Call for Chapters: AI-Enabled Monitoring of Avian Influenza for Human Health and Global Preparedness

Editors

Walid Ben Ameur, University of Gabes, Tunisia
P. S. Chouhan, Shree Tagore College, India

Call for Chapters

Proposals Submission Deadline: June 7, 2026
 Full Chapters Due: August 30, 2026
 Submission Date: August 30, 2026

Introduction

Avian influenza A viruses continue to represent a major threat to global public health, animal health, food security, and economic stability. Emerging and re-emerging subtypes such as H5N1, H9N2, H10N3, and H5N9 demonstrate a significant capacity for rapid evolution, genetic reassortment, interspecies transmission, and adaptation to humans. While some strains cause severe disease and high mortality in humans, others circulate silently in poultry and wild birds, creating reservoirs that may facilitate the emergence of future pandemic variants. The increasing complexity of influenza surveillance requires innovative and interdisciplinary approaches that integrate virology, epidemiology, veterinary science, environmental monitoring, genomics, and computational intelligence. In this context, artificial intelligence (AI) has emerged as a transformative tool for improving disease surveillance, outbreak prediction, genomic analysis, and public health preparedness. Machine learning algorithms, predictive modeling, data mining, and AI-assisted analytics can help identify patterns in viral evolution, detect early warning signals of outbreaks, and support rapid decision-making during health emergencies. This edited volume, AI-Enabled Monitoring of Avian Influenza for Human Health and Global Preparedness, aims to provide a comprehensive and forward-looking exploration of emerging avian influenza viruses and the growing role of AI-driven technologies in influenza monitoring and pandemic preparedness. The book will examine the biological, ecological, epidemiological, and computational dimensions of avian influenza while emphasizing One Health approaches that integrate human, animal, and environmental health data. By bringing together contributions from experts in infectious diseases, public health, veterinary medicine, computational biology, genomics, and AI research, this book seeks to establish an interdisciplinary platform for discussing current advances, challenges, and future directions in AI-enabled influenza preparedness and global health security.

Objective

This book intends to accomplish several important scientific and public health goals by combining perspectives from virology, epidemiology, veterinary science, artificial intelligence, and computational modeling. Specifically, the book aims to:  Provide a comprehensive overview of emerging avian influenza viruses and their implications for human and animal health.  Explore the epidemiology, transmission dynamics, mutation patterns, and zoonotic potential of influenza A virus subtypes.  Demonstrate how artificial intelligence and machine learning can improve surveillance, outbreak prediction, genomic analysis, and risk assessment.  Present advanced computational approaches for early-warning systems and pandemic preparedness.  Highlight the role of AI-assisted genomic surveillance in detecting viral evolution and reassortment events.  Promote interdisciplinary collaboration among virologists, epidemiologists, veterinarians, computational scientists, and policymakers.  Support One Health strategies that integrate environmental, animal, and human health data for disease prevention and response.  Identify current research gaps, methodological challenges, ethical considerations, and future opportunities in AI-enabled infectious disease monitoring.  Contribute to the development of evidence-based policies and global preparedness strategies for emerging zoonotic influenza threats. The book will add to current research by bridging biological and computational approaches, offering both conceptual foundations and practical applications for AI-assisted influenza surveillance and response systems.

Target Audience

This book is designed for a broad interdisciplinary audience involved in infectious disease research, public health preparedness, and computational health sciences. The primary audience includes:  Virologists and influenza researchers  Epidemiologists and infectious disease specialists  Public health professionals and policymakers  Veterinary scientists and One Health practitioners  Data scientists, bioinformaticians, and AI researchers  Computational biologists and genomic researchers  Healthcare professionals involved in outbreak preparedness and response  Graduate and postgraduate students in life sciences, public health, veterinary medicine, and computational biology  International organizations and governmental agencies focused on pandemic preparedness and zoonotic disease surveillance  NGOs and professionals working in disease monitoring and global health security  Researchers and professionals seeking to understand how AI technologies can enhance surveillance and management of emerging influenza viruses will particularly benefit from the interdisciplinary perspectives presented in this volume.

Recommended Topics

Potential chapter topics include, but are not limited to:  Overview of avian influenza A viruses and major subtypes  Molecular biology and evolution of influenza viruses  Ecology and natural reservoirs of avian influenza  Poultry production systems and transmission pathways  Epidemiology of H5N1, H9N2, H10N3, and H5N9  Zoonotic transmission and host adaptation mechanisms  Human infections and public health implications  Clinical manifestations and diagnosis of avian influenza infections  Viral mutation, reassortment, and emergence of novel strains  Genomic surveillance and sequencing technologies  AI-supported surveillance systems for influenza monitoring  Machine learning models for predicting viral emergence and spread  Deep learning approaches in infectious disease forecasting  AI-assisted genomic analysis and mutation prediction  Big data analytics in influenza epidemiology  Geographic information systems (GIS) and spatial modeling of outbreaks  Predictive modeling for pandemic preparedness  Computational epidemiology and outbreak simulation  Real-time outbreak detection using AI and digital surveillance  One Health approaches integrating human, animal, and environmental health data  Environmental and ecological drivers of influenza emergence  Wildlife surveillance and migratory bird monitoring  Veterinary public health and influenza control strategies  Vaccine development and antiviral resistance monitoring  Ethical considerations and data governance in AI-based surveillance  Policy frameworks and international collaboration for pandemic preparedness  Case studies of AI applications in infectious disease surveillance  Future directions in AI-enabled influenza research and global health preparedness

Submission Procedure

Researchers and practitioners are invited to submit on or before June 7, 2026, a chapter proposal of 1,000 to 2,000 words clearly explaining the mission and concerns of his or her proposed chapter. Authors will be notified by June 21, 2026 about the status of their proposals and sent chapter guidelines.Full chapters of a minimum of 10,000 words (word count includes references and related readings) are expected to be submitted by August 30, 2026, and all interested authors must consult the guidelines for manuscript submissions at https://www.igi-global.com/publish/contributor-resources/before-you-write/ prior to submission. All submitted chapters will be reviewed on a double-anonymized review basis. Contributors may also be requested to serve as reviewers for this project.

Note: There are no submission or acceptance fees for manuscripts submitted to this book publication, AI-Enabled Monitoring of Avian Influenza for Human Health and Global Preparedness. All manuscripts are accepted based on a double-anonymized peer review editorial process.

All proposals should be submitted through the eEditorial Discovery® online submission manager.

Publisher

This book is scheduled to be published by IGI Global Scientific Publishing, an international academic publisher of the "Information Science Reference", "Medical Information Science Reference", "Business Science Reference", and "Engineering Science Reference" imprints. IGI Global Scientific Publishing specializes in publishing reference books, scholarly journals, and electronic databases featuring academic research on a variety of innovative topic areas including, but not limited to, education, social science, medicine and healthcare, business and management, information science and technology, engineering, public administration, library and information science, media and communication studies, and environmental science. For additional information regarding the publisher, please visit https://www.igi-global.com. This publication is anticipated to be released in 2027.

Indexing Information for Prospective Authors

IGI Global Scientific Publishing meets the criteria for inclusion in major indexing services such as Scopus; however, it is important to note that all indexing decisions are made independently by these services. IGI Global Scientific Publishing books are selectively indexed by the indexing organization after publication. Indexing cannot be guaranteed for any book prior to publication, and the indexing organization has complete control over the final selection and timeline.

Important Dates

June 7, 2026: Proposal Submission Deadline
June 21, 2026: Notification of Acceptance
August 30, 2026: Full Chapter Submission
October 11, 2026: Review Results Returned
November 8, 2026: Final Acceptance Notification
November 15, 2026: Final Chapter Submission

Inquiries

Walid Ben Ameur, University of Gabes, benameurwalid@gmail.com | P. S. Chouhan, Shree Tagore College, prithvisinghchouhan5@gmail.com
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