RESUMO
OBJECTIVES: The objectives were to examine Mycobacterium tuberculosis transmission patterns by RFLP analysis in Shinjuku city, and to elucidate more effective methods of contact investigations. METHODS: We applied RFLP analysis to 389 M. tuberculosis isolates from 402 TB patients registered in Shinjuku city from September 2002 though August 2006. RESULTS: Forty-six clusters consisting of 155 TB patients (average 3.4 people per cluster) were identified (proportion of clustering: 39.8%). The clustering rates were 34.5% among general patients, and 57.8% among homeless patients, and the latter was higher than that of non-homeless patients (odds ratio: 2.6, 95% CI; 1.6-4.1, p < 0.001). On the other hand, the clustering rates were only 19.4% among foreigners (odds ratio: 0.5, 95% CI; 0.2-1.2, p = 0.090). Twenty-eight of 46 clusters (60.9%) were consisted of mixture of general patients, homeless patients and foreigner patients. Thus, RFLP analysis can detect the transmission route which can not be identified by the routine contact examination, thus enabling contact investigations extended to the appropriate persons. DISCUSSION: The homeless clustering rate was significantly high. This suggests that the proportion of transmission among the homeless patients might be high. However, many clusters were composed of a mixture of homeless patients and non-homeless patients, so transmission patterns are not easy to identify. It is not always true that transmission of tuberculosis to non-homeless patients took place from homeless patients. Clustering rates among homeless patients are high, therefore taking countermeasures for the homeless patients is an effective way to prevent the spread of tuberculosis. Introduction of RFLP analysis is a practical epidemiological methodology to investigate the source of infection and transmission route of infection, and can be applied to contact investigations. If RFLP analysis can be applied in a larger area, yearly changes of notification rates and molecular epidemiological clustering rates will provide indices for preventive measures against tuberculosis.