Author: Tom Britton
Title: Basic estimation-prediction techniques for Covid-19, and a prediction for Stockholm Document date: 2020_4_17
ID: 0fmeu4h4_3
Snippet: As input to our prediction model we use the observed doubling time d during the initial (random) phase of the epidemic and the basic reproduction number R 0 . Estimation of d is straightforward (e.g. [1] ) and many estimates of R 0 for covid-19 can be found in the literature, most of them lying in the range 2.2-2.8 (e.g. [9] , [8] ). We start by describing the different steps in the methodology, including also how to time-calibrate the model to c.....
Document: As input to our prediction model we use the observed doubling time d during the initial (random) phase of the epidemic and the basic reproduction number R 0 . Estimation of d is straightforward (e.g. [1] ) and many estimates of R 0 for covid-19 can be found in the literature, most of them lying in the range 2.2-2.8 (e.g. [9] , [8] ). We start by describing the different steps in the methodology, including also how to time-calibrate the model to calendar time, and the apply our method by predicting the Covid-19 outbreak in the Stockholm region.
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