Author: Jacob Deasy; Emma Rocheteau; Katharina Kohler; Daniel J. Stubbs; Peitro Barbiero; Pietro Liò; Ari Ercole
Title: Forecasting ultra-early intensive care strain from COVID-19 in England Document date: 2020_3_23
ID: i37ygb2z_5
Snippet: We assumed that the daily incidence of COVID-19 can be modelled as an exponential growth (in line with what was observed in Italy [2] ). Therefore, we forecast the likely distributions of new COVID-19 diagnoses over the next 14 days by using an ordinary least squares fit to linearly extrapolate from the logarithm of the cumulative cases. We di↵erentiated the cumulative model to obtain a daily incidence model i.e. we multiply by the exponent ( d.....
Document: We assumed that the daily incidence of COVID-19 can be modelled as an exponential growth (in line with what was observed in Italy [2] ). Therefore, we forecast the likely distributions of new COVID-19 diagnoses over the next 14 days by using an ordinary least squares fit to linearly extrapolate from the logarithm of the cumulative cases. We di↵erentiated the cumulative model to obtain a daily incidence model i.e. we multiply by the exponent ( d dx ⇥ Ae Bx ⇤ = BAe Bx ), which stabilises the exponent fitting (B).
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