Abstract: Objective To explore the current situation of TB case detection in universities in shanghai, and implement interventions in order to improve the TB case detection in universities.  Methods Secondary data review method was used to investigate the situation of pulmonary TB case detection in Yangpu and Songjiang districts in 2006—2007, Excel 2007 is used to sort the data. Qualitative interviews was carried out to student with TB, CDC TB staff, teachers and health care workers (HCWs) in universities to explore the current situation of TB case detection and existing problems, MAXQDA software was used to sort, tag and categorize the data. The interventions were taken in 17 universities in two districts. The effects of the intervention were evaluated through indicators including case detection methods and corresponding proportion, registration rate of student TB, cavity detection rate, median days from symptoms onset to visiting the clinics,  awareness rate of core TB knowledge.   Results Before the implementation of the intervention, case detection rates of active and smear positive pulmonary TB patients were 11.0/100000 and 3.8/100000, respectively. 97.8% (45/46)of the student with TB were detected via passive case identification. 32.6% (15/46)of the patients visited doctors within 14 days after symptom onset. The awareness rate of core TB knowledge was 57.6%. After the interventions, case detection rates of active and smear positive pulmonary TB patients increased to 22.1/100000 (χ²=15.89,P<0.0001) and 6.0/100000, respectively. The awareness rate of core TB knowledge increased to 65.4%(6319/9660)（χ²=126.9,P<0.0001）. The proportion of the patients visited doctors within 14 days after symptom onset increased to 54.8%(51/93).  Conclusion The model greatly improved the TB case detection in universities in Shanghai.