Digital Innovations in Veterinary Epidemiology: Tools for Disease Forecasting, Surveillance and Risk Management

The growing complexity of infectious disease emergence, especially zoonotic threats, demands a transformation in how veterinary epidemiology collects, analyzes, and acts on health data. In this evolving landscape, digital innovations are playing a central role in enhancing our capacity to detect, anticipate, and manage animal health risks. Tools such as AI-driven predictive models, interoperable surveillance platforms, remote sensing technologies, and real-time data systems offer new ways to monitor disease dynamics and support decision-making. These technologies are helping shift veterinary epidemiology toward more responsive, data-integrated approaches. Within a One Health framework, where animal, human, and environmental health are deeply interdependent, digital solutions can improve collaboration across sectors, provide early warnings, and support evidence-based interventions. This Research Topic explores the scientific advances and practical applications of digital tools that are reshaping veterinary epidemiology and improving preparedness for current and future disease threats.

This Research Topic aims to explore how digital technologies are reshaping veterinary epidemiology by enhancing our capacity to anticipate, monitor, and manage infectious disease risks in animal populations. As disease emergence becomes increasingly dynamic, driven by factors such as climate variability, global trade, and wildlife-livestock-human interactions, traditional surveillance methods often fall short in providing timely and actionable insights. To address this, we invite research focused on the development and application of digital tools for disease forecasting, outbreak detection, and risk assessment. These include predictive modelling, artificial intelligence, machine learning, deep learning, and data-driven decision support systems. Particular attention is given to approaches that combine multiple data sources such as clinical reports, environmental factors, mobility data to support surveillance and intervention strategies. While grounded in veterinary science, this collection encourages a systems-level view aligned with the One Health paradigm, where animal health is considered within broader ecological and public health contexts. By bringing together interdisciplinary efforts, this Research Topic seeks to highlight how digital innovations can improve preparedness and contribute to more resilient, adaptive disease control frameworks.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Community Case Study
• Conceptual Analysis
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Review
• Systematic Review
• Technology and Code

Keywords: Veterinary Epidemiology, Digital Health Technologies, One Health, Infectious Disease Emergence, Zoonotic Threats, Predictive Modeling, Artificial Intelligence, Disease Surveillance, Data Integration

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.