Abstract
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 for five or more days with relative errors consistently kept below 5%. The method should improve with more realistic models.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Mathematics in Applied Sciences and Engineering |
| Volume | 2 |
| Issue number | 1 |
| DOIs | |
| State | Published - Mar 29 2021 |
Keywords
- Covid-19
- forecasting
- gradient search
- logistic model
ASJC Scopus subject areas
- Applied Mathematics
- Modeling and Simulation