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

TL;DR

This paper introduces a new method for estimating parameters of a modified SIRD model to forecast COVID-19 deaths in Poland, demonstrating stable and effective short-term predictions using GPU acceleration.

Contribution

A novel parameter estimation methodology for the SIRD model tailored to COVID-19 data, enabling accurate short-term forecasts and computational efficiency with GPU use.

Findings

Effective short-term forecasts up to 2 weeks

Stable parameter estimates over selected intervals

GPU acceleration improves computation time

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.