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_6
Snippet: Our detailed analysis shows that, in the current phase, reliable short-and long-term forecasts are very difficult, if not impossible: In Fig. 1C ,D already the three example scenarios quickly diverge from each other, and consequently span a huge range of future case numbers. Thus, any uncertainty on the magnitude of our social distancing in the past two weeks can have a major impact on the case numbers in the next two weeks. Beyond two weeks, the.....
Document: Our detailed analysis shows that, in the current phase, reliable short-and long-term forecasts are very difficult, if not impossible: In Fig. 1C ,D already the three example scenarios quickly diverge from each other, and consequently span a huge range of future case numbers. Thus, any uncertainty on the magnitude of our social distancing in the past two weeks can have a major impact on the case numbers in the next two weeks. Beyond two weeks, the case numbers depend on our future behavior, for which we have to make explicit assumptions. We illustrate how the precise magnitude and timing of potential change points impact the forecast of case numbers (see Fig. 2 , main paper).
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