Conceptual Approaches to Responding to Public Health Emergencies in Ukraine at the Community Level

Abstract

Purpose to develop and substantiate conceptual approaches to managerial decision-making by specialists involved in the public health emergency response system at the community level under conditions of high uncertainty. Materials and methods. The study was based on regulatory and legal documents of legislative and central executive authorities of Ukraine, as well as scientific publications by domestic and international authors addressing public health system organization, epidemiological surveillance, emergency response, and the use of information technologies in decision support. Open data and analytical materials were also used as an information base. The following research methods were applied: bibliosemantic analysis, content analysis, systemic and comparative analysis. Approaches based on principles of mathematical analysis and information modeling were also considered. Results. It was determined that the initiation of the public health emergency response system begins at the community level when a physician (or other emergency services) identifies a suspected emergency situation, such as a relevant disease or other health threat, and submits an emergency notification to the local Center for Disease Control and Prevention, specifically to a field epidemiologist. The analysis of emergency response practices at the community level showed that decision-making processes are characterized by a high degree of uncertainty, time constraints, and the need to simultaneously consider information from multiple sources. These sources differ in completeness, reliability, and structure, which complicates their coordinated use under time pressure. This determines the relevance of applying mathematical models and methods that allow formalizing decision-making processes, integrating heterogeneous data, and improving the justification of managerial choices, including multi-criteria analysis methods, forecasting models, simulation modeling, and expert-based approaches. To accelerate and automate certain stages of decision-making, the integration of digital technologies is also appropriate, forming the basis for effective information systems that serve as decision support tools in emergency situations. The functioning of such decision support systems can be formalized into recommendations and practical tools aimed at improving response efficiency, including: recommendations for selecting optimal management actions depending on the type and parameters of the emergency; adaptive response algorithms tailored to specific epidemiological conditions; rules and protocols for decision-making during the first critical hours after detection; structured data collection tools (questionnaires, surveys, checklists); and scenario-based models for both typical and atypical situations, considering available resources and constraints. Conclusions. The existing response system, based on regulatory procedures, requires enhancement through tools that ensure integration of heterogeneous data sources and support the selection of alternative response strategies. In this context, the relevance of applying mathematical methods, including multi-criteria analysis, forecasting, simulation modeling, and expert evaluation, is substantiated. The proposed conceptual approach to building decision support systems enables the transformation of analytical results into practical response tools, such as recommendations, algorithms, rules, protocols, and checklists. The integration of mathematical methods and digital technologies into public health emergency response processes provides a foundation for improving the efficiency, consistency, and adaptability of decision-making at the local level. Additionally, the proposed approach creates a foundation for the development of adaptive decision-making frameworks capable of responding to rapidly changing epidemiological conditions. It also supports the standardization of response processes while preserving flexibility in unique or poorly structured emergency situations. Furthermore, the integration of these approaches enhances the coordination between different levels of the public health system, improving the overall resilience of emergency response mechanisms.