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INFECTIOUS DISEASE SPREADING: FROM DATA TO MODELS

  • Ana Pastore y Piontti
  • Nicola Perra
  • Luca Rossi
  • Nicole Samay
  • Alessandro Vespignani
Chapter

We live in an increasingly interconnected world where every day one billion cars take the road and more than two billion people travel each year by plane. Urbanization, growing populations, and global migrations are creating a new and complex battlefield in the fight against new and old diseases. As a result, we demand ever-increasing predictive power to anticipate future epidemic outbreaks and evaluate associated risks. In scientific terms, this power corresponds to the mathematical description of patterns found in real-world data needed to develop models that can be used to predict future events.

In the natural sciences, we are used to predicting the complex properties of new materials through precise measurements of physical quantities and the implementation of numerical models or studying the performance of a new airplane by means of computers before we even assemble one of parts. One of the most successful examples of predictive power is that of weather forecasts, which are...

Keywords

Infectious Disease Spread DATA FROM Potential Transmission Mechanisms User Modeling Perspective Mathematical Epidemic Models 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  • Ana Pastore y Piontti
    • 1
  • Nicola Perra
    • 2
  • Luca Rossi
    • 3
  • Nicole Samay
    • 1
  • Alessandro Vespignani
    • 1
  1. 1.Northeastern UniversityBostonUSA
  2. 2.University of GreenwichLondonUK
  3. 3.Institute for Scientific InterchangeTorinoItaly

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