The Overview, Design Concepts and Details Protocol of ICM Epidemiological Model (PDYN 1.5)

Niedzielewski, Karol; Nowosielski, Jędrzej; Bartczuk, Rafał P.; Dreger, Filip; Górski, Łukasz; Gruziel-Słomka, Magdalena; Kaczorek, Artur; Kisielewski, Jan; Krupa, Bartosz; Moszyński, Antoni; Radwan, M.; Semeniuk, Marcin; Zieliński, Jakub; Rakowski, Franciszek

doi:10.2139/ssrn.4039054

Cited by 4 publications

(6 citation statements)

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“…Our research utilizes pDyn, the detailed epidemiological ABM developed at the Interdisciplinary Center for Mathematical and Computational Modelling at the University of Warsaw, Poland (ICM) [18]. The simulator was optimized for High-Performance Computing environment and runs in the ICM supercomputing facility.…”

Section: The Pdyn Modelmentioning

confidence: 99%

“…Functions developed by adapting the original version of the simulator to the COVID-19 are marked in the őgure by asterisk. The detailed description of the pDyn model following the Overview, the Design concepts, and the Details protocol (ODD, [55]) is publicly available [18].…”

Section: The Pdyn Modelmentioning

confidence: 99%

“…Thus, the probability of each susceptible agent getting infected on the next day of the simulation is a function of the disease-related states of all agents with whom it has been in contact in contexts during the current day [18]. Immediately after the recovery or after taking a vaccine, the agent is immune to the infection variant of the pathogen, but the level of immunity wanes over time.…”

Section: Course Of Diseasementioning

confidence: 99%

“…For the COVID-19 epidemic, we adapted the simulation platform to accommodate the speciőc characteristics and requirements of decision-makers based on the demands of the situation. The pDyn model [18] is capable of simulating and forecasting various SARS-CoV-2 transmission scenarios. It has been officially endorsed by the government, along with the MOCOS model [19] and the Ministry of Health Department of Analysis and Strategy model, as one of the primary tools for providing scientiőc explanations and forecasts of the epidemic processes to policymakers and medical advisory councils on a long-term basis.…”

Section: Introductionmentioning

confidence: 99%

“…During this time, Poland experienced four SARS-CoV-2 epidemic waves. The őrst and second waves (March 4, 2020 -July 12, 2020, and July 13, 2020 -February 14, 2021, respectively) were predominantly driven by the wild-type virus variant, followed by the third Alpha variant wave (February 15, 2021 -July 5, 2021), and the fourth Delta variant wave (July 6, 2021 -December 31, 2021), resulting in a total of 4,106,914 SARS-CoV-2 cases, 96,967 COVID-19 related deaths, and 173,376 total excess deaths reported in Poland [28] (see Figure 1 The forecast, formulated on October 28, 2021, used pDyn [18] to focus on the fourth (Delta) wave of the epidemic in Poland, which marked the end of the process of obtaining herd immunity. This wave was unique in falling spontaneously, without restrictions or limiting contacts.…”

Section: Introductionmentioning

confidence: 99%

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A Deep Dive into the Delta Wave: Forecasting SARS-CoV-2 Epidemic Dynamic in Poland with the pDyn Agent-Based Model

Niedzielewski,

Bartczuk,

Bielczyk

et al. 2023

Preprint

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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.

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Section: The Pdyn Modelmentioning

confidence: 99%

Section: The Pdyn Modelmentioning

confidence: 99%

Section: Course Of Diseasementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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