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_36
Snippet: Ideally, detected changes can be related to specific mitigation measures, so that one gains an understanding about the effectiveness of different measures (Fig. 3) . Indeed ; this inferred date matches the timing of the first governmental intervention including cancellations of large events, as well as increased awareness. After this first intervention, the (effective) growth rate λ * (t) = λ(t) − µ decreased by more than a factor 2, from me.....
Document: Ideally, detected changes can be related to specific mitigation measures, so that one gains an understanding about the effectiveness of different measures (Fig. 3) . Indeed ; this inferred date matches the timing of the first governmental intervention including cancellations of large events, as well as increased awareness. After this first intervention, the (effective) growth rate λ * (t) = λ(t) − µ decreased by more than a factor 2, from median λ 0 − µ = 0.3 to median λ 1 − µ = 0.14, given that the recovery rate was inferred as µ = 0.10 (CI [0.07, 0.14]). Second, λ(t) decreased from λ 1 = 0.24 to λ 2 = 0.15 (CI [0.12, 0.19]), which is larger than our prior assumption. The date of the change point was inferred to be March 16 (95% CI [15, 18] )]; this inferred date matches the timing of the second governmental intervention including closing schools and some stores. After this second intervention, the median growth rate became λ * (t) = λ 2 − µ = 0.05 ≈ 0 and is thus in the vicinity of the critical point, yet still positive. The first two interventions in Germany thereby mitigated the spread by drastically reducing the growth rate, but the spread of COVID-19 remained exponential. Third, λ(t) decreased from λ 2 = 0.15 to λ 3 = 0.10 (CI [0.07, 0.13]). The date of the change point was inferred to be March 23 (CI [21, 25] )]; this inferred date matches the timing of the third governmental intervention including contact ban and closing of all non-essential shops. Only after this third intervention, the median (effective) growth rate, λ * (t) = λ 3 − µ = −0.009 < 0 (CI [−0.039, 0.015])], finally became minimally negative, pointing at a possible decrease in the number of new infections. We can thus clearly relate the change points to the governmental interventions and quantify their mitigation effect. All rights reserved. No reuse allowed without permission.
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