| Partner: J. Zieliński |
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Ostatnie publikacje
| 1. | Niedzielewski K.♦, Bartczuk R.♦, Bielczyk N.♦, Bogucki D. J., Dreger F.♦, Dudziuk G.♦, Górski Ł.♦, Gruziel-Słomka M.♦, Haman J.♦, Kaczorek A.♦, Kisielewski J.♦, Krupa B.♦, Moszyński A.♦, Nowosielski J.♦, Radwan M.♦, Semeniuk M.♦, Tymoszuk U.♦, Zieliński J.♦, Rakowski F.♦, Forecasting SARS-CoV-2 epidemic dynamic in Poland with the pDyn agent-based model, Epidemics, ISSN: 1755-4365, DOI: 10.1016/j.epidem.2024.100801, Vol.49, No.100801, pp.1-31, 2024 Streszczenie: We employ pDyn (derived from ‘‘pandemics dynamics’’), an agent-based epidemiological model, to forecast the fourth wave of the SARS-CoV-2 epidemic, primarily driven by the Delta variant, in Polish society. The model captures spatiotemporal dynamics of the epidemic spread, predicting disease-related states based on pathogen properties and behavioral factors. We assess pDyn’s validity, encompassing pathogen variant succession, immunization level, and the proportion of vaccinated among confirmed cases. We evaluate its predictive capacity for pandemic dynamics, including wave peak timing, magnitude, and duration for confirmed cases, hospitalizations, ICU admissions, and deaths, nationally and regionally in Poland. Validation involves comparing pDyn’s estimates with real-world data (excluding data used for calibration) to evaluate whether pDyn accurately reproduced the epidemic dynamics up to the simulation time. To assess the accuracy of pDyn’s predictions, we compared simulation results with real-world data acquired after the simulation date. The findings affirm pDyn’s accuracy in forecasting and enhancing our understanding of epidemic mechanisms. Słowa kluczowe: Epidemic dynamics , Epidemiology, Agent-based model, COVID-19 Afiliacje autorów:
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Prace konferencyjne
| 1. | Opara K.♦, Zieliński J.♦, Brzeziński K.♦, Kaczmarek-Majer K.♦, Bukowicki M., Evaluation of pavement roughness through vehicle vibration monitoring, 26th World Road Congress, 2019-10-06/10-10, Abu Dhabi (AE), pp.1-15, 2019 Streszczenie: Driving on uneven roads causes vibrations of the vehicle. Modern smartphones are equipped with accelerometers and gyroscopes which allow for inexpensive acquisition of information about the shaking level. This study reports on field tests of a system, which measures vibrations of a driving vehicle using four smartphones as sensors. The collected data undergo a series of processing steps, namely synchronization, virtual reorientation, temporal and spectral filtering, and assignment of road localization. We use quarter-car and half-car suspension models to retrieve the longitudinal road profile and to compute unevenness indicators. The accuracy of the system was computed by comparison with traditional laser profilometer on an 18.6 km long test section using eight rides with different speeds. It averages to 71% and exceeds 80% for the best calibrated cases. Additionally, we report on the feedback obtained during tests of the system in a district road administration in Poland. Afiliacje autorów:
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