Introduction. The World Health Organization considers the values of antibody titers in the hemagglutination inhibition assay as one of the most important criteria for assessing successful vaccination. Mathematical modeling of cross-immunity allows for identification on a real-time basis of new antigenic variants, which is of paramount importance for human health. Materials and methods. This study uses statistical methods and machine learning techniques from simple to complex: logistic regression model, random forest method, and gradient boosting. The calculations used the AAindex matrices in parallel to the Hamming distance. The calculations were carried out with different types and values of antigenic escape thresholds, on four data sets. The results were compared using common binary classification metrics. Results. Significant differentiation is shown depending on the data sets used. The best results were demonstrated by all three models for the forecast autumn season of 2022, which were preliminary trained on the February season of the same year (Auroc 0.934; 0.958; 0.956, respectively). The lowest results were obtained for the entire forecast year 2023, they were set up on data from two seasons of 2022 (Aucroc 0.614; 0.658; 0.775). The dependence of the results on the types of thresholds used and their values turned out to be insignificant. The additional use of AAindex matrices did not significantly improve the results of the models without introducing significant deterioration. Conclusion. More complex models show better results. When developing cross-immunity models, testing on a variety of data sets is important to make strong claims about their prognostic robustness.

Introduction. The WHO regularly updates influenza vaccine recommendations to maximize their match with circulating strains. Nevertheless, the effectiveness of the influenza A vaccine, specifically its H3N2 component, has been low for several seasons. The aim of the study is to develop a mathematical model of cross-immunity based on the array of published WHO hemagglutination inhibition assay (HAI) data. Materials and methods. In this study, a mathematical model was proposed, based on finding, using regression analysis, the dependence of HAI titers on substitutions in antigenic sites of sequences. The computer program we developed can process data (GISAID, NCBI, etc.) and create real-time databases according to the set tasks. Results. Based on our research, an additional antigenic site F was identified. The difference in 1.6 times the adjusted R2, on subsets of viruses grown in cell culture and grown in chicken embryos, demonstrates the validity of our decision to divide the original data array by passage histories. We have introduced the concept of a degree of homology between two arbitrary strains, which takes the value of a function depending on the Hamming distance, and it has been shown that the regression results significantly depend on the choice of function. The provided analysis showed that the most significant antigenic sites are A, B, and E. The obtained results on predicted HAI titers showed a good enough result, comparable to similar work by our colleagues. Conclusion. The proposed method could serve as a useful tool for future forecasts, with further study to confirm its sustainability.

The aim of the study — demonstration of the capabilities of new generation geographic information system software and agent-based modeling for solving epidemiological problems (on the example of the spread of measles in a metropolis).Materials and methods. Examples of the use of thematic layers and the functionality of the geoinformation platform, as well as the developed multi-agent model of measles spread in the megalopolis, are given. The measles spread model is presented as following three independent sub-models or nested models: behavior model, infection model, infectious process model. The modularity and independence of the sub-models allow the useof the necessary statistical and clinical data, both directly related to the studied disease and demographic indicators, which are analyzed and stored in the thematic layers of the platform.Results. The developed software tools allow visualizing, analyzing and short-term forecasting of the spread of the disease in the study area, with the ability to generate reports, which can be a useful and relevant addition to the daily work of specialists, contribute to the improvement and deepening of practical skills and abilities, in accordance with the types and tasks of professional activities, as well as expand opportunities for assistance in management decision making.

Relevance . In the context of high coverage of the population with preventive measles vaccination (more than 90% according to official statistics), in recent years there has been a complication of the epidemic situation for this infection, which necessitates an in-depth study of the causes and factors that contributed to the increase in morbidity. The aim of the study was to assess the susceptibility of the population of Moscow to measles on the basis of preventive vaccinations coverage data in a planned immunization and on epidemic indications. Materials and methods. To achieve this goal, epidemiological, statistical methods and Geographic Information System (GIS) technologies were used; the electronic database of materials of sanitary and epidemiological investigation in measles foci was created. Results . Тhe practical applicability of the proposed approach was shown, risk groups for measles incidence were identified. Due to the low coverage of routine preventive vaccinations and epidemic indications (compared with official statistics), the most vulnerable to measles are the age groups from one to two years and from three to six years, where these indicators were the lowest among the total population surveyed (routine and epidemic indications: about 55.9%, 10.8% and 75.3%, 40% respectively). Among the adult population, a decrease in the coverage of preventive vaccinations was revealed as the age of contact persons increased from 81.3% in the age group 20–35 to 51.0% in the age group 36 years and older. With the help of GIS technology, the possibility of visualization of the disease spread in a specific period of time in a certain area of the observed city was shown. Conclusions . According to the results the situation with measles in Moscow remains tense. There is a need for correction of the population immunization with the aim of increasing vaccination coverage in the individual age groups, and correction of statistical accounting of the facts of vaccination.

Relevance. In the context of high coverage of the population with preventive measles vaccination (more than 90% according to official statistics), in recent years there has been a complication of the epidemic situation for this infection, which necessitates an in-depth study of the causes and factors that contributed to the increase in morbidity. The aim of the study was to assess the susceptibility of the population of Moscow to measles on the basis of preventive vaccinations coverage data in a planned immunization and on epidemic indications. Materials and methods. To achieve this goal, epidemiological, statistical methods and Geographic Information System (GIS) technologies were used; the electronic database of materials of sanitary and epidemiological investigation in measles foci was created. Results. Тhe practical applicability of the proposed approach was shown, risk groups for measles incidence were identified. Due to the low coverage of routine preventive vaccinations and epidemic indications (compared with official statistics), the most vulnerable to measles are the age groups from one to two years and from three to six years, where these indicators were the lowest among the total population surveyed (routine and epidemic indications: about 55.9%, 10.8% and 75.3%, 40% respectively). Among the adult population, a decrease in the coverage of preventive vaccinations was revealed as the age of contact persons increased from 81.3% in the age group 20–35 to 51.0% in the age group 36 years and older. With the help of GIS technology, the possibility of visualization of the disease spread in a specific period of time in a certain area of the observed city was shown. Conclusions. According to the results the situation with measles in Moscow remains tense. There is a need for correction of the population immunization with the aim of increasing vaccination coverage in the individual age groups, and correction of statistical accounting of the facts of vaccination.