Methodology for integral assessment of territorial epidemiological risk in the context of the evolutionary dynamics of dominant Mycobacterium tuberculosis genotypes

Background . Current tuberculosis monitoring methods rely on retrospective analysis and fail to account for the dynamics of the pathogen population's genetic structure. The lack of analytical tools capable of integrating molecular genetic indicators into quantitative risk models prevents a transition toward predictive, risk-based surveillance. The aim . To develop and justify a methodology for applying the territorial epidemiological risk index within the genomic surveillance system for multidrug-resistant and extensively drug-resistant tuberculosis in regions of the Russian Federation to investigate the dynamics of the epidemic process and forecast adverse trends. Materials and Methods . The index architecture is based on the consolidation of regional statistics and a complex of genotypic determinants: lineage-specific hazard weights, population frequencies, and drug resistance levels. Monte Carlo simulation (100,000 iterations) was employed to determine statistical thresholds for the epidemic significance of genotypes. Risk level scaling was performed through quartile analysis of the theoretical distribution (10,000 iterations). The tool was validated using data from four constituent entities of the Russian Federation with contrasting pathogen population structures. Results . Stochastic modeling established a critical expansion threshold of 2.15 (p < 0.001), enabling mathematically sound identification of epidemically significant genotypes. Quartile analysis facilitated an objective classification of territories based on the threat of situational destabilization. A high coefficient of determination (R^2 = 0.874) confirms that the pathogen population structure is a decisive factor in regional epidemiological distress. Conclusion . The developed index addresses modern epidemiological challenges by enabling the detection of cryptic expansion of aggressive genotypes before they are reflected in standard reporting forms. The tool is applicable within both polymerase chain reaction monitoring programs and whole-genome sequencing systems, serving as a universal platform for state sanitary and epidemiological control.