Selected article for: "mortality ratio and SIR type model"

Author: Lucas Böttcher; Mingtao Xia; Tom Chou
Title: Why estimating population-based case fatality rates during epidemics may be misleading
  • Document date: 2020_3_30
  • ID: embnko1q_29
    Snippet: where Ï„ res is a corresponding time lag that accounts for the duration from the day when first symptoms occurred to the day of cure/death. Many estimates of the COVID-19 mortality ratio assume that Ï„ res = 0 [1, 2] and thus underestimate the number of death cases D(t) that result from a certain number of infected individuals. Similar underestimations using CFR d have been reported in previous epidemic outbreaks of SARS [4, 6] and Ebola [20] . A.....
    Document: where Ï„ res is a corresponding time lag that accounts for the duration from the day when first symptoms occurred to the day of cure/death. Many estimates of the COVID-19 mortality ratio assume that Ï„ res = 0 [1, 2] and thus underestimate the number of death cases D(t) that result from a certain number of infected individuals. Similar underestimations using CFR d have been reported in previous epidemic outbreaks of SARS [4, 6] and Ebola [20] . Alternatively, a simple and interpretable population-level mortality ratio is M p (t) = D(t)/(R(t) + D(t)), the death ratio of all resolved cases. To provide a concrete model for D(t) and R(t), and hence M p (t), we will use a variant of the standard infection duration-dependent susceptible-infected-recovered (SIR)-type model described by [21]

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