Forecasting SARS-CoV-2 Epidemic Dynamic in Poland with the Pdyn Agent-Based Model

Abstract In this work, we describe and forecast the fourth wave of the SARS-CoV-2 epidemic, driven by the Delta variant, using pDyn — a detailed epidemiological agent-based model. It is designed to explain the spatiotemporal dynamics of the SARS-CoV-2 spread across Polish society, predicting the number and locations of disease-related states for agents living in the virtual society in response to varying properties of the pathogen and the social structure and behavior. We evaluate the validity of the dynamics generated by the model, including the succession of pathogen variants, immunization dynamics, and the ratio of vaccinated individuals among confirmed cases. Additionally, we assess the model’s predictive power in estimating pandemic dynamics (peak timing, peak value, and wave length) of disease-related states (number of confirmed cases, hospitalizations, ICU hospitalizations, and deaths) both at the national level and in the highest administrative units in Poland (voivodships). When testing the model’s validity, we compared real-world data (excluding data used for calibration) to our model estimates to evaluate whether pDyn accurately reproduced the epidemic dynamics up to the simulation time (October 28, 2021). To assess the accuracy of pDyn’s predictions, we retrospectively compared simulation results with real-world data acquired after the simulation date, evaluating pDyn as a tool for predicting future epidemic spread. Our results indicate that pDyn accurately predicts and can help us better understand the mechanisms underlying the SARS-CoV-2 dynamics.