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Article · Journal of Health Development · August 31, 2025

Цифровые решения в эпидемиологии: Международный опыт

Zhanat SADUAKASSOVA, М.Б. Кадырова

Zhanat Saduakassova
Open via DOIPDF

Abstract

This review presents the of digital epidemiology, which based on the use of digital data and analytical methods to detect, analyze, and prevent outbreaks of infections. Digital epidemiology can start early investigation, diagnosis, and response measures at the regional level, and it is a useful approach to traditional surveillance in the modern world. The article provides an overview of early warning systems, including ProMed-mail, HealthMap, EIOS, and MedISys, highlighting their effective application in the early detection of disease outbreaks through digital tools. The GLEAM project provides analytical and forecasting tools using the complex stochastic models of infection spread based on big data. Countries such as South Korea, Singapore, Taiwan, and Germany have demonstrated the effectiveness of digital epidemiology approach within the context of government initiatives that applied non-traditional medical data and digital solutions to manage disease outbreaks. The research methodology blends specialized techniques, such as a literature review, comparative analysis, and SWOT analysis. A comparative table of early warning systems highlights the advantages of systems that use big data from open sources with minimal human intervention. The SWOT analysis suggests that digital epidemiology has potential for implementation in Kazakhstan, raising the bar for epidemiological surveillance and monitoring. The study aims to analyze modern approaches to epidemiological surveillance and monitoring of infectious diseases and assess the prospects for implementation in the healthcare system in Kazakhstan.

Data-Driven Disease SurveillanceHistorical and modern epidemiology studiesCOVID-19 Digital Contact Tracingdigital epidemiologyearly warning systemsinfectious disease surveillance

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