Computation of COVID-19 epidemiological data in Hungary using dynamic model inversion

Autor:	Csutak, Balazs, Polcz, Peter, Szederkenyi, Gabor
Rok vydání:	2021
Předmět:	Quantitative Biology - Populations and Evolution Mathematics - Dynamical Systems Quantitative Biology - Quantitative Methods
Druh dokumentu:	Working Paper
Popis:	In this paper, we estimate epidemiological data of the COVID-19 pandemic in Hungary using only the daily number of hospitalized patients, and applying well-known techniques from systems and control theory. We use a previously published and validated compartmental model for the description of epidemic spread. Exploiting the fact that an important subsystem of the model is linear, first we compute the number of latent infected persons in time. Then an estimate can be given for the number of people in other compartments. From these data, it is possible to track the time dependent reproduction numbers via a recursive least squares estimate. The credibility of the obtained results is discussed using available data from the literature. Comment: 11 pages, 12 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2105.04423 Zobrazit plný text záznamu View this record from Arxiv