Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic
Overview & Synopsis
We propose a forecasting method for predicting epidemiological health series on a two-week horizon at regional and interregional resolution. The approach is based on the model orderreduction of parametric compartmental models and is designed to accommodate small amounts ofsanitary data. The efficiency of the method is shown in the case of the prediction of the number ofinfected people and people removed from the collected data, either due to death or recovery, duringthe two pandemic waves of COVID-19 in France, which took place approximately between Februaryand November 2020. Numerical results illustrate the promising potential of the approach
Indexed from repository: HAL Open Science
(
hal.science)
Keyboard Shortcuts:
← / → for pages • + / - for zoom • 0 to fit width
Powered by Mozilla PDF.js v3.11
Document Information
| Document Title | Epidemiological Forecasting with Model Reduction of Compartmental Models. Application to the COVID-19 Pandemic |
|---|---|
| Author / Organization | Athmane Bakhta, Thomas Boiveau, Yvon Maday, Olga Mula |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2020 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-194705 |
| Original Source Link | Visit Source Page on hal.science » |