Introduction/objective. The significant part of young people in the structure of hepatitis C virus (HC/HCV infection) incidence, a lot of latent cases of this infection, and the lack of specific prevention may complicate the epidemic situation regarding this infection in Ukraine in the coming years. The authors developed a mathematical model of the HC epidemiological process to determine the most significant factors in this infection transmission in the country.
Materials and methods. The study is based on correlation-regression analysis of the relationship between a dependent (or responding) and explanatory (factorial or predictors) variables. In total, the analysis involved 3 dependent variables y1, y2, y3, corresponding to the annual number of acute and chronic HC cases and the number of HC virus seropositive individuals, and 17 predictors x1 – x17, including patients who received etiotropic treatment; patients with mental and behavioral disorders due to narcotics use, including opioids; patients with sexually transmitted infections; the number of visits to dentists; the number of patients who had dentures placed; the number of surgical operations, blood transfusions, endoscopic examinations, laboratory blood tests, hemodialysis, etc. The number of observations (n) of dependent and explanatory variables was equal to 25, which corresponds to the number of administrative-territorial units in Ukraine (24 regions and Kyiv).
The quality of regression models was evaluated using multiple correlation coefficients (R), determination coefficients (R2), and regression coefficients (b0, b1, b2). Statistical significance of R2 was determined by F-statistics, regression coefficients – by standard errors (m), t-test, p-value, and the range of 95% confidence intervals (CI).
To compare the degree of influence of factor variables over dependent variables in the two-factor regression model, standardized regression coefficients were calculated.
The reliability of regression models was evaluated by the statistics of Durbin–Watson (DW), Breusch–Godfrey (BG), and White (W) tests.
The relative risk (RR) of HC infection was retrospectively determined in individuals from behavioral and medical risk groups.
Results. In mathematical model of the epidemic process of acute HC, statistical significance was demonstrated for only one variable effect – annual number of dentist visits. The obtained regression equation was as follows:
y1 = 0.000021 x5 – 11.353,
where y1 = annual number of patients with acute HC; х5 = annual number of dentist visits. Statistical characteristics of the model: R = 0.892, R2 = 0.796; F-test: 89.9 for 1 and 23 degrees of freedom, statistical significance for F: 0.0000000021; regression coefficients: b1= 0.000021 (m = ±0.0000023; t = 9.48, tcrit = 1.71; p = 0.0000000021; 95% CІ [0.000017; 0.000026]), b0 = -11.353 (m = ±3.982; t = 2.85, tcrit = 1.71; p = 0.009; 95% CІ [-19.59; -3.116]).
When developing a model of the epidemic process of acute HC taking into account the annual number of seropositive individuals, statistical significance was demonstrated only for two variables: annual number of the sexually transmitted infections and annual number of laboratory blood tests. The analytical relationship of variables in this model had the following mathematical expression:
y3 = 4.563 x4 + 0.0058 x15 – 36552.721,
where y3 = number of HCV-seropositive individuals; x4 = number of sexually transmitted diseases, x15 = number of laboratory blood tests.
Statistical characteristics of the model: R = 0.92, R2 = 0.842; F-test: 58.62 for 2 and 22 degrees of freedom, statistical significance for F: 0.00000000153; regression coefficients: b0= -36552.721 (m = ±10649.1; t = 3.43, tcrit = 1.71; p = 0.0024; 95% CІ [-58637.63; -14467.81]), b1 = 0.0058; m = ±0.00082; t = 7.1, tcrit = 1.71; р = 0.0000004; 95% CІ [0.0041; 0.0075]; b2 = 4.563; m = ±1.526; t = 2.99, tcrit = 1.71; р = 0.0067; 95% CІ [1.4; 7.73].
The Durbin–Watson and Breusch–Godfrey tests did not reveal autocorrelation of residues for both regression models: DWU < DWр < 4 – DWU; BG < χ2. White's test shows no heteroscedasticity for both models: W < χ2. The test results indicate the reliability of both regression models.
Conclusions. According to our data, at least 84% of HC virus infection cases in Ukraine occur through sexual contact and during laboratory blood sampling, and the role of the latter route of transmission in the HC virus spread was even more significant (standardized regression coefficients are 0.3 and 0.7, respectively).
Almost 80% of acute HC cases are associated with dental interventions.
Etiotropic treatment of patients with HC at the current level of treatment coverage can reduce the incidence of complications and the risk of death, but it is ineffective as a measure of influence on the first stage of the epidemiological process (source of infection).
Drug users have little effect on the intensity of the HC epidemiological process in Ukraine as a whole, despite the fact that the relative risk of HC among this population is quite significant (RR = 6.5; 95% CI [6.39; 6.63]).
Concealed correlations meta-analysis: A new method for synthesizing standardized regression coefficients
