During the prevention and control of the COVID-19 epidemic, identifying and controlling the source of infection has become one of the most important prevention and control measures to curb the epidemic in the absence of vaccines and specific therapeutic drugs. While actively taking traditional and comprehensive "early detection" measures, Yinzhou district implemented inter-departmental data sharing through the joint prevention and control mechanism. Relying on a healthcare big data platform that integrates the data from medical, disease control and non-health sectors, Yinzhou district innovatively explored the big data-driven COVID-19 case finding pattern with online suspected case screening and offline verification and disposal. Such effort has laid a solid foundation and gathered experience to conduct the dynamic and continuous surveillance and early warning for infectious disease outbreaks more effectively and efficiently in the future. This article introduces the exploration of this pattern in Yinzhou district and discusses the role of big data-driven disease surveillance in the prevention and control of infectious diseases.
在新型冠状病毒肺炎（COVID-19）疫情防控中，在没有疫苗和特异性治疗药物的情况下，控制传染源成为遏制疫情流行的最重要的防控措施之一。宁波市鄞州区在积极落实传统"早发现"综合措施的同时，通过联防联控机制实现了部门间数据信息共享，依托融合了医疗、疾控以及非卫生部门数据的健康大数据平台，创新性地探索开展大数据驱动的线上可疑病例筛选、线下核实处置的COVID-19病例发现工作模式，为今后实现更有效和高效的动态、持续的传染病监测预警奠定工作基础、积累经验。本研究对宁波市鄞州区的这一模式探索进行介绍，并对大数据驱动的监测模式在传染病防控中的作用进行讨论。.
Keywords: Active case finding; Big data; COVID-19; Paradigm.