Selected article for: "different model and exponential growth"

Author: Morten Gram Pedersen; Matteo Meneghini
Title: A simple method to quantify country-specific effects of COVID-19 containment measures
  • Document date: 2020_4_10
  • ID: aqwdg489_18
    Snippet: We simulated the dynamics of the SIQR model (Fig. 3) and found that the data of the different countries was very well fitted when assuming piecewise-constant time-variance in β. From Eq. 3 and Eq. 5 (see Methods) it can be shown analytically that following the transient and during the initial exponential growth, I/Q = (γ + τ −1 1 )/η, where the com-bined recovery/death rate γ can be estimated from data (see Methods). In other words, the re.....
    Document: We simulated the dynamics of the SIQR model (Fig. 3) and found that the data of the different countries was very well fitted when assuming piecewise-constant time-variance in β. From Eq. 3 and Eq. 5 (see Methods) it can be shown analytically that following the transient and during the initial exponential growth, I/Q = (γ + τ −1 1 )/η, where the com-bined recovery/death rate γ can be estimated from data (see Methods). In other words, the relation between Q and I follows directly from the data up to the factor η. With the value of η = 0.033/day that we use here, we obtain that, e.g., for Italy the number of hidden infectious individuals is ∼7 times the number of positive cases, whereas in N.Y.C. this number is as high as ∼15. In the other countries the value is 6-10. These I-to-Q-ratios are slightly higher than the result of a recent study on the number of unidentified infectious individual during the epidemic in China [8] , but in line with a study on the European countries [2] .

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