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Agent-based modeling of COVID-19 outbreaks for New York state and UK: Parameter identification algorithm
Olga Krivorotko1,2, Mariia Sosnovskaia2, Ivan Vashchenko2
1Institute of Computational Mathematics and Mathematical Geophysics Siberian Branch of the Russian Academy of Sciences, 6 Prospect Akademika Lavrentieva Street, Novosibirsk, 630090, Russia.
Infectious Disease Modelling
|December 6, 2021
Summary
This study used an agent-based model (Covasim) to simulate COVID-19 spread. Maintaining current measures in New York State may keep cases stable, while the UK could see a reduction.
Area of Science:
- Epidemiology
- Computational modeling
- Public health
Background:
- COVID-19 epidemic spread varies significantly based on regional factors and interventions.
- Accurate epidemiological modeling is crucial for predicting disease trajectories and informing policy.
- Agent-based models (ABMs) offer a powerful tool for simulating complex disease dynamics.
Purpose of the Study:
- To evaluate COVID-19 epidemic spread scenarios in New York State and the UK using the Covasim ABM.
- To calibrate and validate the Covasim model using regional epidemiological data and machine learning.
- To forecast the impact of sustained containment measures on future COVID-19 cases.
Main Methods:
- Utilized the Covasim agent-based model for COVID-19 simulation.
- Analyzed regional epidemiological data (testing, diagnoses, hospitalizations, deaths) for seasonality and stationarity.
- Employed machine learning for parameter extrapolation and the Optuna optimizer for parameter estimation, validating against 2020 data.
Main Results:
- Modeled COVID-19 spread in New York State and the UK.
- Projected that maintaining current testing and containment levels would lead to stable case numbers in New York State through March 2021.
- Forecasted a reduction in COVID-19 cases in the UK under the same conditions.
Conclusions:
- The Covasim model effectively simulates COVID-19 spread and can forecast future trends.
- Sustained public health interventions are projected to have differing impacts on epidemic trajectories in New York State and the UK.
- Model predictions highlight the importance of ongoing monitoring and adaptive strategies for epidemic control.
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