Multiply Regression Analysis as An Integrated Approach in the TB Indicators Assessment in the Republic of Crimea

Golubova T. N.
PhD, Assistant Professor, Chair for Public Health, Health Organization and Health Economics¹

Ovsyannikova N. M.
PhD, Assistant Professor, Chair for Condensed Matter Physics, Physical Methods and Information Technologies in Medicine²

Makhkamova Z. R.
PhD, Assistant Professor, Chair for Public Health, Health Organization and Health Economics¹

Tkachenko I. Yu.
Director³

1 - S.I. Georgievsky Medical Academy of V.I. Vernadsky Crimean Federal University, Simferopol, Russia
2 - Physics and Technology Institute of V.I. Vernadsky Crimean Federal University, Simferopol, Russia
3 - State Budgetary Institution of the Republic of Crimea Crimean Republican Clinical Center of Phthisiology and Pulmonology

Golubova Tatiana; e-mail: tn.golubova@yandex.ru

None declared.

The study had no sponsorship.

The use of multiply regression analysis for the TB indicators assessment and prediction in the Republic of Crimea is discussed. Basic TB indicators in the Republic of Crimea for the period 2014-2018 were studied using Pearson correlation coefficient and step-by-step multiply linear regression analysis. During paired correlation analysis, dependable association with an average and high degree is identified for the most indicators of interest. The multiple correlation coefficients were higher than the paired correlation coefficients, which demonstrated the greater significance of the group conditionality of the indicators. For key epidemiological TB indicators the regression equations are constructed and the most relevant predictors are found using stepwise multiply regression analysis. The regression equations for TB incidence, prevalence and mortality rates are proposed for practical applying to predict epidemiological situation.

tuberculosis, indicators, epidemiologic situation, correlation analysis, multiply regression analysis, forecasting, Republic of Crimea

10.29234/2308-9113-2021-9-2-100-112

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