Volume 45 Issue 6
Jun.  2024
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ZHENG Yongtao, YE Chunmei, NI Zuowei, ZHANG Jiani, LAI Fenhua, GAO Yanmin, YANG Dongbo, WANG Yanmei. Establish of the risk predictive model for varicella outbreaks in primary and middle schools[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2024, 45(6): 873-877. doi: 10.16835/j.cnki.1000-9817.2024191
Citation: ZHENG Yongtao, YE Chunmei, NI Zuowei, ZHANG Jiani, LAI Fenhua, GAO Yanmin, YANG Dongbo, WANG Yanmei. Establish of the risk predictive model for varicella outbreaks in primary and middle schools[J]. CHINESE JOURNAL OF SCHOOL HEALTH, 2024, 45(6): 873-877. doi: 10.16835/j.cnki.1000-9817.2024191

Establish of the risk predictive model for varicella outbreaks in primary and middle schools

doi: 10.16835/j.cnki.1000-9817.2024191
  • Received Date: 2024-03-29
  • Rev Recd Date: 2024-04-23
  • Available Online: 2024-06-27
  • Publish Date: 2024-06-25
  •   Objective  To investigate the epidemiological characteristics of varicella outbreaks in primary and middle schools, and to establish a risk predictive model, so as to provide scientific guidance for the prevention of varicella outbreaks in schools.  Methods  Based on a nested case-control study, primary and middle schools in 4 districts of Shanghai (Yangpu District and Jingan District) and Hangzhou (Xiaoshan District and Linping District) from January to December 2023 were selected to observe the status of varicella outbreaks. Associated factors of varicella outbreaks were investigated and used for establishing the predictive model, which was evaluated by the Hosmer-Lemeshow(H-L) goodness of fit test, receiver operating characteristic (ROC) curve, Calibration curve, decision curve analysis (DCA).  Results  A total of 98 varicella outbreaks were included, with 195 schools without varicella outbreaks during the same period as controls. Eight factors, including the availability of warm water in restroom, availability of hand soap in restroom, average class size, duration of student attendance at school per day, presence of a full-time school doctor, hesitancy of the school principal towards varicella vaccination, and rates of first and second doses of varicella vaccination, were identified as potential factors for school varicella outbreaks, with statistically significant differences (χ2/Z=10.01, 20.49, 17.43, 9.74, 32.17, 6.60, 2.20, 3.39, P < 0.05). The 8 variables above were employed to construct a risk predictive model, and Hosmer-Lemeshow goodness of fit test yielded a χ2 value of 5.863 (P>0.05); the area under the ROC curve (AUC) was 0.846 (95%CI=0.799-0.893); Calibration curve analysis indicated good consistency between predicted and actual values of the model. DCA demonstrated favorable predictive performance of the model over a wide range.  Conclusions  The predictive model for school varicella outbreaks demonstrates satisfactory accuracy and efficacy. It suggested to make good use of this prediction model and take relevant measures to reduce the risk of varicella transmission in schools.
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