Selected article for: "insight provide and mathematical model"

Author: Gao, X.; Dong, Q.
Title: A Logistic Model for Age-Specific COVID-19 Case-Fatality Rates
  • Cord-id: iy5f598w
  • Document date: 2020_6_13
  • ID: iy5f598w
    Snippet: Objectives To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Materials and Method Based on two large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CFR and age. Results and Discussion We inferred that CFR increased faster in Italy than in China, as well as in females over males. In addition, while CFR increased with age, the rate of growth eventually slowed down, with a pre
    Document: Objectives To develop a mathematical model to characterize age-specific case-fatality rates (CFR) of COVID-19. Materials and Method Based on two large-scale Chinese and Italian CFR data, a logistic model was derived to provide quantitative insight on the dynamics between CFR and age. Results and Discussion We inferred that CFR increased faster in Italy than in China, as well as in females over males. In addition, while CFR increased with age, the rate of growth eventually slowed down, with a predicted theoretical upper limit for males (32%), females (21%), and the general population (23%). Conclusion Our logistic model provided quantitative insight on the dynamics of CFR.

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