Using big data and artificial intelligence to establish a multi-point monitoring, early warning, and disposal system to achieve early warning and intervention of infectious disease outbreaks is an important means of controlling the spread of the epidemic. Taking Xiaoshan district as an example, this study analyzes the monitoring contents, warning methods, and application effectiveness of the infectious disease monitoring, early warning and disposal system. Based on Xiaoshan's health big data resources, the system starts with syndrome, disease diagnosis and etiology. Through advanced technologies such as artificial intelligence and block chain, it realizes early identification of infectious disease outbreaks, data fusion, multi-cross collaboration, and closed-loop management. It has improved the sensitivity of clustered outbreaks monitoring and the effectiveness of epidemic disposal and provided a reference for grassroots disease prevention and control departments to establish an infectious disease monitoring and early warning system.
运用大数据和人工智能手段建立传染病监测预警处置系统，以实现对传染病疫情的早期预警、早期干预，是控制疫情扩散的重要手段。本文以杭州市萧山区为例，对传染病监测预警处置系统建设的监测内容与预警方法、应用成效进行专题分析。系统依托健康大数据资源，从症候群、疾病诊断、病原学三方面入手，通过人工智能、区块链等先进技术，实现传染病暴发的早期识别、数据融合和多跨协同、闭环管理，提高了聚集性疫情监测敏感性，有效提高了疫情处置成效，为基层疾病预防控制部门建立传染病监测预警系统提供参考。.