Introduction. Microbiological safety of water supply, sanitation and hygiene (WASH) is one of the priority tasks in maintaining and strengthening the public health. The purpose of this work was to review the results of foreign and domestic sanitary and microbiological studies on the microbiological safety of water supply, sanitation and hygiene (WASH). Search Strategies. The authors of this article codeveloped a search strategy that was the same for each database. Traditional search of sources by keywords was carried out in the PubMed, Scopus, Web of Science and Google Scholar databases in English, Russian and Kazakh languages with inclusion and exclusion criteria. Fifty-three sources out of 116 were selected as analytical materials. The depth of the search was from 1977 to 2020. The criteria for includingpublications in the review were as follows: publications in Russian and English that are in open full-text access and contain statistically confirmed conclusions. Summary reports, newspaper articles and personal messages were excluded from the review. Results. Ensuring the microbial safety of the drinking-water supply relies on the use of many barriers from the water collection to the consumer in order to prevent contamination from drinking water or reduce it to acceptable levels, not harmful to health. Safety is enhanced when multiple barriers against contamination are established, including protecting water resources, selecting and implementing a range of appropriate treatment measures, and regulating distribution systems (piped or non-piped) to maintain and protect the quality of treated water. The preferred strategy is a regulatory approach that focuses on preventing or reducing the entry of pathogens into water sources, and on reducing reliance on water treatment to remove pathogens. Conclusion. Thus, ensuring the microbial safety of WASH requires the following: an assessment of the entire system to determine the potential harmful factors that may affect it; determination of control measures to reduce or eliminate these harmful factors as well as operational monitoring to ensure the effective functioning of barriers from infection within the system; and developing regulatory plans to describe actions to be taken both under normal conditions and in unforeseen circumstances. Введение. Обеспечение микробиологической безопасности водоснабжения, санитарии и гигиены (ВСГ) является одной из приоритетных задач в сохранении и укреплении здоровья населения. Целью настоящей работы явился обзор результатов зарубежных и отечественных санитарно-микробиологических исследований по проблеме обеспечения микробиологической безопасности водоснабжения, санитарии и гигиены (ВСГ). Стратегия поиска. Авторы этой статьи совместно разработали стратегию поиска, которая была одинаковой для каждой базы данных. Традиционный поиск источников по ключевым словам проводился в базах данных PubMed, Scopus, Web of Science и Google Scholar на английском, русском и казахском языках по критериям включения и исключения. В качестве аналитического материала были выбраны пятьдесят три источника из 116. Глубина поиска составляла с 1977 по 2020 год. Критерии включения публикаций в обзор были следующими: полнотекстовые публикации на русском и английском языках, находящиеся в открытом доступе и содержащие статистически подтвержденные выводы. Краткие отчеты, газетные статьи и личные сообщения были исключены из обзора. Результаты. Обеспечение микробной безопасности питьевого водоснабжения основано на использовании множества преград на пути от водосбора до потребителя в целях предупреждения заражения питьевой воды или сокращения заражения до уровней, которые не вредны для здоровья. Безопасность возрастает, если установлено множество преград по предупреждению заражения, включая защиту водных ресурсов, надлежащий выбор и осуществление ряда мер по очистке, а также регулирование систем распределения (водопроводных или не водопроводных) для поддержания и защиты качества обработанной воды. Предпочтительной стратегией является подход регулирования, при котором основной акцент ставится на предупреждении или сокращении проникновения патогенных микроорганизмов в источники воды, а также на уменьшении зависимости от процессов очистки для удаления патогенов. Заключение. Таким образом, обеспечение...

The distribution of the health workforce affects the availability of health service delivery to the public. In practice, the demographic and geographic maldistribution of the health workforce is a long-standing national crisis. In this study, we present an approach based on Functional Principal Component Analysis (FPCA) of data to identify patterns in the availability of health workers across different regions of Kazakhstan in order to forecast their needs up to 2033. FPCA was applied to the data to reduce dimensionality and capture common patterns across regions. To evaluate the forecasting performance of the model, we employed rolling origin cross-validation with an expanding window. The resulting scores were forecasted one year ahead using Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) methods. LSTM showed higher accuracy compared to ARIMA. The use of the FPCA method allowed us to identify national and regional trends in the dynamics of the number of doctors. We identified regions with different growth rates, highlighting where the most and least intensive growth is taking place. Based on the FPSA, we have predicted the need for doctors in each region in the period up to 2033. Our results show that the FPCA can serve as a significant tool for analyzing the situation relating to human resources in healthcare and be used for an approximate assessment of future needs for medical personnel.

Purpose: The Successive Approximation Model (SAM) provides an iterative framework for developing digital learning resources, while artificial intelligence (AI) may enhance personalization and cognitive support. However, empirical evidence on the combined implementation of SAM and AI in medical education remains limited. This study aimed to evaluate the acceptability and perceived educational effectiveness of a biostatistics e-course developed using the SAM model and supplemented with an AI-supported component. Materials and Methods: A mixed-perspective descriptive study was conducted following the development and implementation of a modular biostatistics e-course based on the SAM at Karaganda Medical University. The course was developed through iterative prototyping, stakeholder feedback, and progressive refinement consistent with the SAM framework. Participants included 215 undergraduate medical students, 73 students involved in the needs assessment phase, and course developers. Questionnaires and descriptive analysis were used to gain staff perceptions of the SAM model of course development, student use of AI, and student evaluation of the quality of the course. Results: Across key evaluation domains, 64.7% of students reported positive perceptions of the course, including improved understanding of biostatistics and greater convenience compared with traditional learning formats, while negative responses remained below 12%. The AI component was used by 56.9% of students, primarily for explanation of theoretical material and analysis of statistical concepts. Among AI users, 82.1% reported improved understanding, and 53.7% reported increased motivation. However, 57.7% encountered errors, and trust in AI remained moderate. Developers positively evaluated the SAM model, particularly its iterative design and flexibility, while highlighting the need for methodological training and institutional support. Conclusion: The integration of SAM-based instructional design and AI-supported learning represents a feasible and acceptable approach to developing adaptive digital courses in medical education. Effective implementation depends on the balanced integration of instructional design, AI-mediated support, and institutional readiness.

Background: A good understanding of the demand for health services requires not only an analysis of the current and historical volume of health care provided but also relies on accurate forecasting of trends in the future. Such trends provide invaluable information for needs assessment, resource planning, facility evaluation and policy formulation. We set the task of assessing the load on the healthcare system of Kazakhstan in the next decade using indicators of general morbidity, outpatient visits, the need for medical personnel and financial costs of medical care. Methods: This study applies a dynamic Markov chain model to forecast population dynamics and ARIMAX method for healthcare demand forecasting. Results: In the next decade, the population of Kazakhstan is expected to grow by an average of 1.4% per year, reaching 23,334,397 people by 2033. The population growth will lead to an increase in the overall morbidity of the population in absolute values. The growth rate for children will be 1.6%, for adults - 0.8% per year. In this regard, the number of visits to medical specialists will increase by approximately 1.5% per year. Therefore, the demand for internists will increase by an average of 4.7% per year. The need for labour and material resources will entail an increase in financial costs. Total costs by 2033 will increase by 11.6% compared to 2023. Conclusions: Understanding the demand for health services requires not only the analysis of past and current health data but also relies on accurate forecasting of future trends. Assessing such trends provides invaluable information for identifying needs, planning resources, evaluating facilities, and formulating policies.

The aim of the study was to ensure logical and consistent implementation of training, as well as effective organization of the educational process. The study employed methods of system analysis, pedagogical design, and a modular approach. The materials included theoretical developments in the fields of didactics, pedagogy, and information technology, as well as practical experience in creating electronic educational courses. To implement the structuralmodular approach, the following stages of course design were developed: conceptual, technological, operational, and implementation. During the design process, multimedia technologies, interactive elements, and testing systems for knowledge assessment were applied. As a result of the study, the structure of an electronic educational course was developed, comprising three interconnected subsystems: content, information-navigation, and diagnostic. The content subsystem provides the theoretical foundation of the course, the information-navigation subsystem ensures convenient access to materials, and the diagnostic subsystem enables the monitoring and assessment of students' knowledge. The modular approach allowed the educational material to be divided into autonomous blocks, each aimed at achieving specific educational goals. This ensures the flexibility of the course, its adaptability to different levels of student preparation, and simplifies the process of updating content. Particular attention was paid to interactive elements, such as forums, assignments, tests, and multimedia materials, which contribute to increased motivation and engagement among learners. The developed course design methodology was tested in the educational process, confirming its effectiveness in improving the quality of learning. The structural-modular approach to designing electronic educational courses allows for the systematization of educational material, ensuring its logical sequence and accessibility.