2023年全国传染病突发公共卫生事件发现方式特征分析

Analysis on characteristics of detections of public health emergencies caused by infectious diseases in China, 2023

  • 摘要:
    目的 分析2023年通过突发公共卫生事件管理信息系统报告的传染病突发公共卫生事件发现方式的特征,为提高我国传染病突发公共卫生事件报告质量提出建议。
    方法 对2023年经突发公共卫生事件管理信息系统报告的传染病突发公共卫生事件相关信息进行分析,了解最初获得事件信息的方式。
    结果 2023年全国传染病突发公共卫生事件主要通过疾病预防控制机构识别(238起,35.47%)、医疗机构发现(205起,30.55%)以及学校报告(161起,23.99%)等方式发现,3种方式共占2023年传染病突发公共卫生事件总数的90.01%。 此外,通过智慧化预警信息提示发现32起突发公共卫生事件。 2023年全国传染病突发公共卫生事件从首例患者发病至事件发现的时间间隔中位数为6.83(四分位间距:4.19~9.94)d。
    结论 2023年全国传染病突发公共卫生事件的发现方式呈现出多样化的特征,智慧化预警信息提示的价值正在逐步凸显,为进一步建立健全智慧化多点触发传染病监测预警体系提供了数据支撑。 建议优化智慧化监测预警系统,提高信息整合与风险评估能力,以进一步缩短事件发现时间间隔。

     

    Abstract:
    Objective To analyze the characteristics of detections of public health emergencies caused by infectious diseases in China in 2023 reported through Public Health Emergency Management Information System, and provide evidence for the improvement of the reporting quality of the public health emergencies in China.
    Methods We analyzed the incidence data of public health emergencies caused by infectious diseases in China in 2023, and investigated the initial information source of the public health emergencies.
    Results In 2023, the public health emergencies caused by infectious diseases were mainly detected by centers for disease control and prevention (238 events, 35.47%), hospitals (205 events, 30.55%) and schools (161 events, 23.99%), accounting for 90.01% of the total. Additionally, 32 public health emergencies were identified through intelligent early warning. In the public health emergencies caused by infectious diseases in 2023, the median interval between the onset of the first case and the detection was 6.83 days (interquartile range: 4.19−9.94).
    Conclusion The detections of public health emergencies caused by infectious diseases showed varied characteristics in China in 2023, and the value of intelligent early warning has gradually became obvious, providing data support for the further establishment and improvement of intelligent multi-source trigger surveillance and early warning system for infectious diseases. It is suggested to optimize the intelligent surveillance and early warning system and improve the information integration and risk assessment for the rapid detection of public health emergency.

     

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