Selected article for: "future case and short term"

Author: Jonas Dehning; Johannes Zierenberg; Frank Paul Spitzner; Michael Wibral; Joao Pinheiro Neto; Michael Wilczek; Viola Priesemann
Title: Inferring COVID-19 spreading rates and potential change points for case number forecasts
  • Document date: 2020_4_6
  • ID: c8zfz8qt_42
    Snippet: We used a formal Bayesian model comparison in order to validate the presence of change points. Our model comparison ruled out models with less than two change points (Tab. I,V). While this may seem trivial, it has important consequences for making the short-term forecasts that decision makers rely on. Demonstrating and quantifying the effect of change points in the past enables us to project the effects of recent change points, that are not appar.....
    Document: We used a formal Bayesian model comparison in order to validate the presence of change points. Our model comparison ruled out models with less than two change points (Tab. I,V). While this may seem trivial, it has important consequences for making the short-term forecasts that decision makers rely on. Demonstrating and quantifying the effect of change points in the past enables us to project the effects of recent change points, that are not apparent in the observed case numbers yet, into future forecasts. Hence, it is important to look out for and identify potential change points as early as possible, and incorporate them appropriately into forecasts.

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