In India, tuberculosis is an enormous public health problem. This study provides the first description of molecular diversity of the Mycobacterium tuberculosis complex (MTBC) from Sikkim, India. A total of 399 Acid Fast Bacilli sputum positive samples were cultured on Lőwenstein–Jensen media and genetic characterisation was done by spoligotyping and 24-loci MIRU-VNTR typing. Spoligotyping revealed the occurrence of 58 different spoligotypes. Beijing spoligotype was the most dominant type constituting 62.41% of the total isolates and was associated with Multiple Drug Resistance. Minimum Spanning tree analysis of 249 Beijing strains based on 24-loci MIRU-VNTR analysis identified 12 clonal complexes (Single Locus Variants). The principal component analysis was used to visualise possible grouping of MTBC isolates from Sikkim belonging to major spoligotypes using 24-MIRU VNTR profiles. Artificial intelligence-based machine learning (ML) methods such as Random Forests (RF), Support Vector Machines (SVM) and Artificial Neural Networks (ANN) were used to predict dominant spoligotypes of MTBC using MIRU-VNTR data. K-fold cross-validation and validation using unseen testing data set revealed high accuracy of ANN, RF, and SVM for predicting Beijing, CAS1_Delhi, and T1 Spoligotypes (93–99%). However, prediction using the external new validation data set revealed that the RF model was more accurate than SVM and ANN.

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Sikkim, India, has the highest proportion of tuberculosis (TB) patients on first-line anti-tuberculosis regimens with the outcome 'failure' or 'shifted to regimen for multidrug-resistant TB (MDR-TB)'. Objective: To assess the factors associated with non-response to treatment, i.e., 'failure' or 'shifted to MDR-TB regimen'. Methods: We conducted a retrospective cohort study using Revised National Tuberculosis Control Programme data of all TB patients registered in 2015 for first-line TB treatment. In addition, we interviewed 42 patients who had not responded to treatment to ascertain their current status. Results: Of 1508 patients enrolled for treatment, about 9% were classified as non-response to treatment. Patient factors associated with non-response were urban setting (adjusted odds ratio [aOR] 2.39, 95%CI 1.22-4.67), ethnicity (being an Indian tribal, aOR 1.73, 95%CI 1.17-2.57, Indian [other] aOR 1.83, 95%CI 1.29-2.60 compared to patients of Nepali origin) and those on retreatment (aOR 2.40, 95%CI 1.99-2.91). Of the patients interviewed, 28 (67%) had received treatment for drug-resistant TB. Conclusion: In Sikkim, one in 11 patients had not responded to first-line anti-tuberculosis treatment. Host-pathogen genetics and socio-behavioural studies may be required to understand the reasons for the differences in non-response, particularly among ethnic groups. * Data for 26 patients were not available and were therefore not included in the table. RNTCP = Revised National Tuberculosis Control Programme; TB = tuberculosis; MDR-TB = multidrug-resistant TB.

Background: Diagnosis and treatment of Latent Tuberculosis Infection (LTBI) remains to be one of the main bottlenecks in eradication of tuberculosis (TB). TB and LTBI risk among the residents of a congregate facility in a monastery, situated in a high-TB burden area, Sikkim, India, may be high due to their frequent travel history and has never been illustrated. Method: A population based cross sectional screening of all the monks and residents of Rumtek Monastery (Sikkim, India) was carried out for diagnosis of active TB and LTBI. TrueNat MTB and GenXpert MTB/Rif systems were utilized for active TB diagnosis, whereas QFT-plus IGRA analysis was carried out for LTBI detection. LTBI positive cases were followed up with TrueNat MTB system to diagnose any progression to active TB.Results: Among the 350 residents of the monastery, no participant was found to be having active TB infection; however, ~45% of residents were LTBI positive showing high exposure of disease to the monks belonging to various age groups (9-73 yrs). Participants with frequent travel history, family history of TB or having contacts with TB patients, showed higher percentage of LTBI. Similarly, abnormal BMI showed significant positive correlation with LTBI.Conclusion: This study provides status of high prevalence of LTBI among the residence of a congregate facility in a monastery. These results can be useful to design strategies to treat LTBI in the high TB burden area to achieve the goal of TB elimination.