Selected article for: "epidemic size and multiplying factor"
Author: Chakrit Pongkitivanichkul; Daris Samart; Takol Tangphati; Phanit Koomhin; Pimchanok Pimton; Punsiri Dam-O; Apirak Payaka; Phongpichit Channuie
Title: Estimating the size of COVID-19 epidemic outbreak
  • Document date: 2020_3_31
    • ID: auzioqyz_29
    Snippet: The copyright holder for this preprint (which was not peer-reviewed) is . https://doi.org/10.1101/2020.03.28.20044339 doi: medRxiv preprint FIG. 7: The multiplying factor a/a0 as a function of n of 5 European countries. We observed that up till n ≤ 5 the factor a/a0 is not greater than 2 apart from Germany. This factor is useful for the estimation of the size of epidemic. large uncertainty coming from other parameters especially the size of the.....
    Document: The copyright holder for this preprint (which was not peer-reviewed) is . https://doi.org/10.1101/2020.03.28.20044339 doi: medRxiv preprint FIG. 7: The multiplying factor a/a0 as a function of n of 5 European countries. We observed that up till n ≤ 5 the factor a/a0 is not greater than 2 apart from Germany. This factor is useful for the estimation of the size of epidemic. large uncertainty coming from other parameters especially the size of the epidemic, a, in this category we focus on using n = 1 for countries in this phase. We estimate the asymptotic number of cumulative infected cases of countries in the growth-dominated phase. We also provide an estimate of the epidemic size as a function of n. However, in order to obtain a reliable prediction of model, we need more data from these countries in the second category. In conclusion, we provide an alternative way to describe the spread of COVID-19 using the renormalization group method originated from physics' point of view.

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