基于多数据融合的全球传染病监测预警信息系统的建立与初步应用

Establishment of the global infectious disease surveillance and early warning information system based on multi-data fusion and its preliminary application

  • 摘要:
    目的 针对传染病监测预警体系面临的信息整合与共享不畅、预警响应机制落后等瓶颈,构建全球传染病监测预警信息系统,以实现生物安全事件的动态感知,相关本底信息的一站式获取以及输入风险的快速准确评估。
    方法 基于网络爬虫和文献调研获取传染病相关多源大数据,规范统一其时间、空间、宿主、媒介、疾病、病原体等信息,建立疾病-病原体-宿主-媒介-社会经济-自然环境的关联性,嵌入境外输入风险自动化评估技术,开发基于数据获取层、数据抽取与处理层、数据存储层、数据分析层和应用服务层的信息系统。
    结果 本系统实时监测来自34个组织或机构共76个开源网站的人类传染病、动物疫病、外来物种入侵等生物安全事件,系统整合150种重要传染病、15类宿主动物、8类媒介生物、412种病原体和86种动物疫病的历史报告数据以及航空流量、卫生条件等相关影响因素,实现传染病时空分布可视化,并能在5 s内完成境外疫情输入我国各省风险的评估。
    结论 本系统践行“One Health”理念,有效整合多源异构数据,关联传染病相关的人-动物-环境因素,显著提升了监测预警的时效性、准确性,实现了对新发突发传染病的多维度动态感知与快速风险评估,为精准制定防控策略提供坚实的数据基础和技术支撑。

     

    Abstract:
    OBJECTIVE To address bottlenecks in the infectious disease surveillance and early warning system, such as poor information integration and sharing, as well as outdated response mechanisms, this study aims to construct a global infectious disease surveillance and early warning information system, so as to achieve dynamic perception of biosafety events, one-stop access to relevant background information and rapid and accurate assessment of importation risks.
    METHODS Multi-source big data on infectious diseases were collected through web crawlers and literature reviews. Information on time, space, hosts, vectors, diseases and pathogens was standardized and unified. Correlations among diseases, pathogens, hosts, vectors, socio-economic factors and the natural environment were established. Automated risk assessment technology for cross-border importation was embedded, and an information system was developed based on five layers: data acquisition, data extraction and processing, data storage, data analysis and application services.
    RESULTS This system monitored biosafety events in real time, including human infectious diseases, animal epidemic diseases and alien species invasion, from 76 open-source websites of 34 organizations or institutions. It integrated historical reporting data on 150 major infectious diseases, 15 categories of host animals, 8 categories of vector organisms, 412 pathogens and 86 animal epidemic diseases, along with influencing factors such as air traffic and sanitary conditions. The system visualized the spatiotemporal distribution of infectious diseases and was able to assess the risk of imported overseas epidemics to each province in China within 5 seconds.
    CONCLUSIONS This system embodies the "One Health" concept, effectively integrating multi-source heterogeneous data and linking human-animal-environment factors related to infectious diseases. It significantly improves the timeliness and accuracy of surveillance and early warning, enabling multi-dimensional dynamic perception and rapid risk assessment of emerging infectious diseases. This provides a solid data foundation and technical support for precisely formulating prevention and control strategies.

     

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