结果,利用SEIR模型和疫情风险迁徙模型,模拟疫情传播情况以及评估传播风险;根据评估结果制定疫情传播风险控制策略。测试结果表明:该模型能够可靠获取时空位置数据中的疫情信息,具备疫情传播风险控制能力,在100%执行程度下,可实现标准化风险指数的最低化以及连续感染率的最小化。

A risk control model for COVID-19 transmission based on spatio-temporal location big data is proposed.Based on spatio-temporal location big data,control relationship chain and spatio-temporal location,combined with the characteristics of the epidemic,control objectives and control work content,a risk control model for the spread of COVID-19 was established.In the ear⁃ly and middle stages of epidemic control,the model analyzed the characteristics of the epidemic through epidemic tracking,and in⁃tegrated spatio-temporal location big data according to the transmission risk assessment model.Combined with the epidemic charac⁃teristics and data integration results,SEIR model and epidemic risk migration model were used to simulate the spread of the epidem⁃ic and assess the spread risk.Based on the assessment results,risk control strategies for epidemic transmission were formulated.The test results show that the model can reliably obtain epidemic information from spatio-temporal location data,and has the ability to control epidemic transmission risk.Under 100%implementation,the standardized risk index and continuous infection rate can be minimized.