Selected article for: "fatality ratio and total case number"

Author: Tom Britton
Title: Basic estimation-prediction techniques for Covid-19, and a prediction for Stockholm
  • Document date: 2020_4_17
  • ID: 0fmeu4h4_18
    Snippet: In the previous subsection an epidemic model was fitted to the observed initial doubling time d and the known basic reproduction number R 0 . An important remaining task is to identify where in this outbreak the epidemic is at calendar time t 1 ("today") (cf. [1] ). We hence want to know which relative time t since the start of the epidemic that corresponds to the calendar time t 1 . In order to do so we use the observed total number of case fata.....
    Document: In the previous subsection an epidemic model was fitted to the observed initial doubling time d and the known basic reproduction number R 0 . An important remaining task is to identify where in this outbreak the epidemic is at calendar time t 1 ("today") (cf. [1] ). We hence want to know which relative time t since the start of the epidemic that corresponds to the calendar time t 1 . In order to do so we use the observed total number of case fatalities up to calendar time t 1 , denoted Λ(t 1 ). We further need approximate knowledge of two quantities: the typical duration s D between getting infected and dying (for those who die) and the infection fatality ratio f being defined as the probality that an individual who gets infected dies. For covid-10 s D ≈ 21 days but estimates of f vary in the range 0.2% − 1% (e.g. [13] , [12] ). Fortunately it turns out that the time calibration is not too sensitive to these numbers.

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