"This book provides an introduction to the computational and complex systems modeling of the global spreading of infectious diseases. The latest developments in the area of contagion processes modeling are discussed, and readers are exposed to real world examples of data-model integration impacting the decision-making process. Recent advances in computational science and the increasing availability of real-world data are making it possible to develop realistic scenarios and real-time forecasts of the global spreading of emerging health threats. The first part of the book guides the reader through sophisticated complex systems modeling techniques with a non-technical and visual approach, explaining and illustrating the construction of the modern framework used to project the spread of pandemics and epidemics. Models can be used to transform data to knowledge that is intuitively communicated by powerful infographics and for this reason, the second part of the book focuses on a set of charts that illustrate possible scenarios of future pandemics. The visual atlas contained allows the reader to identify commonalities and patterns in emerging health threats, as well as explore the wide range of models and data that can be used by policy makers to anticipate trends, evaluate risks and eventually manage future events. Charting the Next Pandemic puts the reader in the position to explore different pandemic scenarios and to understand the potential impact of available containment and prevention strategies. This book emphasizes the importance of a global perspective in the assessment of emerging health threats and captures the possible evolution of the next pandemic, while at the same time providing the intelligence needed to fight it. The text will appeal to a wide range of audiences with diverse technical backgrounds."--Publisher's description.

Part I. How to model pandemics. Chapter 1. Infectious disease spreading: from data to models. Computational modeling of infectious disease spreading; Global Epidemic and Mobility Model -- Chapter 2. Data, data, and more data. Population; The age structure of the world population; Human mobility; Mobility patterns and epidemic spreading; Diseases; Health infrastructures -- Chapter 3. Data model integration: the global epidemic and mobility framework. Building a synthetic world; Moving people around; The disease dynamic; Synthetic epidemics -- Chapter 4. From data to knowledge: how models can be used. Affected countries; Invasion tree; Epidemic profiles and activity peak; Attack rate; Risk indicators and severity assessment; Containment and mitigation scenarios -- Chapter 5. The numerical forecast of pandemic spreading: the case study of the 2009 A/H1N1 pdm; Modeling the 2009 H1N1 pandemic; Calibration and parameter estimates for specific outbreaks; Forecast output; Invasion tree; Pandemic activity peaks; Risk and severity assessment; Vaccination campaigns; Real-time forecast with computational epidemic models -- Part II. Pandemic charts. Pandemic influenza. Barcelona, Spain; Buenos Aires, Argentina; Hanoi, Vietnam; Johannesburg, South Africa; Melbourne, Australia; New York City, USA -- Coronavirus. Barcelona, Spain; Guangzhou, China; Jeddah, Aaudi Arabia -- Ebola virus. Arua, Uganda; Kisangani, Democratic Republic of the Congo; Lagos, Nigeria -- Chapter 6. Computational modeling of "Disease X" -- Outlook.