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FROM DATA TO KNOWLEDGE: HOW MODELS CAN BE USED

  • Ana Pastore y Piontti
  • Nicola Perra
  • Luca Rossi
  • Nicole Samay
  • Alessandro Vespignani
Chapter
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BY INTEGRATING THE DATASETS we have explored in previous chapters and by performing the complex calculations necessary to numerically integrate the epidemic and mobility models, GLEAM can be used to produce microsimulations of infectious disease spreading.

Once all the parameters and initial conditions of an outbreak are plugged into the model, computers generate a large number of nominally identically initialized, numerical stochastic simulations of the global progression of the epidemic. The output provides, for each point in space and time allowed by the resolution of the model, the ensemble of possible epidemic evolutions. From this ensemble it is possible to define the median, mean, and confidence interval of epidemic observables, such as newly generated cases, seeding events, and the time of arrival of the infection amongst others. It is important to note that the forecast ensemble and the statistical quantities depend on the key parameters of each specific disease and on the...

Keywords

Epidemic Profile Epidemic Impact Eachpoint Relative Local Maximum Relative Risk Ranking 
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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