Selected article for: "growth rate and SIR model"

Author: Lionel Roques; Etienne Klein; Julien Papaix; Samuel Soubeyrand
Title: Mechanistic-statistical SIR modelling for early estimation of the actual number of cases and mortality rate from COVID-19
  • Document date: 2020_3_24
  • ID: dqg8fkca_35
    Snippet: On the value of R 0 . The estimated distribution in France is high compared to recent estimates (2.0-2.6, see [3] ) but consistent with the findings in [16] (2.24-3.58). A direct estimate, by a nonmechanistic method, of the parameters (ρ, t 0 ) of a model of the formδ t = e ρ (t−t0) gives t 0 = 36 (February 5) and ρ = 0.22. With the SIR model, I (t) ≈ I (α − β) for small times (S ≈ N ), which leads to a growth rate equal to ρ ≈ Î.....
    Document: On the value of R 0 . The estimated distribution in France is high compared to recent estimates (2.0-2.6, see [3] ) but consistent with the findings in [16] (2.24-3.58). A direct estimate, by a nonmechanistic method, of the parameters (ρ, t 0 ) of a model of the formδ t = e ρ (t−t0) gives t 0 = 36 (February 5) and ρ = 0.22. With the SIR model, I (t) ≈ I (α − β) for small times (S ≈ N ), which leads to a growth rate equal to ρ ≈ α − β, and a value of α ≈ 0.32, that is to say R 0 = 3.2, which is consistent with our distribution of R 0 . Note that we have assumed here a infectiousness period of 10 days. A shorter period would lead to a lower value of R 0 .

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