Selected article for: "case number and control parameter"

Author: Benjamin F Maier; Dirk Brockmann
Title: Effective containment explains sub-exponential growth in confirmed cases of recent COVID-19 outbreak in Mainland China
  • Document date: 2020_2_20
  • ID: j0nm444m_42
    Snippet: is the i-th pair of a province's time and aggregated confirmed case number. Since the number of unidentified infectious is unknown per definition, the prefactor I 0 /X 0 ≥ 1 was chosen as a fit parameter. The remaining fit parameters were quarantine rate κ > 0 and containment rate κ 0 > 0. For the fit procedure, Eqs. (1)-(3) were integrated using the Dormand-Prince method which implements a fourth-order Runge-Kutta method with step-size contr.....
    Document: is the i-th pair of a province's time and aggregated confirmed case number. Since the number of unidentified infectious is unknown per definition, the prefactor I 0 /X 0 ≥ 1 was chosen as a fit parameter. The remaining fit parameters were quarantine rate κ > 0 and containment rate κ 0 > 0. For the fit procedure, Eqs. (1)-(3) were integrated using the Dormand-Prince method which implements a fourth-order Runge-Kutta method with step-size control, yielding I(t) and X(t) for every parameter configuration and every data set. The residuals were computed as

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