To analyze the epidemiological characteristics of human infection with avian influenza A(H7N9) virus from 2013 to 2016 in Xiaoshan,China,we collected the epidemiological data of human A(H7N9) cases as well as the results of environmental monitoring and analyzed it by case study,descriptive epidemiological method,and statistical analysis.Results showed that a total of 22 cases were confirmed,including 12 deaths.All the cases occurred in winter and spring,and most of them had been exposed to live poultry,and with the underlying condition of chronic diseases.Chi-square test showed that the ratio of cases with chronic diseases in death group was higher (P=0.01).The environmental monitoring result showed there were distinctive seasonal differences of positive rate with peaks in winter and spring and nadirs in autumn and summer.Positive rates for the samples from external environmental monitoring were consistent with the distribution of the case onset.Due to rise of environmental monitoring positive rate,we should be alert to the occurrence of new cases,especially in rural areas where live poultry fairs still exist and among people with occupational exposure.We should further improve ability to prevent and control this disease.

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 (χ2/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 χ2 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.