An empirical forecasting method for epidemic outbreaks with application to Covid-19

In this paper we describe an empirical forecasting method for epidemic outbreaks. It is an iterative process to find possible parameter values for epidemic models to best fit real data. As a demonstration of principle, we used the logistic model, the simplest model in epidemiology, for an experiment of live forecasting. Short-term forecasts can last to 5 or more days with relative errors consistently kept blow 5%. The method should improve with more realistic models.

Abstract licence: CC BY

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