Selected article for: "February end and reproduction number"
Author: Raj Dandekar; George Barbastathis
Title: Quantifying the effect of quarantine control in Covid-19 infectious spread using machine learning
  • Document date: 2020_4_6
    • ID: 222c1jzv_12
    Snippet: The results show a generally strong correlation between strengthening of the quarantine controls, i.e. increasing Q(t) as learnt by the neural network model; actions taken by the regions' respective governments; and decrease of the effective reproduction number R t . For example, in Italy, government restrictions reportedly (Ghiglione et al. 2020) tightened during the week preceding mid March, which is also when our model shows a sharp increase i.....
    Document: The results show a generally strong correlation between strengthening of the quarantine controls, i.e. increasing Q(t) as learnt by the neural network model; actions taken by the regions' respective governments; and decrease of the effective reproduction number R t . For example, in Italy, government restrictions reportedly (Ghiglione et al. 2020) tightened during the week preceding mid March, which is also when our model shows a sharp increase in Q(t) and corresponding decrease in R t (figures 4b, c). For Wuhan and South Korea, similar cusps in government interventions took place earlier, in the weeks leading to and after the end of January (Cyranoski 2020) and February, respectively (Normille 2020) . These cusps were also captured well by our model (Figures 2b, c and 6b , c, respectively). Even for the USA, Q(t) shows a stagnation till 20 March 2020, after which it shows a sharp increase accompanied with a decrease in R t (Figures 8b, c) , which is in alignment with the ramping up of government policies and quarantine interventions post mid March in the worst affected states like New York, New Jersey, California, and Michigan. is the author/funder, who has granted medRxiv a license to display the (which was not peer-reviewed)

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