Artificial Intelligence and Digital Health Innovations for Communicable Disease Surveillance, Prevention and Control, Volume II

Communicable diseases (CDs) remain a major global cause of morbidity and mortality, requiring effective surveillance, prevention, preparedness, and response across healthcare and community settings. Traditional public-health strategies continue to face persistent challenges, including fragmented surveillance systems, workforce shortages, unequal access to digital infrastructure, and delayed outbreak detection. Recent advances in artificial intelligence (AI), digital epidemiology, and digital health offer new opportunities to strengthen communicable disease surveillance, prevention, and control. From real-time surveillance and predictive modelling to automated decision support, digital contact tracing, and environmental monitoring, these tools are reshaping how infections are detected, prevented, and controlled.This Research Topic aims to address the gap between the potential of digital innovations and their practical, ethical, and equitable implementation in diverse real-world settings. We seek to showcase interdisciplinary research on digital and AI-enabled approaches that strengthen public-health decision-making, health-system resilience, outbreak preparedness, and communicable disease control. Building on emerging evidence in this field, Volume II will particularly emphasise real-world implementation, external validation, health-system integration, scalability, and measurable public-health impact.Key objectives include evaluating the effectiveness and utility of automated decision-support systems, improving resource allocation through predictive modelling, strengthening surveillance across healthcare and community settings, and addressing critical challenges related to data quality, interoperability, interpretability, privacy, bias, and global health equity. We seek to advance context-sensitive and sustainable solutions that support healthcare, community, and population-level prevention and response.We particularly welcome contributions addressing, but not limited to, the following themes:AI-Driven Communicable Disease Surveillance: Real-time outbreak detection and early-warning systems using clinical, laboratory, genomic, environmental, mobility, and digital-trace data; digital epidemiology and automated analysis of structured and unstructured health records.Predictive Modelling and Decision Support: Communicable disease transmission and burden modelling; AI-assisted risk assessment, public-health decision-making, and resource allocation; and evaluation of model performance, interpretability, and real-world utility.Digital Tools for Prevention and Response: Digital systems supporting vaccination planning, delivery, uptake, and coverage monitoring; digital contact tracing and exposure notification; risk communication, infodemic management, community engagement, and outbreak response.Digital Innovations for Infection Prevention and Control: Digital surveillance and risk prediction for healthcare-associated infections; integration of clinical, laboratory, infection prevention and control, and public-health data; and digital support for infection prevention, outbreak response, and workforce training.Digital Innovations for Antimicrobial Resistance: Predictive analytics for antimicrobial resistance patterns; digital tools for antimicrobial stewardship; automated phenotypic and genotypic resistance detection; and integrated laboratory, clinical, genomic, and environmental surveillance.Equity, Ethics, Governance, and Implementation: Bias, fairness, explainability, privacy, cybersecurity, and responsible data use; human–AI collaboration; health-system integration, implementation science, workforce capacity, digital inclusion, and scalable solutions for diverse and resource-constrained settings.We particularly encourage studies reporting real-world implementation, external validation, comparative evaluation, or measurable effects on public-health decision-making, health outcomes, equity, and health-system resilience. Topic editors: Marcello Di Pumpo, Francesco Baglivo, Silvana Gastaldi, Costanza Vicentini Source: https://www.frontiersin.org/research-topics/86522/artificial-intelligence-and-digital-health-innovations-for-communicable-disease-surveillance-prevention-and-control-volume-ii