Abstract
Wuhan is located in the hinterland of China, in the east of Hubei Province, at the intersection of the Yangtze River and Hanshui River. It is a national historical and cultural city, an important industrial, scientific, and educational base, and a key transportation hub. There are many schools in Wuhan, with nearly a thousand of all kinds. The number of students is ~2.2 million, accounting for nearly one-fifth of the resident population; college or university students account for ~60% of the total student population. The geographical location of these colleges is relatively concentrated, and the population density is relatively high, making it prone to tuberculosis cluster epidemic. This study analyzed the epidemiological characteristics and influencing factors of tuberculosis aggregation in schools in Wuhan, China, during 2017-2022 to provide the basis for the scientific development of tuberculosis prevention and control strategies and measures in schools. This study adopted the methods of descriptive epidemiology to analyze the epidemic characteristics of tuberculosis aggregation in schools in Wuhan from January 2017 to December 2022, collecting the relevant data on tuberculosis prevention and control in all kinds of schools in the city using Questionnaire Star, an application of the China network questionnaire survey, and analyze the influencing factors of tuberculosis aggregation by using multifactor logistic regression analysis. From 2017 to 2022, 54 outbreaks of pulmonary tuberculosis aggregation in schools were reported in Wuhan, which involved 37 different schools, including 32 colleges or universities and five senior high schools; 176 cases were reported, among which 73 were positive for pathogens and 18 were rifampicin or izoniazid resistant. The median duration of a single cluster epidemic was 46 (26,368) days. Universities were more prone to cluster outbreaks than middle schools (χ2 = 105.160, P = 0.001), and the incidence rate among male students was higher than that of female students in cluster epidemics (χ2 = 12.970, P = 0.001). The multivariate logistic regression analysis results showed that boarding in school (OR = 7.60) is the risk factor for a tuberculosis cluster epidemic in schools. The small number of students (OR = 0.50), the location of the school in the city (OR = 0.60), carry out physical examinations for freshmen (OR = 0.44), carry out illness absence and cause tracking (OR = 0.05), dormitories and classrooms are regularly ventilated with open windows (OR = 0.16), strict implement the management of sick student's suspension from school (OR = 0.36), and seeking timely medical consultation (OR = 0.32) were the protective factors for a tuberculosis cluster epidemic in schools. We successfully identified the epidemiological characteristics and influencing factors of tuberculosis aggregation in schools in Wuhan. The results revealed the influence and status of various factors and indicated ways for schools to improve their TB prevention and control measures in their daily activities. These measures can effectively help curb the cluster epidemic of tuberculosis in schools.
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