Digital epidemiology and public health surveillance: scientometric mapping of emerging technologies and challenges...

The rapid advancement of digital technologies has transformed traditional mechanisms of epidemiological surveillance and response, giving rise to an interdisciplinary field known as digital epidemiology. This study presents a scientometric mapping of the main trends, collaboration networks, and thematic foci linked to the use of emerging technologies-such as artificial intelligence, machine learning, big data, the Internet of Things (IoT), and social media mining-in global public health surveillance from 2000 to 2025. The methodology combines bibliometric and social network analysis on documents indexed in Scopus and Web of Science, complemented by a qualitative examination of the fifty most cited studies. The results reveal an exponential growth in scientific output starting from 2010, with an inflection point during the COVID-19 pandemic. The United States, the United Kingdom, and China stand out as the primary centers of production and international collaboration. However, significant gaps persist in digital equity, interoperability, and ethical governance, particularly in regions with lower technological infrastructure. This work contributes to understanding the evolution and challenges of digital epidemiology, proposing a future research agenda centered on algorithmic ethics, transparency, international cooperation, and technological inclusion in vulnerable contexts.