Published Paper Details:

Background & Objectives: The Government of India has announced its National Strategic Plan (NSP) for controlling TB in India by the year 2025. To achieve NSP, it will be useful for program implementers to identify various forms of cluster locations with high risk of transmission and to initiate appropriate measures to control TB. In this study, our aim is to identify and rank spatial clustering of various forms of tuberculosis among the districts of Tamil Nadu State, India for the years 2016, 2017 and 2018. Methods: We have considered aggregate (count) data in the form of tuberculosis case notification for the districts of Tamil Nadu state and used discrete Poisson model and Log-Likelihood Ratio test to identify the high risk spatial TB clusters. We have used SaTScan software for this purpose. Results: We have identified Madurai, Dindigul and Thiruvarur Districts for new sputum positive pulmonary tuberculosis case clustering, Madurai and Thiruvarur Districts for previously treated smear positive pulmonary tuberculosis case clustering (towards the direction of containing the transmission dynamics of tuberculosis), Vellore District for clinically diagnosed tuberculosis case clustering (towards the direction of enhancing diagnostic facilities such as providing more number of X-ray mechines and incresing the number of trained chest physicians) and Vellore and Chennai Districts are for extra-pulmonary TB case clustering (towards the direction of setting up more surgical facilities to handle such cases) in the study period. Also we have produced thematic maps showing various forms of TB clusters using QGIS software. Interpretation & Conclusions: This method can be used to identify TB clusters for aggregate data for a given time period for prioritizing enhanced intervention activities.