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Article · Public Administration and Civil Service · December 30, 2025

ARTIFICIAL INTELLIGENCE IN SANITARY AND EPIDEMIOLOGICAL MONITORING: CONCEPTUAL APPROACHES AND PERSPECTIVES

Zhanat SADUAKASSOVA, Margarita Kadyrovа, Vainius Smalskys, Ainagul M. Kuatbayeva

Zhanat Saduakassova
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Abstract

This work is aimed at forming a conceptual view of the introduction of artificial intelligence technologies into the sanitary and epidemiological monitoring system of Kazakhstan. This issue is particularly relevant in the context of global challenges manifested in rapid urbanization, industrial development, increasing international cooperation, the growth of trade relations, intensified migration flows, and the expansion of tourism. A major challenge for public health today is environmental change and the growth of anthropogenic factors that directly affect population health. The purpose of this research is to form a conceptual model and identify the main aspects of the implementing artificial intelligence in monitoring based on international experience. The materials and methods include the analysis of international publications, an expert survey among employees of sanitary and epidemiological service employees, and conceptual modeling of the integration of artificial intelligence into the sanitary and epidemiological monitoring system. Results and discussion: The analysis of the literature revealed numerous positive aspects of incorporating artificial intelligence into monitoring, while approaches to implementation are based on the needs of the field and managerial conditions. The results of expert opinions identified the main barriers within the sanitary and epidemiological service on the way to digitalization. The proposed conseptual model illustrates the potential of integrating artificial intelligence into the monitoring system in accordance with the principles of Data-Centric Governance. Keywords: artificial intelligence, digitalization, conceptual model, sanitary and epidemiological monitoring, public health, IT policy.

Data-Driven Disease SurveillanceArtificial Intelligence in Healthcare and EducationHealthcare Systems and Practicesartificial intelligencedigitalizationconceptual model

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