Corpus ID: 218673428

Phenomenological dynamics of COVID-19 pandemic: meta-analysis for adjustment parameters.

@article{Hojman2020PhenomenologicalDO,
  title={Phenomenological dynamics of COVID-19 pandemic: meta-analysis for adjustment parameters.},
  author={Sergio A. Hojman and Felipe A. Asenjo},
  journal={arXiv: Physics and Society},
  year={2020}
}
  • Sergio A. Hojman, Felipe A. Asenjo
  • Published 2020
  • Physics, Biology, Mathematics
  • arXiv: Physics and Society
  • We present a phenomenological way of dealing with the COVID-19 data provided by government health agencies of eight different countries. Instead of using the (exact or approximate) solutions to the SIR (or other) model(s) and trying to adjust the time-independent parameters included in those models, we introduce dynamical parameters whose time-dependence may be phenomenologically obtained by adequately extrapolating a chosen subset of the daily provided data. This phenomenological approach… CONTINUE READING

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    References

    Publications referenced by this paper.
    SHOWING 1-10 OF 20 REFERENCES

    Applied Math

    • T. Harko, F.S.N. Lobo, M. K. Mak
    • and Comp. 236, 184
    • 2014
    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    Chia-Chun Tsai

    • S. Towers, K. Vogt Geisse
    • Q. Han, and Z. Feng, Math. Biosc. and Eng. 9, 413
    • 2012
    VIEW 9 EXCERPTS
    HIGHLY INFLUENTIAL

    Math

    • M A. Abdelkader
    • Biosc., 29, 293
    • 1974
    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    SIAM Review 42

    • H. W. Hethcote
    • 599
    • 2000
    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    The Mathematical Theory of Infectious Diseases and Its Applications

    VIEW 10 EXCERPTS
    HIGHLY INFLUENTIAL

    Proc

    • W. O. Kermack, A. G. McKendrick
    • Roy. Soc. A 115, 700
    • 1927
    VIEW 4 EXCERPTS
    HIGHLY INFLUENTIAL

    Biol

    • A. Mummert, O. M. Otunuga, J. Math
    • 79, 705
    • 2019

    Complete Our World in Data COVID-19 dataset

    • M. Roser, H. Ritchie, E. Ortiz-Ospina, J. Hasell
    • Retrieved from: OurWorldInData.org [Online Resource]
    • 2019