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

arXiv: https://arxiv.org/abs/2204.12346 · HTML: https://mlsanity.com/paper/2204.12346/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 1 of its 18 references that are in the map.
- First posted on arXiv 26 Apr 2022.

## Builds on (most cited first, 1 of 1)

- [Deep learning via LSTM models for COVID-19 infection forecasting in India](https://mlsanity.com/paper/2101.11881/) (2021)

## Abstract (arXiv)

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.