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Statistics > Methodology

arXiv:2204.12346 (stat)
COVID-19 e-print

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[Submitted on 26 Apr 2022]

Title:On automatic calibration of the SIRD epidemiological model for COVID-19 data in Poland

Authors:Piotr Błaszczyk, Konrad Klimczak, Adam Mahdi, Piotr Oprocha, Paweł Potorski, Paweł Przybyłowicz, Michał Sobieraj
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Abstract:We propose a novel methodology for estimating the epidemiological parameters of a modified SIRD model (acronym of Susceptible, Infected, Recovered and Deceased individuals) and perform a short-term forecast of SARS-CoV-2 virus spread. We mainly focus on forecasting number of deceased. The procedure was tested on reported data for Poland. For some short-time intervals we performed numerical test investigating stability of parameter estimates in the proposed approach. Numerical experiments confirm the effectiveness of short-term forecasts (up to 2 weeks) and stability of the method. To improve their performance (i.e. computation time) GPU architecture was used in computations.
Comments: 17 pages, 7 figures
Subjects: Methodology (stat.ME); Machine Learning (stat.ML)
MSC classes: 92-10, 92D30, 62F10, 65L05
Cite as: arXiv:2204.12346 [stat.ME]
  (or arXiv:2204.12346v1 [stat.ME] for this version)
  https://doi.org/10.48550/arXiv.2204.12346

Submission history

From: Paweł Potorski [view email]
[v1] Tue, 26 Apr 2022 14:35:57 UTC (422 KB)
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