Abstract: Objective To explore the epidemiological characteristics of tuberculosis in schools in Suzhou High-tech District,build an ARIMA model to predict the short-term incidence risk,and improve the school epidemic monitoring layout and control strategies. Methods Based on the the China Disease Prevention and Control Information System,the data of tuberculosis epidemic situation in schools of Suzhou High-tech District from 2019 to 2022 were collected,and the retrospective analysis and trend prediction were carried out. Results From 2019 to 2022,Suzhou High-tech District eported 95 cases of pulmonary tuberculosis among students,2 clustered epidemics and 79 sporadic epidemics,with an annual reported incidence rate of 8.88/100 000 to 27.91/100 000. The high incidence stage of cases was in colleges and universities,with the high incidence time concentrated in the third quarter,accounting for 39.00%. The male to female prevalence ratio was 1.64 ∶ 1,and the majority of patients seek medical treatment due to symptoms,accounting for 42.11%. 3 803 close contacts were screened,and the strong positive rate of PPD was 10.70%. The PPD strong positive rate in the class with clustered epidemic cases was higher than that in the expanded screening class and sporadic epidemic（ χ²=30.553,P<0.05）. The rate of preventive medication for latent infections was increasing year by year. The ARIMA model predicted that the quarterly incidence rates of colleges and universities in 2023 will be 1.42/100 000,2.98/100 000, 6.10/100 000,and 3.74/100 000. Conclusion The risk of latent infection and incidence of pulmonary tuberculosis in students is high. It is necessary to accurately identify the close contacts and general contacts,expand the screening objects step by step,take effective preventive measures for the latent infected,scientific early warning,and curb the spread of tuberculosis in schools.

Key words: Students, Tuberculosis, Lung, Epidemiological characteristics, ARIMA model