BIG DATA ANALYTICS IN PUBLIC HEALTH SURVEILLANCE: OPPORTUNITIES AND LIMITATIONS
DOI:
https://doi.org/10.5281/zenodo.19533480Keywords:
Big Data Analytics, Public Health Surveillance, Digital Health, Outbreak Detection, Data SecurityAbstract
The development of digital technology has encouraged the use of big data analytics in public health, particularly in health surveillance systems. This study aims to comprehensively examine the opportunities and limitations of using big data analytics to improve the effectiveness of public health surveillance through a literature review approach. The method used is a literature review, analyzing various relevant scientific sources, such as international journals, health institution reports, and recent academic publications. The study results indicate that big data analytics has significant potential for improving early outbreak detection, real-time disease monitoring, and more accurate and rapid data-driven decision-making. The integration mixing information from multiple sources, including social media, electronic health records, and Internet of Things (IoT) devices, makes surveillance systems more predictive and responsive. However, a number of restrictions need to be addressed, such as data security and privacy concerns, data quality and interoperability challenges, restricted technological infrastructure, and gaps in human resource capacity. Furthermore, ethical and regulatory challenges also hinder optimal implementation. Therefore, a comprehensive strategy is needed to maximize the benefits of big data analytics while still considering the security, ethics, and sustainability of the health system.
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