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Cellular Automata in Covid-19 prediction
Piotr Podolski1, Hung Son Nguyen1
1Faculty of Mathematics, Informatics and Mechanics University of Warsaw Banacha 2, 02-097 Warszawa, Poland.
Procedia Computer Science
|October 11, 2021
Summary
A new model simulates COVID-19 spread in Poland, considering preventive measures and regional factors. This tool aids in pandemic management by predicting future infection dynamics.
Area of Science:
- Epidemiology
- Computational modeling
- Public health
Background:
- The emergence of coronavirus disease 2019 (COVID-19) in late 2019 led to a global pandemic.
- Varying national strategies highlight the need for effective pandemic management tools.
- Poland's specific context requires tailored approaches to combat the virus.
Purpose of the Study:
- To develop and present a predictive model for COVID-19 dynamics in Poland.
- To simulate future infection scenarios incorporating diverse preventive strategies.
- To account for spatial dependencies and regional characteristics within Poland.
Main Methods:
- Utilized a two-dimensional cellular automata framework for simulation.
- Incorporated spatial dependencies between different regions.
- Modeled variations in population and region sizes.
Main Results:
- The model simulates future COVID-19 infection trajectories.
- It allows for the evaluation of various preventive measures' impact.
- Spatial and demographic factors are integrated into the predictions.
Conclusions:
- The developed model offers a valuable tool for predicting COVID-19 spread in Poland.
- It supports informed decision-making for public health interventions.
- Understanding regional dynamics is crucial for effective pandemic control.
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