TY - JOUR AU - Yang, Zhen AU - Jiang，成华PY - 2022 DA - 2022/10/14 TI -基于缺勤和温度的中国流感综合征监测试点系统:开发和可用性研究JO - JMIR公共卫生监测SP - e37177 VL - 8 IS - 10kw -流感KW -综合征监测系统KW -人脸识别KW -红外体温计KW -缺勤KW -温度AB -背景:中国现行校本传染病综合征监测系统的不足之处在于依赖校医手工采集数据，忽视在校生的健康信息。目的:本研究旨在设计并实现基于缺勤率(通过人脸识别收集)和在校学生体温(通过热成像测量)的流感SSS。方法:通过扩展现有应用程序的功能来实现SSS。该制度在长三角地区的2所小学和1所初中实施，共计3535名学生。考试周期为2021年3月1日至2022年1月14日，有效天数为174天。系统报告的每日和每周缺勤率和发烧率(DAR1和DFR;计算WAR1和WFR)。以校医上报的每日和每周缺勤率(DAR2和WAR2)和每周流感病毒阳性率(WPRIV，由中国国家流感中心发布)为标准，评估系统上报数据的质量。结果:校医报告的缺勤率(完整性86.7%)为本系统报告的缺勤率(完整性100%)的36.5%，两者之间存在显著正相关(r=0.372, P=.002)。 When the influenza activity level was moderate, DAR1s were significantly positively correlated among schools (rab=0.508, P=.004; rbc=0.427, P=.02; rac=0.447, P=.01). During the influenza breakout, the gap of DAR1s widened. WAR1 peaked 2 weeks earlier in schools A and B than in school C. Variables significantly positively correlated with the WPRIV were the WAR1 and WAR2 of school A, WAR1 of school C, and WFR of school B. The correlation between the WAR1 and WPRIV was greater than that between the WAR2 and WPRIV in school A. Addition of the WFR to the WAR1 of school B increased the correlation between the WAR1 and WPRIV. Conclusions: Data demonstrated that absenteeism calculation based on face recognition was reliable, but the accuracy of the temperature recorded by the infrared thermometer should be enhanced. Compared with similar SSSs, this system has superior simplicity, cost-effectiveness, data quality, sensitivity, and timeliness. SN - 2369-2960 UR - https://publichealth.www.mybigtv.com/2022/10/e37177 UR - https://doi.org/10.2196/37177 UR - http://www.ncbi.nlm.nih.gov/pubmed/36239991 DO - 10.2196/37177 ID - info:doi/10.2196/37177 ER -