Abstract

Digital epidemiology has emerged as a transformative paradigm that integrates big data, computational modelling, 
and digital platforms into traditional public health surveillance. Driven by rapid advances in technology, data 
availability, and societal digitalisation, it leverages information generated from non-epidemiological sources such 
as social media, search engines, electronic health records, and mobility data to detect, monitor, and predict health 
events in real time. This review explores the foundations, methodological approaches, applications, and ethical 
considerations of digital epidemiology, highlighting its role in infectious disease monitoring, non-communicable 
disease (NCD) surveillance, and the assessment of health behaviours and social determinants. Big data 
technologies support more granular, timely, and wide-ranging insights than conventional epidemiological tools, 
enabling efficient resource allocation, improved intervention design, and enhanced outbreak preparedness. 
However, challenges persist regarding data quality, representativeness, interoperability, privacy, equity, and the 
validity of digital traces. As digital ecosystems grow increasingly complex, robust governance frameworks, 
methodological innovations, multi-sectoral collaboration, and sustained capacity-building efforts will be vital. This 
review concludes that digital epidemiology has significant potential to strengthen global public health systems, 
provided that technological opportunities are matched with ethical safeguards, inclusive policies, and 
interdisciplinary expertise.