空间数据挖掘驱动城市疫情监测常态化的作用研究

Research on the Role of Spatial Data Mining in Driving the Normalization of Urban Epidemic Surveillance

城市疫情监测在未来很长一段时间将成为一种常态化工作,以“健康码”为代表的空间数据成为当前研究疫情发展过程和辅助发现预测可能疫情的重要战略资源。对空间数据的加权聚类提取为解决空间数据挖掘所遭遇的海量、多源和高维挑战提供了新途径。对准确发现疫情可能爆发或具有高传播性的关键区域,准确获取疫情可能爆发的重点区域或感染区域的空间分布,满足于具有大数据特征的空间数据挖掘分析都具有更好的支持作用,驱动了城市疫情监测常态化工作的科学有效开展。

Urban epidemic surveillance will become a normal work for a long time in the future,and spatial data represented by"health code"has become an important strategic resource for studying the development process of epidemic and assisting in detecting and predicting possible epidemic.Weighted clustering extraction of spatial data provides a new way to solve the massive,multi-source and high-dimensional challenges of spatial data mining.To accurately find the outbreak could erupt or critical areas of high transmission,accurately obtain the key area of outbreak could erupt or infected areas of space distribution,satisfied with big data characteristics of spatial data mining analysis has better support,which drive the city the scientific and effective work of epidemic monitoring normalized.