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Models with several levels of mixing (households, workplaces), as well as various corresponding formulations for R 0 , have been proposed in the literature. However, little attention has been paid to the impact of the distribution of the population size within social structures, effect that can help plan effective interventions. We focus on the influence on the model outcomes of teleworking strategies, consisting in reshaping the distribution of workplace sizes. We consider a stochastic SIR model with two levels of mixing, accounting for a uniformly mixing general population, each individual belonging also to a household and a workplace. The variance of the workplace size distribution appears to be a good proxy for the impact of this distribution on key outcomes of the epidemic, such as epidemic size and peak. In particular, our findings suggest that strategies where the proportion of individuals teleworking depends sublinearly on the size of the workplace outperform the strategy with linear dependence. Besides, one drawback of the model with multiple levels of mixing is its complexity, raising interest in a reduced model. We propose a homogeneously mixing SIR ODE-based model, whose infection rate is chosen as to observe the growth rate of the initial model. This reduced model yields a generally satisfying approximation of the epidemic. These results, robust to various changes in model structure, are very promising from the perspective of implementing effective strategies based on social distancing of specific contacts. Furthermore, they contribute to the effort of building relevant approximations of individual based models at intermediate scales. [ABSTRACT FROM AUTHOR]

This study proposes and theoretically substantiates a unique mathematical model for predicting the spread of infectious diseases using the example of COVID-19. The model is described by a special system of autonomous differential equations, which has scientific novelty for cases of complex dynamics of disease transmission. The adequacy of the model is confirmed by testing on the example of the spread of COVID-19 in one of the largest regions of Ukraine, both in terms of population and area. The practical novelty emerges through its versatile application in real-world contexts, guiding organizational decisions and public health responses. The model's capacity to facilitate system functioning evaluation and identify significant parameters underlines its potential for proactive management and effective response in the evolving landscape of infectious diseases. [ABSTRACT FROM AUTHOR]

Objective: to identify modern epidemiological features of viral acute intestinal infections in children and adolescents in the Sakhalin Region.Materials and methods. Data on acute intestinal infection incidence obtained from statistical reports of the Rospotrebnadzor during 2021-2023 was compared with long-term average incidence rates calculated over the period before the COVID-19 pandemic (2010-2019) to perform epidemiological analysis. Incidence was calculated for different age groups; according to months of the year, monthly long-term average incidence rates were established. Index of seasonality, coefficient of seasonality, and index of seasonal growth were determined.Results and discussion. Manifestations of acute intestinal infections epidemic process in the Sakhalin Region indicate persisting conditions for an increase in the registration of both sporadic cases of diseases and outbreaks of infectious diarrhea. Viruses were prevailing in the structure of cases of known etiology (mainly caused by rotaviruses and noroviruses). Their intra-annual dynamics showed changes in rotavirus and norovirus infection incidence rates: a shift in periods of increased incidence, a decrease in the coefficient of seasonality, and for rotavirus infection, a decrease in the index of seasonal growth. Age-adjusted rotavirus infection incidence showed predominance of the infection among preschool-aged children; norovirus infection was frequently detected among schoolchildren and adolescents. An increase in the focality index may indicate ongoing problems in the public catering sector, non-compliance with sanitary rules and hygiene standards, and untimely detection and isolation of patients with acute intestinal infections.Conclusion. Obtained results confirm the epidemiological significance of viral gastroenteritis and the necessity of anti-epidemic measures optimization.

Introduction. The key step in agent-based modeling of epidemics, which allows researchers to take into account individual characteristics of people, is the creation of an artificial population. The main difficulty of this procedure is finding a balance between the detail of the population description and the computational efficiency of the calculations. The aim and objectives of the review: Critically analyze and summarize the current evidence on how to create artificial populations; evaluate the limitations and advantages of available approaches in solving various problems in epidemiology. Materials and methods. An analysis of literature sources devoted to agent-based modeling has been performed. The analysis is focused on algorithms for creating an artificial population with a given level of detail for modeling human respiratory infections. Results. The approaches to the creation of artificial populations are generalized. The main principles of realization of interaction between agents are revealed: by means of networks of contacts between agents and on the basis of taking into account the movement of agents between locations. The first approach is the most computationally efficient and simple; the second approach allows to better take into account the change in the behavior of agents during the development of the epidemic process. Conclusion. Agent-based modeling is an optimal tool for selecting the best scenario for epidemic control and investigating the role of individual characteristics of people in the development of epidemics. When creating an artificial population, it is important to include in the model factors that can be targeted for control. A significant limitation is the lack of factual data on population structure, but this can be overcome by using indirect data.

The spread of infectious diseases is significantly influenced by emergencies, particularly military conflicts, which disrupt healthcare systems and increase the risks of epidemics. The full-scale Russian invasion of Ukraine has exacerbated these challenges, causing environmental damage, mass displacement, and the breakdown of healthcare services, all of which contribute to the spread of infectious diseases. This study aims to develop a comprehensive methodology for assessing the impact of emergencies on the spread of infectious diseases, focusing on the full-scale invasion of Ukraine. The object of this study is to address epidemic threats posed by emergencies, particularly the increased spread of infectious diseases due to war-related disruptions. The subject of this study is methods and models of infectious disease transmission under conditions of emergencies, emphasizing the Russian full-scale invasion of Ukraine. The tasks of this study are to provide an analysis of the current state of research and develop a methodology for assessing the impact of emergencies on the spread of infectious diseases. The proposed methodology includes several key components. Comprehensive data from public health organizations includes infectious disease statistics, demographic shifts, healthcare disruptions, and environmental factors exacerbated by emergencies. Data preprocessing removes inconsistencies, standardization of formats, and normalization for population size differences. Machine learning models, including convolutional neural networks and recurrent neural networks, have been developed to simulate the spread of diseases based on demographic, environmental, and healthcare-related variables. Deep learning models analyze spatial and temporal patterns, whereas compartmental models such as SIR estimate changes in reproductive numbers (R₀ and Re). Additionally, models of excess mortality incorporate mixed effects to account for regional and time-based variations. The methodology incorporates real-time monitoring of epidemic threats using real-time data from multiple sources, enabling dynamic assessments of disease spread and facilitating predictive modeling. The models were trained on historical data and validated using cross-validation techniques to ensure robustness and reliability, with a specific focus on the pre- and post-invasion phases in Ukraine.Results: The study provides a comprehensive framework for collecting and processing data on infectious diseases and epidemic threats in emergencies. The proposed model introduces advanced machine learning and epidemiological models trained on pre- and post-invasion data to analyze disease transmission patterns and forecast future epidemic dynamics. Conclusion: The proposed methodology addresses current gaps in infectious disease during emergencies by integrating real-time data and machine learning techniques. This research improves decision-making in public health management and biosafety during crises, particularly in war-affected regions like Ukraine.

Relevance. Altai Krai (AK) is one of the least prosperous subjects of the Russian Federation in terms of the incidence of acute respiratory infections (ARI). Results of studying long-term and intra-annual dynamics of the incidence of ARI and community-acquired pneumonia (CAP) in various population groups of the AK in 2011–2021 led to a conclusion about possible connection between the characteristics of the epidemic process of ARI and environmental factors, primarily air pollution, as well as the widespread distribution of natural and atropurgic foci of tick-borne transmissible and zoonotic infections in the territory of the AK, along with the problems of diagnostics. Aim. Assessment of the possible influence of environmental factors on the formation of a high level of registered incidence of ARI in the Altai Territory, as well as diagnostics of some natural focal and zoonotic infections with fever and respiratory symptoms. Materials and methods. A retrospective epidemiological study was conducted based on annual and monthly official statistical reporting during 2011–2021 about the morbidity of the population, demographic and environmental features of the territory of the AK for each of the municipalities (MU), the average long-term incidence rates of ARI, VBP, tuberculosis, Siberian tick typhus (STT), ixodid tick-borne borreliosis, tick-borne viral encephalitis were calculated; appeals of the population regarding tick bites; population density and annual average sulfur dioxide (SO2) emissions. Pearson correlation coefficient was used to assess the strength of the relationship between the analyzed indicators; and seasonality coefficients and the method of trend-seasonal decomposition were used to assess the intra-annual dynamics of the incidence of ARI and CAP (for the period 2011-2019). To study seroprevalence of antibodies to C. burnetii, R. sibirica and SARS-CoV-2 in febrile patients with symptoms of ARI blood samples were collected in October 2022 from ten rural districts of the AK. Results and discussion. It was established that there was a significant direct correlation between the incidence of ARI and the amount of SO2 emissions into the atmosphere (r = 0.61, p < 0.001), as well as between the incidence of ARI and population density (r = 0.53, p < 0.001). The largest share (69%) of the total number of ARI cases in the Altai Territory in 2011–2021 was attributed to the cities of Barnaul, Biysk, Rubtsovsk, Zarinsk and Novoaltaisk, which are characterized by maximum SO2 emissions and population density. An additional contribution (8% total) to the incidence of ARI in the Altai Territory was attributed to 7 rural areas with the highest levels of SO2 emissions. Regardless of the ranking for the incidence of ARI and CAP, in 9 out of 10 areas selected for the study, patients had both anamnestic and diagnostic titers of antibodies to C. burnetii and/or R. sibirica. At the same time, coxiellosis cases in these areas were not registered for 12 years, and the number of cases of STT was much less than the probable number based on the proportion of patients which were seropositive to R. sibirica and had symptoms of ARI. IgM to SARS-CoV-2 were detected in 5 out of 203 examined samples, IgG – in 188 out of 203 examined samples, moreover 13.8% of samples had 118 to 499 BAU/ml, 40.9% of samples had 500 to 5000 BAU/ml, and the rest of samples had more than 5000 BAU/ml. Conclusion. Among all the variables analyzed in the study, the greatest role in the formation of the high level of registered incidence of ARI in the AK for many years belong to the high level of air pollution with SO2 emissions, high population density and, especially, their combination. Underdiagnosis of tick-borne rickettsioses and coxiellosis is of particular importance due to the unavailability of test kits for laboratory verification. Starting from 2020, a new coronavirus infection made some contribution to the registered incidence of ARI.

The aim of the work was to study the epidemiological situation on West Nile fever (WNF) in the Republic of Tatarstan in 2023.Materials and methods. An operational epidemiological analysis of WNF cases registered in the Republic of Tatarstan in 2023 was performed. In order to establish sources and risk factors for infection of the population, 987 samples of zoo-entomological material were examined for the presence of West Nile virus (WNV) markers. A set of laboratory diagnostic methods was used: ELISA, RT-PCR, sequencing.Results and discussion. It has been established that all cases of WNF were registered in the region in the summer-autumn period of 2023, mainly in August, among residents of the city of Kazan who had not traveled outside the Russian Federation and the Republic of Tatarstan over the past six months. The incidence rate of WNF in the Republic of Tatarstan was 0.20 per 100 thousand population, the mortality rate reached 12.5 %. Signs of damage to the central nervous system were present in 6 out of 8 (75 %) patients. The majority of people with severe clinical symptoms belonged to older age groups and had concomitant diseases. Cases of the infection were reported in all age groups, with the exception of children and adolescents. The spatial characteristics of morbidity have been investigated, indicating the diffuse nature of the distribution of cases. The integrated use of methods, consisting in the concurrent use of polymerase chain reaction and enzyme-linked immunosorbent assay, made it possible to laboratory confirm cases of WNF in patients at different stages of the disease. The circulation of a subvariant of the WNV of the second genotype in the Republic of Tatarstan, currently dominant in the southern and central regions of Russia, has been established. A set of measures has been proposed to optimize epidemiological surveillance and control of WNF in the Republic of Tatarstan.

Objective: to characterize the dynamics and intensity of the incidence of Q fever for the period from 2015 to 2022, to determine the risk areas for human infection in the Southern and North Caucasian Federal districts and in the new subjects of the Russian Federation.Materials and methods: for epidemiological analysis, materials from analytical reviews "The epidemiological situation of natural focal infectious diseases in the Southern and North Caucasus Federal Districts" and state reports "On the state of sanitary and epidemiological welfare of the population" for 2015-2022, reporting data from the Rospotrebnadzor Department for the Rostov region, «Center for Hygiene and Epidemiology in Russia Rostov region» and the Departments of Rospotrebnadzor for the DPR and LPR. From 2022–2023 PCR study was conducted for the presence of Coxiella burnetii DNA in samples of ixodic mites and small mammals in the Rostov region and in 2023 – in the DPR, LPR, Zaporizhia and Kherson regions.Results: the analysis of the territorial distribution of cases of Q fever in the Astrakhan region and Stavropol Territory revealed a cluster of the most disadvantaged areas. An analysis of the conditions of infection of patients with Ku fever in the Rostov region has established that the most likely transmission factors are environmental objects in private farms. The circulation of C. burnetii in natural biotopes of the Rostov region, DNR and LNR regions.Conclusions: the epidemic process of Ku fever is mainly local, limited in the context of municipal districts of Astrakhan and Rostov regions, Stavropol Territory. The sporadic incidence of Ku fever does not reflect its actual level. There is no convincing evidence indicating the leading role of farm animals as a primary link in the formation of the epizootic process of Q fever in anthropurgical foci.

Indirect disease transmission is modeled via a fractional-order discretetime Susceptible-Infected-Contaminant (SIC) model vaccination as a control strategy. Two control actions are considered, giving rise to two different models: the vaccine efficacy model and the vaccination impact model. In the first model, the effectiveness of the vaccine is analyzed by introducing a new parameter, while in the second model, the impact of the vaccine is studied incorporating a new variable into the model. Both models are studied giving population thresholds to ensure the eradication of the disease. In addition, a sensitivity analysis of the Basic Reproduction Number has been carried out with respect to the effectiveness of the vaccine, the fractional order, the vaccinated population rate and the exposure rate. This analysis has been undertaken to study its effect on the dynamics of the models. Finally, the obtained results are illustrated and discussed with a simulation example related to the evolution of the disease in a pig farm. [ABSTRACT FROM AUTHOR]

The paper analyzes the optimal lockdown policy using the SQAIRD model over a network with three population groups (young, adult, and old). We show that different lockdown policies may be justified by different socioeconomic structures (objective cost functions that are either convex or concave). We also show that a lockdown policy is always better than a laissez-faire policy, and a targeted policy specific to each group outperforms a uniform policy. In our benchmark example, we consider the case of Italy. Our simulations show that: (a) a lockdown policy is always better than the laissez-faire policy because it limits the costs generated by the pandemic in an uncontrolled situation; (b) a group-specific targeted lockout policy is more effective than a uniform policy to the extent that the groups differ. The latter is a less expensive targeted policy (as it optimally minimizes direct, indirect, and vaccination costs), and it is equally effective in controlling the pandemic. One finding of particular interest is that the optimal lockdown rate should be higher for the young and elderly than for adults. This is motivated by the fact that younger individuals are more likely to spread the virus in question asymptomatically. [ABSTRACT FROM AUTHOR]

The paper presents an analysis and assessment of risks of complication of epidemiological situation regarding cholera in the Russian Federation and a forecast for 2024. It briefly characterizes the dynamics of the epidemic process around the world during the last decade (2013–2022). The forecast of cholera importation into the Russian Federation, due to activity of the epidemic process in endemic countries, has been confirmed. In 2023, two cases of cholera importation from India were reported. It was established that the toxigenic strains isolated from patients belonged to the currently dominant in the world “post-Haitian” group, including in India and Bangladesh, with the genotype ctxB7 tcpACIRS rtxA4a VSP-IIΔ0495-0512. Furthermore, non-toxigenic Vibrio cholerae O1 strains were isolated from samples of biological material from persons arriving from India, containing preCTX prophage and distinct from the strain (ctxAB– tcpAEТ–) isolated from a patient with acute intestinal infection (Zaporozhye Region, Melitopol). Nontoxigenic NAG vibrios were isolated from 13 patients with acute intestinal infections, which is 1.9 times more than in 2022. Regardless of importations, a strain of V. cholerae O1 (ctxB1+tcpAEТ) of the “pre-Haitian” group was isolated from a water sample of a surface reservoir. 52 non-toxigenic V. сholerae O1 strains were found on the territory of 11 constituent entities of the Russian Federation, which is 18.9 % more than in 2022. In 2024, epidemiological risks of cholera importation from endemic countries to any administrative territory of the Russian Federation remain. The risks of epidemic manifestations of cholera are especially high in the territories of the constituent entities of the Russian Federation which are under ongoing emergency, due to migration processes, and the impact of other risk-forming factors that contribute to an increase in the degree of contact of the population with water bodies contaminated with cholera vibrios. If epidemic foci of cholera are to emerge in a neighboring country, there will be a high probability of spread of this infection in the stated constituent entities of the Russian Federation and in other territories of southern Russia. In the absence of epidemic manifestations of cholera, the possibility of occasional detection of toxigenic O1 serogroup strains in water samples due to unidentified introductions from cholera-affected areas cannot be ruled out.

An analysis of the epidemiological situation on West Nile fever (WNF) in the Russian Federation in 2023 has revealed an increase in the number of cases (210) relative to the year 2022 by 6.3 times, the long-term average value by 1.2 times. Manifestations of the epidemic process were characterized by a significant expansion in the number of territories, where cases of the disease were confirmed (24 constituent entities, including in 13 – for the first time); a long epidemic season; an increase in the proportion of cases with a severe clinical course and fatality rate, which significantly exceeded the long-term average across Russia (8.5 and 1.2 %, respectively). Patients with fever and other similar manifestations of WNF were examined for the presence of the disease markers in 50 entities of the Russian Federation. Continued trend towards a decrease in the volume of diagnostic studies carried out by medical organizations and an increase in the time required for the etiological deciphering of disease cases has been established. Serological examination of sample groups of healthy population was performed in 65 entities. Epizootiological monitoring was carried out in 74 entities, rate of infection of carriers and vectors with West Nile virus (WNV) was confirmed in 14 entities. In the territory of the European part of Russia and the North Caucasus, the circulation of WNV lineages 1, 2 and 4 with the dominance of WNV lineage 2 has been established. Data on the genetic heterogeneity of WNV lineage 2 strains that circulated in Russia in 2023 have been obtained. Based on an analysis of climatic factors, a forecast of WNF incidence in the Russian Federation for 2024 was prepared.

The COVID-19 pandemic, etiologically related to a new coronavirus, has had a catastrophic impact on the demographic situation on a global scale. The aim of this study was to analyze the manifestations of the COVID-19 epidemic process, the dynamics of circulation, and the rate of the spread of new variants of the SARS-CoV-2 virus in the Russian Federation. Retrospective epidemiological analysis of COVID-19 incidence from March 2020 to fall 2023 and molecular genetic monitoring of virus variability using next-generation sequencing technologies and bioinformatics methods were performed. Two phases of the pandemic, differing in the effectiveness of anti-epidemic measures and the evolution of the biological properties of the pathogen, were identified. Regularities of SARS-CoV-2 spread were determined, and risk territories (megacities), risk groups, and factors influencing the development of the epidemic process were identified. It was found that with each subsequent cycle of disease incidence rise, the pathogenicity of SARS-CoV-2 decreased against the background of the increasing infectiousness of SARS-CoV-2. Data on the mutational variability of the new coronavirus were obtained using the Russian platform of viral genomic information aggregation (VGARus) deployed at the Central Research Institute of Epidemiology. Monitoring the circulation of SARS-CoV-2 variants in Russia revealed the dominance of Delta and Omicron variants at different stages of the pandemic. Data from molecular genetic studies are an essential component of epidemiologic surveillance for making management decisions to prevent the further spread of SARS-CoV-2 and allow for prompt adaptation to pandemic control tactics. [ABSTRACT FROM AUTHOR]

Indirect disease transmission is modeled via a fractional-order discretetime Susceptible-Infected-Contaminant (SIC) model vaccination as a control strategy. Two control actions are considered, giving rise to two different models: the vaccine efficacy model and the vaccination impact model. In the first model, the effectiveness of the vaccine is analyzed by introducing a new parameter, while in the second model, the impact of the vaccine is studied incorporating a new variable into the model. Both models are studied giving population thresholds to ensure the eradication of the disease. In addition, a sensitivity analysis of the Basic Reproduction Number has been carried out with respect to the effectiveness of the vaccine, the fractional order, the vaccinated population rate and the exposure rate. This analysis has been undertaken to study its effect on the dynamics of the models. Finally, the obtained results are illustrated and discussed with a simulation example related to the evolution of the disease in a pig farm.

Relevance. The Altai Krai (AK) is among the least prosperous subjects of the Russian Federation in terms of the incidence of acute respiratory infections (ARI).Aim: to analyze the causes and conditions for the formation of a high incidence of ARI among the population of the Altai Krai based on an assessment of the long-term and intra-annual dynamics of the epidemic process in 2011–2021.Materials and methods. In the course of a retrospective epidemiological study according to the annual forms No. 2 of the state statistical observation (SOS) for 2011-2021 a comparative analysis of the incidence of ARI and community-acquired pneumonia (CAP) in various groups of the population of the AK, the Siberian federal district (SFD) and the population of the Russian Federation as a whole was carried out. Data for 2020–2021 («covid» period) was analyzed separately in comparison with the precovid period of 2011–2019. The intra-annual dynamics of the incidence of ARI and CAP in the AK were studied using the method of trend-seasonal decomposition according to the monthly forms No. 2 of the SOS.Results and discussion. It is established that in 2011–2021. the epidemic process of ARI in the AK was characterized by a higher level and rate of increase in the incidence of all population groups (adults and children, urban and rural) compared to the all-Russian and average for the Siberian Federal District; a higher proportion of children in the overall structure of ARI cases, despite the fact that the proportion of the child population did not exceed (or was even less) than in other regions; no decrease in the incidence of ARI in children in the period 2020–2021; the presence of a trend towards an increase in the incidence of ARI in both urban and rural residents in the pre-covid period; higher incidence in the rural population in 2011–2019 compared to the whole of the Russian Federation or the Siberian Federal District. A less pronounced role of the seasonal component in the registration of CAP was revealed, in comparison with ARI. In some years, an increase in the registration of CAP was observed in the spring-summer period. For 2020-2021 there was a close coincidence of the curves of the intra-annual dynamics of the registered incidence of ARI and COVID-19 among the general population, CAP and COVID-19.Conclusion. The obtained results indicate the need to study the possible impact of environmental factors, as well as the shortcomings of the etiological interpretation and differential diagnosis of some natural focal and zoonotic infections that occur with fever and respiratory symptoms on the formation of a high incidence of ARI in the Altai Territory.

The COVID-19 pandemic, etiologically related to a new coronavirus, has had a catastrophic impact on the demographic situation on a global scale. The aim of this study was to analyze the manifestations of the COVID-19 epidemic process, the dynamics of circulation, and the rate of the spread of new variants of the SARS-CoV-2 virus in the Russian Federation. Retrospective epidemiological analysis of COVID-19 incidence from March 2020 to fall 2023 and molecular genetic monitoring of virus variability using next-generation sequencing technologies and bioinformatics methods were performed. Two phases of the pandemic, differing in the effectiveness of anti-epidemic measures and the evolution of the biological properties of the pathogen, were identified. Regularities of SARS-CoV-2 spread were determined, and risk territories (megacities), risk groups, and factors influencing the development of the epidemic process were identified. It was found that with each subsequent cycle of disease incidence rise, the pathogenicity of SARS-CoV-2 decreased against the background of the increasing infectiousness of SARS-CoV-2. Data on the mutational variability of the new coronavirus were obtained using the Russian platform of viral genomic information aggregation (VGARus) deployed at the Central Research Institute of Epidemiology. Monitoring the circulation of SARS-CoV-2 variants in Russia revealed the dominance of Delta and Omicron variants at different stages of the pandemic. Data from molecular genetic studies are an essential component of epidemiologic surveillance for making management decisions to prevent the further spread of SARS-CoV-2 and allow for prompt adaptation to pandemic control tactics.

This study proposes and theoretically substantiates a unique mathematical model for predicting the spread of infectious diseases using the example of COVID-19. The model is described by a special system of autonomous differential equations, which has scientific novelty for cases of complex dynamics of disease transmission. The adequacy of the model is confirmed by testing on the example of the spread of COVID-19 in one of the largest regions of Ukraine, both in terms of population and area. The practical novelty emerges through its versatile application in real-world contexts, guiding organizational decisions and public health responses. The model’s capacity to facilitate system functioning evaluation and identify significant parameters underlines its potential for proactive management and effective response in the evolving landscape of infectious diseases.

According to the WHO, 90-95% of all infectious diseases are acute respiratory viral infections of various etiologies and influenza. The purpose of the research work is to study some epidemiological characteristics of acute infections of the upper respiratory tract with multiple or uncertain MULAIURT localization during the Covid-19 pandemic in the regions of Baku. Intensive (per 1000 population %) and extensive (0%) indicators of morbidity with acute upper respiratory tract infections were determined in the regions of Baku. During the research period, for the years 2020-2022, in 12 districts of Baku city (Binagadi, Khazar, Garadag, Narimanov, Nasimi, Pirallahi, Nizami, Sabail, Sabunchu, Surakhani, Yasamal, Khatai), statistics on morbidity with acute upper respiratory tract infections data were analyzed, analytical epidemiological analysis of absolute indicators among the population (0-17 years, including 0-1 years, 1-4 years, 5-13 years, 14-17 years and 18 years and older), by gender (women and men), was conducted based on the study of the dynamics of registration by years (2020-2022) and by months (seasonality) within the country. In 2022, the level of infection with MULAIURT in Baku was 2.5 times higher than in 2020. In 2022, the number of cases was already twice as high among both women and men. In 3 years, the incidence rates of MULAIURT were higher in the 18-year-old age group compared to the 0-17 age group. In 2020, the intensity indicator of the incidence of MULAIURT was 29.53 people per 1000 people in Sabail region (2.95%), in 2021 it was 82.29 people per 1000 people in Khazar region (8.22%), in 2022 90.20 people per 1000 people per year was set at the maximum level in Garadag district (9.02%). Binagadi, Khazar and Yasamal regions are the regional risk factor for getting sick with MULAIURT. In 2020, the maximum level of morbidity with MULAIURT was determined in December in Sabunchu district, in December in Khazar district in 2021, and in January in Yasamal district in 2022. [ABSTRACT FROM AUTHOR]

Teaching the discipline «Epidemiology» to foreign students is associated with certain difficulties due to both the lack of equivalents in the English language of terms and concepts used in Russia and the historically established difference in approaches to studying the occurrence and spread of diseases in human society. Schematically, in English-language literature and textbooks on epidemiology, the process of the occurrence of diseases is described on the model of the epidemiological triangle, in Russian literature – historically on the model of the epidemic process, the founder of the doctrine of which is L.V. Gromashevsky. The epidemiological triad is represented by the interaction of a human host, agent and environment – the basis of the epidemic process are 3 elements: the source of infection, the transmission mechanism and the susceptible organism. At first glance, the model of the epidemic process and the epidemiological triangle are somewhat similar. However, the model of the epidemic process according to L.V. Gromashevsky more clearly indicates the population level of the phenomenon, and the epidemiological triangle pays more attention /emphasis on the properties of the pathogen and its interaction with the human body (the level of organism) in the external environment. Teaching in the section «General epidemiology of infectious diseases» teaching about the epidemic process for foreign students is advisable to build from universal models such as the epidemiological triad, harmoniously combining the epidemiology of infectious and non-communicable diseases, followed by the separation of these concepts and the introduction of specific terminology adopted in Russia (source of infection, epidemic focus, transmission mechanism, transmission pathways). At the same time, along with non- communicable diseases, the processes of the spread of infections associated with the provision of medical care, sapronoses are most significantly illustrated with the help of an epidemiological triangle.

Relevance. The pandemic of a new coronavirus infection has become an unprecedented challenge for modern society. It took the entire population of the Earth by surprise, changing the lives of millions of people in the world in record time. Governments of different countries have reacted differently to the pandemic. The list of preventive measures and the timeliness of their adoption differed. Comparing and evaluating the experience of different countries and emergency response systems will help in the future to use best practices and models to combat future biological threats. The aim of the study was to identify and describe the features of the manifestation of the COVID-19 epidemic process in a number of countries, taking into account the ongoing anti-epidemic and preventive measures, and to hypothesize about the main factors that could potentially influence the differences in the manifestation of the COVID-19 epidemic process. Materials and methods. The choice of countries was conditioned by the purpose to compare the manifestations of epidemic process in our country with the great powers and economies of the world - USA and China and countries (Republic of Belarus and Sweden), which did not introduce lockdown and did not follow all WHO recommendations. To achieve this goal, a descriptive research method was used based on open source data, an analysis of relevant Russian and foreign literature was carried out (scientific electronic libraries PubMed and Elibrary; open sources of statistical information: Yandex DataLens Public: Coronavirus: Dashboard, Johns Hopkins University website, United Nations Population Division, World Bank, Global Panel Database on COVID-19 Pandemic Policy (Oxford COVID-19 Government Response Tracker), as well as the website of the World Health Organization (WHO), Our World in Data, Rospotrebnadzor and some media). Conclusion. The lowest incidence rate is observed in China (on average 315.1 per 100 thousand population [95% CI 314.8–315.4]), and the highest is in the USA (9957.7 per 100 thousand population [95% CI 9954.5–9960.9]). In terms of the number of tests conducted, the United States and Russia are in the lead. To date, the highest vaccination coverage and vaccination rate are observed in the PRC and amount to 92.4% and 90.1%, respectively. In general, these indicators do not reach 95% in all countries, which requires improving the quality of immunoprophylaxis measures. Anti-epidemic measures in the studied countries differed in their set, scope and severity of implementation. In China, Russia and the USA were held in full, and in Belarus and Sweden only partially, some of the events were not held at all. Thanks to the rapid creation of effective vaccines in Russia and China, it was possible to delay the onset of pronounced increases in morbidity at a later date, which, in turn, helped to reduce the burden on the healthcare system. At the same time, despite the obvious relevance of COVID-19, the question of a comprehensive study of the alleged risk factors (biological, social and natural) is still open. There is a certain probability that the virus will now be permanently present in the global population (it will become a seasonal disease).

Relevance. It is known that the main trigger for the development of the pandemic was the genomic diversity of viruses. Meanwhile, we did not find any studies on the influence of population susceptibility on the complex process of evolutionary transformations of the SARS-CoV-2 virus and their interdependent variability during the development of the pandemic. Aim. The study of the interdependent variability of two heterogeneous populations interacting in the dynamics of the development of the COVID-19 pandemic - the virus population and the population. Materials and methods. The study was conducted in the city of Perm from 03/01/2021. (Beginning of sequencing of the SARS-CoV-2 virus in the territory) until 01.01.2023. In weekly dynamics, the following were studied: SARS-CoV-2 genomic diversity (molecular genetic study of 2521 samples of biomaterial from patients), seroprevalence of the population (366,804 blood sera were examined for the presence of IgG), morbidity, disease prevalence rate and mortality (according to official statistics). The interpretation of the results was carried out in accordance with the provisions of the theory of self-regulation of parasitic systems by V.D. Belyakov. Results and discussion. An analysis of the genomic diversity of the virus during the pandemic made it possible to distinguish 5 periods. Three periods were characterized by the homogeneity of the pathogen population, when the variants Alpha, Delta and Omicron circulated. Two periods were characterized by the simultaneous circulation of two variants of viruses due to the adaptation of the virus to the changed habitat. Thus, the circulation of the Alpha variant in a population heterogeneous in terms of susceptibility (the proportion of seropositive ones increased to 52%) caused mutational changes in the virus genome with the formation of high transmission properties and high pathogenicity (according to the theory of V.D. Belyakov, the phase of formation of an epidemic variant). The formation of the epidemic variant of the pathogen (Delta genovariant) occurred within 12 weeks, it dominated for more than 6 months, increasing the incidence by 2.8 times, mortality by 17.3 times (epidemic spread phase). The increase in the incidence and large-scale vaccination increased the seroprevalence of the population to 70% or more. The Delta variant begins to adapt to a new habitat with a high proportion of immune organisms, the formation of the Omicron genovariant with high transmission and evasion of the immune response is underway (the phase of formation of the pathogen reservation variant). The pathogen population is heterogeneous; Delta and Omicron circulate simultaneously. Morbidity increases by 2.9 times, RT by 1.3 times, and mortality decreases by 5.1 times. Omicron replaces the Delta genovariant within 5 weeks, mortality decreases, while maintaining the distribution coefficient (reservation phase). Conclusions. Interdependent variability of the virus and the susceptibility of the population determined the phase development of the pandemic.

The review generalizes data on West Nile fever manifestations in Russian between 1963 and 2022. Researchers have deter-mined peculiarities of the endemic process typical for this arboviral infection: cyclic rises in incidence with an interval of 1 to 8 years; the disease cases being predominantly registered in the south of the European part of the country; elevated risks of the disease for people aged 60 years and older; most West Nile fever cases without affecting the central nervous system with a continuous steady increase in the share of neuroinvasive forms. There are ongoing discussions of a considerable growth in an area where West Nile fever spreads as the incidence of the disease has been registered in Central Russia and this calls for assessment studies aimed at determining the northern borders of the infection area. The reviewed studies also systematize data on the WNV carriers and vectors and highlight the necessity to conduct large-scale experimental studies with their focus on examining susceptibility of various species of vertebrates and arthropods to the West Nile virus and assessing the efficiency of its transmission. The West Nile virus population that circulates in Russia has been shown to be heterogeneous and represented by the genotypes 1, 2, and 4, of which the genotype 2 is prevailing at present. The review also provides the findings of our own research with its focus on the genomes of the West Nile virus isolates indicating circulation of various genetic variants of the pathogen belonging to the genotype 2. The reviewed studies consider issues related to establishing epidemiological surveillance and sanitary-anti-epidemic (preventive) measures regarding West Nile fever in Russia and the principles of their organization at the present stage.

Background. Constant assessment of the dynamics of the main characteristics of the epidemic process is the basic function of epidemiological surveillance of infectious diseases. The search for factors that determine changes in the characteristics of the epidemic process makes it possible to develop timely management decisions and reduce the risk of an increase in the scale of the pandemic. Moscow is the main centre of attraction for the population of other Russian regions with the most complex structure of social links and the highest population density. The purpose of the study is to identify factors that potentially determine the trends of observed changes using a molecular epidemiological analysis of the main characteristics of the epidemic process of a new coronavirus infection (COVID-19). Materials and methods. For the analysis, the data of Russian national genome sequence database of SARS-CoV-2 virus (VGARus) were combined with information on morbidity and mortality presented at the official internet resources стопкоронавирус.рф and Yandex DataLens, the dynamics of vaccination, COVID-19 disease incidence and hospitalization from the portal Gogov.ru. A multicentre retrospective observational epidemiological study was conducted to examine the sex and age structure of hospitalised patients. Anonymized case histories of patients with COVID-19 collected at different follow-up periods in the institutions of Moscow (41,561 cases) served as a source of data for the sex and age structure analysis. Results. We identified 11 periods with significantly different complex epidemiological characteristics. A decrease in the incidence among young people of working age during the period of restrictive measures was revealed. In 3 out of 11 worsening of the epidemic situation coincided with the beginning of the circulation of a new genetic variant of the pathogen COVID-19 (variants Wuhan, Delta, Omicron). A decrease in the incidence in the summer period was noted, regardless of the circulating genetic variants. Conclusion. A significant part of the observed dynamics of the characteristics of the epidemic process in Moscow can be explained by the properties of the pathogen, seasonality and dynamics of magnitude of the herd immunity. The influence of the dynamics of the herd immunity indicators on the course of the epidemic process is to be studied further.

Introduction. Among the available scientific literature, there are no publications addressing processes of self-regulation in the parasite-host population systems with reference to chronic infections, including the infection caused by the EpsteinBarr virus (EBV infection). The aim of the study is to assess manifestations of the epidemic process of chronic EBV infection through the lens of the basic tenets of the theory of self-regulation of parasitic systems. Materials and methods. The study was performed using data from scientific publications selected from such database sources as Scopus, Web of Science, Cochrane Library, PubMed, CyberLeninka, RSCI, etc. The list of analyzed publications included published articles of the authors of this study, reporting the results of the retrospective epidemiological analysis of the incidence of infectious mononucleosis in Russia in general and in Moscow in particular, as well as the results of the laboratory tests regarding the detection frequency of specific antibodies to EBV proteins. Results. The chronic course of EBV infection promotes a close long-term interaction between the pathogen and the host. The genetic variability of the pathogen and the functions of specific and nonspecific human immune defense systems play a key role in the interaction between two heterogeneous populations and underlie their phasal self-transformation. A variety of social and natural factors (adverse chemical, physical, biological, climatic impacts, etc.) trigger the reactivation of chronic EBV infection, thus providing the continuous existence of additional sources of infection in the host population. Conclusion. The analysis of the manifestations of chronic EBV infection in the context of the theory of self-regulation of parasitic systems promotes the understanding of the factors underlying the unevenness of its epidemic process. The obtained data can be adjusted for other infections having similar transmission mechanisms and virus life cycles (including other herpes infections) to map out strategies to control the epidemic process of chronic infections spread by aerosol transmission of the pathogen.

Features of the landscape and geographical conditions of the Samara region, the rich world of flora and fauna create favorable conditions for the existence of natural foci of infectious and parasitic diseases. The high population density, the presence of megacities (Samara, Togliatti), the passion of the inhabitants of the region for country recreation, together with developed agriculture, determine a high risk of infection of people with pathogens of natural focal infections.Objectives: to analyze the manifestations of the epidemic and epizootic processes of natural focal infections in the Samara region for its zoning according to the degree of danger of infection of the population with actual zoonoses.Methods. We used information on the incidence of the population (form No. 2 "Information on infectious and parasitic diseases") for the period from 2019 to 2021, data from an immunological examination of residents of municipalities using enzyme immunoassay, results of examination of environmental objects in natural foci (indication of genomes and antigens of viruses and bacteria) in vertebrates and their pellets (litter), arthropods using polymerase chain reaction and enzyme immunoassay. Cluster analysis was performed using the Statgraphics plus for Windows application program for a personal computer.Results. Territories with high, moderate and low risk of infection of the population of the Samara region with hemorrhagic fever with renal syndrome, viral tick-borne encephalitis, tularemia, leptospirosis, Q fever and West Nile fever were identified. It is shown that the most relevant zoonosis is hemorrhagic fever with renal syndrome.Discussion. Compiled cartographic mapping of the administrative formations of the Samara region with different risks of infection and disease of people with natural focal infections is relevant for planning preventive measures.

At present, a major challenge in research that addresses risks of hospital-acquired infections (HAIs) is the lack of methodological and theoretical studies generalizing the available knowledge in the sphere whereas applied works are plentiful. In recent years, methods of influence on the epidemic process of HAIs have been reassessed and some experts believe transition to the risk-based approach to be quite promising in this respect. This approach makes it possible to take timely measures aimed at reducing risks of such infections in advance. Since the risk-based approach within epidemiological safety is only starting to be integrated into the whole system of healthcare safety, development and specification of its individual components seems to be a promising trend in healthcare support. The key role in creating an effective system for control and surveillance over hospital-acquired infections belongs to activities related to development of scientific approaches to systematizing and unifying indicators that describe the subject area of HAIs risks in healthcare organizations of various profiles; improvement of the methodology for analyzing HAIs risks, the risk-based approach and risk management technologies within surveillance over such infections; optimization of science-based approaches to decision-making that relies on the risk-based approach and HAIs risk management technologies; development of methodical guidelines on monitoring, assessment, and prediction of HAIs risks in healthcare organizations of various profiles.

The primary objective of this study is to assess the informativeness of various parameters influencing epidemic processes utilizing the Shannon and Kullback–Leibler methods. These methods were selected based on their foundation in the principles of information theory and their extensive application in machine learning, statistics, and other relevant domains. A comparative analysis was performed between the results acquired from both methods, and an information system was designed to facilitate the uploading of data samples and the calculation of factor informativeness impacting the epidemic processes. The findings revealed that certain features, such as “Chronic lung disease,” “Chronic kidney disease,” and “Weakened immunity,” did not carry significant information for further analysis and hindered the forecasting process, as per the data set examined. The developed information system efficiently supports the assessment of feature informativeness, thereby aiding in the comprehensive analysis of epidemic processes and enabling the visualization of the results. This study contributes to the current body of knowledge by providing specific examples of applying the described algorithmic models, comparing various methods and their outcomes, and developing a supportive tool for analyzing epidemic processes. [ABSTRACT FROM AUTHOR]

Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of many countries. Hence, it is therefore important to minimize the economic damage, which includes both loss of work and treatment costs, quarantine costs, etc. Recent studies have presented many different models describing the dynamics of virus spread, which help to analyze the epidemic outbreaks. In the current work we focus on finding solutions that are robust to noise and take into account the dynamics of future changes in the process. We extend previous results by using a nonlinear model-predictive-control (MPC) controller to find effective controls. MPC is a computational mathematical method used in dynamically controlled systems with observations to find effective controls. [ABSTRACT FROM AUTHOR]

The aim of the review was to analyze and assess the epidemiological situation on cholera in the world and Russia in 2013–2022 and to make a forecast for 2023. Over the period of 2013–2022, 500 administrative territories affected by cholera were identified in various regions of 71 countries of Asia, Africa and America (the Caribbean region) with formation of 69 endemic foci in 16, 41 and 12 countries, respectively. In 2022, 1 209 301 cases of cholera were registered in 36 countries of the world. The intensity of epidemic process in Asian countries (Syria, Lebanon) increased. Unfavorable epidemiological situation on the African continent persisted. Epidemics and large outbreaks, which began in 2021–2022 due to emergency situations (ES) of social and natural character, continued. The prediction of the stability of the epidemiological situation on cholera in the territories of constituent entities of the Russian Federation (RF), given for 2022, has been confirmed. In 2022, 43 non-toxigenic strains of Vibrio cholerae О1 were isolated from surface water bodies, 8 V. cholerae nonO1/nonO139 strains – from humans. Similarity of those strains with genetically closely related ones isolated in the course of monitoring in previous years in Russia, Donetsk People’s Republic (DPR) and Zaporozhye Region was demonstrated. In 2023, the risks of importation of the infection into RF are retained. It is associated with the intensification of epidemic processes in Asian, African and Caribbean region countries. The extended border with Ukraine, to where importation of cholera from endemic countries is possible, contributes to increased degree of threat. Bioterrorism is also not excluded. The consequences of a possible cholera epidemic complication in DPR, Lugansk People’s Republic, Zaporozhye and Kherson Regions are exacerbated by social emergencies resulting in disruption of infrastructure, interruptions in water supply, etc. In the absence of implementation of the risks of importation of this infection on the territory of RF, a stable epidemiological situation on cholera will be retained. Detection of non-toxigenic V. cholerae O1 strains (including probability of clonal complexes formation), as well as strains of non-O1/non-O139 serogroups, which can be etiological factors of sporadic cases or outbreaks of diarrheal diseases, in surface water bodies is predicted.

Introduction. Identification of the groups of the population most susceptible to infection with hepatitis A virus (HAV) is a key component for the regulation of anti-epidemic measures during the activation of the epidemic process. The aim аssessment of the herd immunity to hepatitis A (HA) among different age groups of the population of the Republic of Tatarstan. Materials and methods. The analysis of the HA incidence of from 2006 to 2021 and the study of herd immunity to HA among 6,553 persons from different age groups that were not vaccinated against HA were carried out. Participants with protective concentrations of antibodies to HAV of 20 mMU/ml or more were considered as seropositive. Results. The analysis showed a low intensity of the epidemic process in general (3.6 0.3о/оооо), while the HA incidence among children and adults was significantly different, with incidence rates 2.3 times higher in the first group (6.9 0.9 and 3.0 0.3о/оооо, respectively). The epidemic process is determined by persons aged 1517 years (8.2 2.5о/оооо), 36 years (7.0 1.9о/оооо, 714 years (6.2 1.3о/оооо), the incidence among these age groups in all observed years remained the highest. In general, the proportion of seropositive children was 32.1 1.0%. Among adults, anti-HAV IgG antibodies in a protective concentration was detected in 68.2 0.7%. The highest frequency of anti-HAV IgG positive samples was observed among persons aged 5059 years 89.4 1.1%, in age group 4049 years 73.5 1.2%, in age group 3039 years 65.5 1.3%, and in age group 2029 years 48.2 1.6%. In total, 56.9 0.6% of the examined individuals had protective antibodies to HAV. The detection rates of anti-HAV IgG antibodies were significantly different in all age groups (p 0.05).

Relevance. The peculiarities of the course of the COVID-19 epidemic process in the regions of the world, as a rule, are determined by the epidemic risks characteristic of them. Identification and evaluation of the latter is necessary to improve measures to counter infection in a particular area. Aim. To study the features of the COVID-19 epidemic process in the regions of the North Caucasus, to identify and assess the impact of epidemic risk factors on the epidemic situation. Materials and methods. The data of the Departments of Rospotrebnadzor for the subjects of the North Caucasus, Internet resources: stopkoronavirus were used Russia, Johns Hopkins University and Our World in Data project. Statistical processing was carried out using methods of variation statistics and MS Excel software package (2016, USA). Correlation analysis was performed using Spearman's coefficient. Results. As of 01.12.2021, the incidence of COVID-19 in the Caucasus was lower than the Russian average (3890.0 and 65921.8 per 100 thousand population), and the mortality rate was higher (4.8 and 1.9%, respectively). The dynamics of the epidemic process as a whole repeated the situation in the Russian Federation, but with a delay of each phase by 2–3 weeks and had 4 periods of rising morbidity (waves), with the exception of the Stavropol Territory, the Republics of Adygea and Ingushetia, where three waves of morbidity were observed. In the Republics of Dagestan, Chechen and Adygea, a high proportion of community-acquired pneumonia was noted - 58.8, 47.0 and 34.1%, respectively. The mortality rate from a new coronavirus infection was higher than the national average in Dagestan (in the period of the 1st wave – 4.7%), Krasnodar Krai (in the period of the 2nd wave – 5.0%; 3 – 12.6%, in 4 – 9.9%), Karachay-Cherkess Republic (in the 3rd period of the rise – 9.0%) and in Stavropol Krai (in 4 – 7.6%). The lowest mortality from COVID-19 in the 3rd and 4th periods of the rise in morbidity in the North Caucasus was registered in Ingushetia – 2.2 and 2.1%, respectively. The exceptional situation in the Republic of Dagestan is due not only to a large proportion of community acquired pneumonia and high mortality from COVID-19, compared with other regions of the North Caucasus and Russia as a whole, but also to an increase in excess mortality in the republic. The excess of the average annual (over the previous 5 years) number of deaths in the Caucasus in 2020 was +19.8%, in 2021 +32.7%, in the Russian Federation as a whole 14.8 and 31.4%, respectively. Conclusion. The general epidemic risks of COVID-19 for the North Caucasus region have been identified – the level of vaccination, the implementation of non–specific prevention measures, as well as local risks for specific regions: in Dagestan – adherence to local mass ceremonies, as well as insufficient control over the implementation of restrictive measures, in Ingushetia – relatively high population density.

COVID-19 pandemic has significantly impacted the world, with millions of infections and deaths, healthcare systems overwhelmed, economies disrupted, and daily life changed. Simulation has been recognized as a valuable tool in combating the pandemic, helping to model the spread of the virus, evaluate the impact of interventions, and inform decision-making processes. The accuracy and effectiveness of simulations depend on the quality of the underlying data, assumptions, and modeling techniques. Ongoing efforts to improve and refine simulation approaches can enhance their value in addressing future public health emergencies. The Russian full-scale military invasion of Ukraine on February 24, 2022, has created a significant humanitarian and public health crisis, with disrupted healthcare services, shortages of medical supplies, and increased demand for emergency care. The ongoing conflict has displaced millions of people, with Spain ranking 5th in the world for the number of registered refugees from Ukraine. The research aims to estimate the impact of the Russian war in Ukraine on COVID-19 transmission in Spain using means of machine learning. The research is targeted at COVID-19 epidemic process during the war. The research subjects are methods and models of epidemic process simulation based on machine learning. To achieve the study's aim, we used forecasting methods and built a model of COVID-19 epidemic process based on the XGBoost method. As a result of the experiments, the accuracy of forecasting new cases of COVID-19 in Spain for 30 days was 99.79 %, and the death cases of COVID-19 in Spain – were 99.86 %. The model was applied to data on the incidence of COVID-19 in Spain for the first 30 days of the war escalation (24.02.2022 – 25.03.2022). The calculated forecasted values showed that the forced migration of the Ukrainian population to Spain, caused by the full-scale invasion of Russia, is not a decisive factor affecting the dynamics of the epidemic process of COVID-19 in Spain. Conclusions. The paper describes the results of an experimental study assessing the impact of the Russian full-scale war in Ukraine on COVID-19 dynamics in Spain. The developed model showed good performance to use it in public health practice. The analysis of the obtained results of the experimental study showed that the forced migration of the Ukrainian population to Spain, caused by the full-scale invasion of Russia, is not a decisive factor affecting the dynamics of the epidemic process of COVID-19 in Spain.

The COVID-19 pandemic, which has been going on for almost three years, has shown that public health systems are not ready for such a challenge. Measures taken by governments in the healthcare sector in the context of a sharp increase in the pressure on it include containment of the transmission and spread of the virus, providing sufficient space for medical care, ensuring the availability of testing facilities and medical care, and mobilizing and retraining medical personnel. The pandemic has changed government and business processes, digitalizing the economy and healthcare. Global challenges have stimulated data-driven medicine research. Forecasting the epidemic process of infectious processes would make it possible to assess the scale of the impending pandemic to plan the necessary control measures. The study builds a model of the COVID-19 epidemic process to predict its dynamics based on neural networks. The target of the research is the infectious diseases epidemic process in the example of COVID-19. The research subjects are the methods and models of epidemic process simulation based on neural networks. As a result of this research, a simulation model of COVID-19 epidemic process based on a neural network was built. The model showed high accuracy: from 93.11% to 93.96% for Germany, from 95.53% to 95.54% for Japan, from 97.49% to 98.43% for South Korea, from 93.34% up to 94.18% for Ukraine, depending on the forecasting period. The assessment of absolute errors confirms that the model can be used in healthcare practice to develop control measures to contain the COVID-19 pandemic. The respective contribution of this research is two-fold. Firstly, the development of models based on the neural network approach will allow estimate the accuracy of such methods applied to the simulation of the COVID-19 epidemic process. Secondly, an investigation of the experimental study with a developed model applied to data from four countries will contribute to empirical evaluation of the effectiveness of its application not only to COVID-19 but also to other infectious diseases simulations. Conclusions. The research’s significance lies in the fact that automated decision support systems for epidemiologists and other public health workers can improve the efficiency of making anti-epidemic decisions. This study is especially relevant in the context of the escalation of the Russian war in Ukraine when the healthcare system's resources are limited.

The COVID-19 pandemic has become a challenge to public health systems worldwide. As of June 2022, more than 545 million cases have been registered worldwide, more than 6.34 million of which have died. The gratuitous and bloody war launched by Russia in Ukraine has affected the public health system, including disruptions to COVID-19 vaccination plans. The use of simulation models to estimate the necessary coverage of COVID-19 vaccination in Ukraine will make it possible to rapidly change the policy to combat the pandemic in the wartime. This study aims to develop a COVID-19 vaccination model in Ukraine and to study the impact of war on this process. The study is multidisciplinary and includes a sociological study of the attitude of the population of Ukraine toward COVID-19 vaccination before the escalation of the war, the modeling of the vaccine campaign, forecasting the required number of doses administered after the start of the war, epidemiological analysis of the simulation results. This research targeted the COVID-19 epidemic process during the war. The research subjects are the methods and models of epidemic process simulation based on statistical machine learning. Sociological analysis methods were applied to achieve this goal, and an ARIMA model was developed to assess COVID-19 vaccination coverage As a result of the study, the population of Ukraine was clustered in attitude to COVID-19 vaccination. As a result of a sociological study of 437 donors and 797 medical workers, four classes were distinguished: supporters, loyalists, conformists, and skeptics. An ARIMA model was built to simulate the daily coverage of COVID-19 vaccinations. A retrospective forecast verified the model's accuracy for the period 01/25/22 - 02/23/22 in Ukraine. The forecast accuracy for 30 days was 98.79%. The model was applied to estimate the required vaccination coverage in Ukraine for the period 02/24/22 – 03/25/22. Conclusions. A multidisciplinary study made it possible to assess the adherence of the population of Ukraine to COVID-19 vaccination and develop an ARIMA model to assess the necessary COVID-19 vaccination coverage in Ukraine. The model developed is highly accurate and can be used by public health agencies to adjust vaccine policies in wartime. Given the barriers to vaccination acceptance, despite the hostilities, it is necessary to continue to perform awareness-raising work in the media, covering not only the events of the war but also setting the population on the need to receive the first and second doses of the COVID-19 vaccine for previously unvaccinated people, and a booster dose for those who have previously received two doses of the vaccine, involving opinion leaders in such works.

Background. The ongoing pandemic of the novel coronavirus infection (COVID-19) draws attention to the significance of molecular and genetic monitoring of the SARS-CoV-2 spread among the population of the Russian Federation. The aim of the study was to analyze the dynamics of circulation of SARS-CoV-2 genetic variants in Russia. Materials and methods. The analysis of the circulation dynamics for SARS-CoV-2 genetic variants in Russia was carried out, covering the period from 28/12/2020 to 26/6/2022. The analysis included the data from Rospotrebnadzor Report No. 970 "Information about Infectious Diseases in Individuals with Suspected Novel Coronavirus Infection" and the Virus Genome Aggregator of Russia (VGARus). The presence of SARS-CoV-2 RNA was confirmed by the real-time reverse transcription polymerase chain reaction. The primer panels developed at the Central Research Institute of Epidemiology were used for amplification of genomic fragments and the subsequent sequencing. Results and discussion. Using the Russian VGARus platform developed by the Central Research Institute of Epidemiology, we received the data on mutational variability of SARS-CoV-2. By monitoring the circulation of SARS-CoV-2 genetic variants in Russia from 28/12/2020 to 26/6/2022, we found that Delta and Omicron genetic variants prevailed at different stages of the epidemic. Conclusion. The data of molecular and genetic studies are an essential component of epidemiological surveillance, being critically important for making executive decisions aimed at prevention of further spread of SARS-CoV-2 and laying the groundwork for creating new vaccines.

In recent years there have been discussions about the universality of the theory of self-regulation of the epidemic process, developed by academician V.D. Belyakov. Its adequacy for infections with different mechanisms of pathogen transmission, as well as for different groups in the ecological classification of infectious diseases (anthroponoses, zoonoses, sapronoses) has been questioned. In this connection, it seemed relevant to test the applicability of the main provisions of the self-regulation theory to the manifestations of the COVID-19 epidemic process.The aim of the investigation was to determine whether the manifestations of COVID-19 epidemic process in the territory of Samara region were in compliance with certain provisions of the self-regulation theory of epidemic process by academician V.D. Belyakov.Material and methods. The study was conducted in the Samara region and Moscow, the study period: March 2020 – June 2022. The data of official statistics on morbidity, population mortality from COVID-19, morbidity of community-acquired pneumonia were used as research material. Elements of classical epidemiological analysis were used as research tools, for calculations we used Excel, Statgraphics plus for Windows programs.Results. The second (key) proposition of the theory of self-regulation of the epidemic process by academician V. D. Belyakov was shown to be applicable to the epidemic process COVID-19. On the example of COVID-19, as an infection with an unspecified group in the ecological classification of infectious diseases, the postulate of V.D. Belyakov on the relative autonomy of the course of the epidemic process in different territories was confirmed.

The analysis of global epidemics, such as SARS, MERS, and COVID-19, suggests a hierarchical structure of the epidemic process. The pandemic wave starts locally and accelerates through human-to-human interactions, eventually spreading globally after achieving an efficient and sustained transmission. In this paper, we propose a hierarchical model for the virus spread that divides the spreading process into three levels: a city, a region, and a country. We define the virus spread at each level using a modified susceptible–exposed–infected–recovery–dead (SEIRD) model, which assumes migration between levels. Our proposed controlled hierarchical epidemic model incorporates quarantine and vaccination as complementary optimal control strategies. We analyze the balance between the cost of the active virus spread and the implementation of appropriate quarantine measures. Furthermore, we differentiate the levels of the hierarchy by their contribution to the cost of controlling the epidemic. Finally, we present a series of numerical experiments to support the theoretical results obtained. [ABSTRACT FROM AUTHOR]

Background. The priority direction of the COVID-19 fight is the identification of target population groups. These are primarily elderly people. The purpose of this work is to conduct a comparative assessment of laboratory and instrumental indicators in patients with new coronavirus infection COVID-19 of different age groups. Materials and methods. A retrospective analysis of data on the study of age-related features of laboratory and instrumental indicators in COVID-19 was carried out. All patients were divided into 2 groups depending on age: group 1 (n=12) – patients younger than 60 years, group 2 (n=27) – patients older than 60 years. The results of laboratory and instrumental inducators were used for the analysis. The statistical analysis was carried out using the Student's criterion and the χ2 test. Results. Despite the fact that the percentage of lung damage was higher in younger patients by 10,5 %, mortality prevailed in the elderly (p

In recent years, it became clear that super-spreader events play an important role, particularly in the spread of airborne infections. We investigate a novel model for super-spreader events, not based on a heterogeneous contact graph but on a random contact rate: Many individuals become infected synchronously in single contact events. We use the branching-process approach for contact tracing to analyze the impact of super-spreader events on the effect of contact tracing. Here we neglect a tracing delay. Roughly speaking, we find that contact tracing is more efficient in the presence of super-spreaders if the fraction of symptomatics is small, the tracing probability is high, or the latency period is distinctively larger than the incubation period. In other cases, the effect of contact tracing can be decreased by super-spreaders. Numerical analysis with parameters suited for SARS-CoV-2 indicates that super-spreaders do not decrease the effect of contact tracing crucially in case of that infection. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has posed a challenge to public health systems worldwide. As of March 2022, almost 500 million cases have been reported worldwide. More than 6.2 million people died. The war that Russia launched for no reason on the territory of Ukraine is not only the cause of the death of thousands of people and the destruction of dozens of cities but also a large-scale humanitarian crisis. The military invasion also affected the public health sector. The impossibility of providing medical care, non-compliance with sanitary conditions in areas where active hostilities are occurring, high population density during the evacuation, and other factors contribute to a new stage in the spread of COVID-19 in Ukraine. Building an adequate model of the epidemic process will make it possible to assess the actual statistics of the incidence of COVID-19 and assess the risks and effectiveness of measures to curb the curse of the disease epidemic process. The article aims to develop a simulation model of the COVID-19 epidemic process in Ukraine and to study the results of an experimental study in war conditions. The research is targeted at the epidemic process of COVID-19 under military conditions. The subjects of the study are models and methods for modeling the epidemic process based on statistical machine learning methods. To achieve the study's aim, we used forecasting methods and built a model of the COVID-19 epidemic process based on the polynomial regression method. Because of the experiments, the accuracy of predicting new cases of COVID-19 in Ukraine for 30 days was 97,98%, and deaths of COVID-19 in Ukraine – was 99,87%. The model was applied to data on the incidence of COVID-19 in Ukraine for the first month of the war (02/24/22 - 03/25/22). The calculated predictive values showed a significant deviation from the registered statistics. Conclusions. This article describes experimental studies of implementing the COVID-19 epidemic process model in Ukraine based on the polynomial regression method. The constructed model was sufficiently accurate in deciding on anti-epidemic measures to combat the COVID-19 pandemic in the selected area. The study of the model in data on the incidence of COVID-19 in Ukraine during the war made it possible to assess the completeness of the recorded statistics, identify the risks of the spread of COVID-19 in wartime, and determine the necessary measures to curb the epidemic curse of the incidence of COVID-19 in Ukraine. The investigation of the experimental study results shows a significant decrease in the registration of the COVID-19 incidence in Ukraine. An analysis of the situation showed difficulty in accessing medical care, a reduction in diagnosis and registration of new cases, and the war led to the intensification of the COVID-19 epidemic process.

Relevance. The formation of humoral immunity is one of the most important manifestations of the protective mechanism against an infectious disease. The formation of antibodies with neutralizing activity is a key factor in preventing infection.Aims. Analysis of the esults of an ELISA study for the presence of IgM and IgG antibodies to the causative agent of a new coronavirus infection (COVID-19) in the population of the Central Orenburg region.Materials and methods. Immunoassay of blood serum for the presence of IgM and IgG antibodies using ELISA test by Vectro-Best (Novosibirsk, Russia).Results and discussion. The analysis revealed the presence of more than half of the cases of seroconversion among the examined individuals. The most surveyed was the group aged 21 to 65 years. The most typical humoral immune response to SARS-CoV-2 has been established, and the age-related characteristics of its formation have been determined. The dependence of the positivity coefficient on the age of the patients was revealed.Conclusions. According to the results of the study, the formed humoral (collective) immunity to the SARS-CoV-2 virus was registered in more than half of the studied sample.

The aim of the work was to summarize the results of cholera monitoring in 2021, to assess current trends in the development of the epidemic process, and to predict the epidemiological situation in the Russian Federation for 2022. It was established that within the period of 2012–2021, 4117264 cases of cholera with the spread of infection across 83 countries on all continents were registered in the world and there was a downward trend in the incidence in Asia and Africa. The dynamics of monthly morbidity in 2021 was associated with emergencies as factors of epidemiological risk. Epidemics and outbreaks of cholera were documented against the background of COVID-19 pandemic and laid a double burden on healthcare systems. At the same time, based on the overview of the results of cholera monitoring in the constituent entities of the Russian Federation, it was shown that the forecast of epidemic well-being given for 2021 was fully justified. It has been determined that the increase in the number of non-toxigenic strains of Vibrio cholerae O1 (67) isolated from water bodies compared to 2020 (25) is mainly due to the appurtenance of a number of isolates to clonal complexes. The study of phylogenetic relation has demonstrated that the detection of strains with genotypes which were previously identified in the isolates evidences the persistence potential. The identification of strains with new genotypes, which were earlier established in the strains circulating in other territories, pointed at the possibility of the occasional importations. The forecast of the epidemiological situation on cholera in Russia for 2022 is associated with the continuous existence of risks of introduction. If these epidemiological risks are not realized, a favorable epidemiological situation is predicted regarding this infection in the country. It is expected that the detection of epidemiologically insignificant strains of V. cholerae O1 in environmental water bodies, along with their clones and/or clonal complexes, will remain, including strains that may be an etiological factor in sporadic cases or outbreaks of disease.

Introduction. For more than 10 years, the Tumen Region has been reporting steadily high rates of HIV infection prevalence. Among the groups at risk for HIV infection, a special place is occupied by the group of incarcerated individuals. This group is mostly represented by drug users, men who have sex with men, commercial sex workers. Diseases acquired during imprisonment or exacerbated in a prison setting become a problem not only for released inmates, but also for communities outside the prison system. Epidemiologically, it is critically important to identify the prison-related factors contributing to HIV progression, considering their unequal significance among incarcerated individuals and civilian population. The aim of the study is to identify and assess the risk factors affecting the HIV epidemic process in the high riskgroup density areas. Materials and methods. The study was performed using epidemiological study and stepwise logistic regression methods. Results. Since 2008, the epidemiological situation in prison settings has become increasingly severe, being characterized by higher rates of detection of HIV cases and HIV prevalence among inmates. The situation has also been aggravated by high death rates among HIV-infected inmates. Our study found that the high risk of fatal outcomes in HIV-infected inmates was associated with multiple parameters: the male gender, parenteral (injection drug use) HIV transmission, existing comorbidities viral hepatitis and thoracic diseases.

Relevance. At the present stage, the Russian Federation does not have a coherent system of supervision and control of infection caused by the Epstein-Barr virus (EBV), while there is an epidemiological problem with this pathology, requiring the development and adoption of a set of adequate management decisions. The goal is to scientifically substantiate the creation of an epidemiological surveillance system (ES) for EBV -infection in Russia. Materials and methods. Based on the results of previous studies, an assessment of the manifestations of the epidemic process of EBV infection and measures aimed at each of its links was carried out. Results. The structure and content of the system of epidemiological surveillance of EBV infection are presented. Conclusion. To implement and improve the effectiveness of EBV-infection control, it is necessary to adjust existing and develop new regulatory and methodological documents that allow introducing: a standard definition of the case of EBV-infection and new approaches to accounting and registration; studies of nasopharyngeal smear material for the presence of EBV genetic material as part of the monitoring of influenza and ARVI pathogens; algorithms for the examination of patients with diagnoses that do not exclude the presence of active EBV-infection, as well as organ, tissue and cell donors with the determination of a complex of nonspecific immunological markers (neopterin, melatonin, C-reactive protein, ALT); standard operating procedures for medical professionals for the identification and isolation of patients with active EBV-infection, clinical and laboratory diagnostics, registration and accounting, the use of personal protective equipment and nonspecific immunoprophylaxis. Also, improving the control of EBVinfection is impossible without continuing scientific research; professional training of medical workers on the clinic, diagnosis, epidemiology and prevention of EBV-infection; development of modern visual methods and means of informing the population about the clinic and prevention of EBV-infection.

Infectious diseases are one of the most important problems of the modern world, for example, the periodic outbreaks of coronavirus infections caused by COVID-19, influenza, and many other respiratory diseases have significantly affected the economics of many countries. Hence, it is therefore important to minimize the economic damage, which includes both loss of work and treatment costs, quarantine costs, etc. Recent studies have presented many different models describing the dynamics of virus spread, which help to analyze the epidemic outbreaks. In the current work we focus on finding solutions that are robust to noise and take into account the dynamics of future changes in the process. We extend previous results by using a nonlinear model-predictive-control (MPC) controller to find effective controls. MPC is a computational mathematical method used in dynamically controlled systems with observations to find effective controls.

Objective: To study the regional features of the West Nile fever (WNF) epidemic process manifestations using the example of the territory with stable and long-term pathogen circulation (Volgograd Oblast).Materials and Methods: We used the data of the Reference Center for monitoring the WNF pathogen based on the Volgograd Research Anti-Plague Institute of Rospotrebnadzor over 1999–2021. The main method is a comprehensive epidemiological method.Results: The long-term changes in the WNF incidence in Volgograd Oblast is characterized by a cyclical nature with an interval of 1–8 years and a tendency to decrease. The maximum risk of infection occurs in August (58.8%), but there is an increase in the number of cases in September. The average duration of the epidemic season is 8.4 weeks. Case fatality rate is at the level of 4.3%; the prevalence of the number of deaths in the group of 70 years and older (75%), as well as among men (63.6%) has been established. The greatest contribution to the incidence rate is made by the age group of 60 years and older (37.7%). Features of the clinical presentation include the dominance of forms without damage to the central nervous system (91.1%) and moderate clinical course (72.3%). The prevalence of the urban population among the infected was noted (85.5%).Conclusion: A comparative analysis of the clinical and epidemiological WNF manifestations in Volgograd Oblast, territories with a stable circulation of the pathogen (Astrakhan and Rostov Oblasts) and, in overall, the Russian Federation, established differences in the duration of cyclical fluctuations in incidence, seasonality (Rostov Oblast), age structure of incidence (Astrakhan Oblast), distribution of cases by the severity of the clinical course, the site of the alleged infection and social status.

The article discusses aspects of the application of extrapolation and factor approaches to epidemiological forecasting, outlines the limitations and features of their application in relation to the prediction of morbidity.It is shown that when using an extrapolation approach, it becomes possible to predict the most likely numerical characteristics of morbidity in a certain time perspective. At the same time, the accuracy of the obtained forecast depends on the length of the time series and the type of long-term dynamics of morbidity. In turn, the trends formed by the results of forecasting artificially level the critical levels of morbidity that characterize individual periods of time and are fundamentally important for understanding the real picture.The factor approach is based on the prediction of morbidity levels using a certain set of factors. The difficulty of using the factor approach is noted due to the stochasticity of the epidemic process.Based on the results of a retrospective epidemiological analysis of the personalized morbidity of cadets of the Military Medical Academy, the heterogeneity of military contingents in susceptibility to acute respiratory infections of the upper respiratory tract is shown.From the standpoint of the academician V.D .Belyakov’s et al. theory of the parasitic systems self-regulation, the conclusion is made about the expediency of using a factor approach for epidemiological forecasting of morbidity in organized collectives. It is proposed to use the state of individual resistance as one of the main factors determining the epidemic well-being of organized collectives.The results of the development and testing of an electronic database that allows epidemiological surveillance of the morbidity of trainees and its linear prediction are presented.

Aim: To evaluate the epidemic situation on measles and rubella and to carry out the laboratory diagnostics of these infections in the North-West of Russia in the period of elimination.Materials and Methods. In 2016-2019 a total of 534 blood serum samples from patients with measles diagnosis, 210 – from patients with rubella diagnosis and 1251 – from patients with exanthema were studied by ELISA using “VectoMeasles-IgM” and “EIA-Rubella-IgM” test-systems.Results. Measles incidence in NWR varied from 0 to 0.96 per 100,000 in 2016 and 2019, respectively. Among measles patients the proportion of children and adults changed in 2018-2019, adults constituted 65.9%. Patients not vaccinated against measles and those with the unknown vaccination status were mainly involved in epidemic process (85%). High level of patients with revaccination status was revealed in 2018 (18.4%). These patients demonstrated high levels of IgG (>3.0 IU/ml) as well as high percentage of IgG avidity (>94.3%) on 4-7th day of rash onset thus evidencing secondary immune response. Molecular studies of the samples from patients revealed the circulation of D8 and B3 genotypes of measles virus. Strains of D8 and B3 genotypes were represented by 3 and 4 variants, respectively. Rubella incidence did not exceed 0.13 per 100,000. Strains of rubella virus of genotype 1E were detected.Conclusion. The data of annual measles incidence and molecular studies of circulating wild type measles viruses prove the on-going measles elimination process in the NorthWest of Russia. For rubella, the persistent phase of elimination was demonstrated in the region.