Open AccessAn empirical forecasting method for epidemic outbreaks with application to Covid-19
Author(s) -
Bo Deng
Publication year - 2020
Publication title -
mathematics in applied sciences and engineering
Language(s) - English
Resource type - Journals
ISSN - 2563-1926
DOI - 10.5206/mase/11101
Subject(s) - covid-19 , outbreak , econometrics , epidemic model , computer science , process (computing) , statistics , mathematics , virology , demography , population , infectious disease (medical specialty) , medicine , sociology , operating system , disease , pathology
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.