Selected article for: "epidemiological model and machine learning"
Author: Brydon Eastman; Cameron Meaney; Michelle Przedborski; Mohammad Kohandel
Title: Mathematical modeling of COVID-19 containment strategies with considerations for limited medical resources
  • Document date: 2020_4_22
    • ID: 51g3vhcx_40
    Snippet: In this work, an epidemiological mathematical model, the Distancing-SEIRD model, is developed for use in predicting the effectiveness of various social distancing strategies in Canada. Disease parameters are fitted to the model using machine learning techniques for the specific cases of Ontario and Quebec and used to project the number of deaths and ventilator demand for proposed social distancing strategies. Social distancing strategies are defi.....
    Document: In this work, an epidemiological mathematical model, the Distancing-SEIRD model, is developed for use in predicting the effectiveness of various social distancing strategies in Canada. Disease parameters are fitted to the model using machine learning techniques for the specific cases of Ontario and Quebec and used to project the number of deaths and ventilator demand for proposed social distancing strategies. Social distancing strategies are defined by the proportion of the population social distancing and the length of time over which social distancing occurs. Allowing for a proportion of the population to social distance, rather than all-or-nothing, allows for the more realistic case of imperfect social distancing to be modelled.

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