Abstract
A comparative analysis of methods for evaluating an integral indicator of population health, based on the summation of weighted arithmetic group averages, has shown that their advantage lies in the use of weighting coefficients, which improve the accuracy of the integral assessment. However, their disadvantage is the quality of expert assessments of the weighting coefficients, which depend on the segment selection and the number of experts, which requires their further improvement. The goal of the work is to develop a comprehensive integral indicator to assess the state of population health for the purpose of prompt situation assessment and decision-making. Methods Used: Modeling of the integral indicator of population health, based on the theory of mathematical statistics, systems of linear algebraic equations, and regression-correlation analysis. Novelty: The developed model of the integral indicator of population health, in the form of a function of individual statistical health indicators over time, allows for comparison and analysis of population health in spatial and temporal aspects. Results: The use of the presented methodological approach for creating a research base and developing an algorithm for calculating the integral indicator using regression-correlation analysis, the range amplitude of statistical indicators, situation analysis methods, event theory, and averages, allows for the assessment of the medical-demographic state both at the current moment and based on trend assessments using linear trends in the forecast period.