Analysis of long-term dynamics of morbidity by the method of complex assessment at different territorial levels

Abstract

Background: A comparative epidemiological analysis of the primary incidence of tuberculosis was carried out using its standard approach with a generalized indicator that takes into account the main statistical criteria for incidence. The "sensitivity" of the method may vary depending on the population in the analyzed territories.Aims: The aim of the study is a comparative assessment of the standard epidemiological approach and the method of integral assessment in the primary analysis of incidence at different territorial levels on the example of the epidemic process of tuberculosis.Materials and methods: A retrospective study of the dynamics of the incidence of tuberculosis in the total population at the levels of the federal districts (FD) of Russia, subjects of the Siberian Federal District (SFD) and urban municipalities of the Irkutsk Region (a structural unit of the SFD) for the period 20052019) was carried out. Based on the obtained integral indicators, a generalized visibility coefficient was calculated. Results: A statistically significant decrease in the incidence of TB was established at the level of all federal districts and subjects of the SFD. When assessing the average long-term incidence rates, the maximum discrepancy between ranking places was inversely proportional to the size of the studied territories: 1.5 positions - at the level of the FD, 2 positions - at the level of regional formations and 5 positions - at the level of urban settlements.Conclusions: The integral assessment method can be used in the primary analysis of morbidity in all types of infectious and non-infectious pathologies. The generalized morbidity criterion expands the informative possibilities of the standard indicator, contributes to the substantiation of risk areas already at the initial stages of epidemiological analysis, and responds more sensitively to changes in the epidemiological situation in relatively small areas.