Mathematical Modeling, Simulations, and AI for Emergent Pandemic Diseases 1st Edition

Capture the forefront of outbreak science with Mathematical Modeling, Simulations, and AI for Emergent Pandemic Diseases, 1st Edition by Edgar Sanchez. This authoritative volume blends rigorous mathematical frameworks, large-scale simulations, and practical AI techniques to illuminate how emergent infectious diseases spread—and how policy and technology can shape the response.

Explore clear explanations of compartmental and agent-based models, data-driven forecasting, machine learning approaches for parameter estimation, and scenario simulations that inform public health decisions. Written for researchers, epidemiologists, data scientists, and public health professionals, the text bridges theory and practice with real-world case studies that span local, regional, and global outbreak contexts.

You’ll gain actionable insights into model selection, uncertainty quantification, calibration with real surveillance data, and the ethical use of AI in epidemic forecasting. Chapters guide readers from foundational mathematics to advanced simulation workflows, making complex concepts accessible without sacrificing technical depth.

Ideal for academic courses, research teams, and policy advisors, this book equips readers to evaluate model assumptions, design robust simulations, and translate computational results into clearer strategies for outbreak mitigation. Its multidisciplinary approach supports collaboration across epidemiology, computer science, and public health planning.

Whether you’re building predictive models, advising governments, or advancing pandemic research, Edgar Sanchez provides the tools to turn data into decisive action. Stay ahead in a world where rapid, evidence-based response matters—order your copy today and strengthen your capacity to understand, simulate, and respond to emergent pandemic threats.

Note: eBooks do not include supplementary materials such as CDs, access codes, etc.