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Abstract
Since the novel coronavirus (COVID-19) outbreak in China, and due to the open accessibility of COVID-19 data, several researchers and modellers revisited the classical epidemiological models to evaluate their practical applicability. While mathematical compartmental models can predict various contagious viruses’ dynamics, their efficiency depends on the model parameters. Recently, several parameter estimation methods have been proposed for different models. In this study, we evaluated the Ensemble Kalman filter’s performance (EnKF) in the estimation of time-varying model parameters with synthetic data and the real COVID-19 data of Hubei province, China. Contrary to the previous works, in the current study, the effect of damping factors on an augmented EnKF is studied. An augmented EnKF algorithm is provided, and we present how the filter performs in estimating models using uncertain observational (reported) data. Results obtained confirm that the augumented-EnKF approach can provide reliable model parameter estimates. Additionally, there was a good fit of profiles between model simulation and the reported COVID-19 data confirming the possibility of using the augmented-EnKF approach for reliable model parameter estimation.
Original language | English |
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Article number | e0256227 |
Pages (from-to) | 1-25 |
Number of pages | 25 |
Journal | PLoS One |
Volume | 16 |
Issue number | 8 |
DOIs | |
Publication status | Published - 19 Aug 2021 |
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Dive into the research topics of 'An application of the ensemble Kalman filter in epidemiological modelling'. Together they form a unique fingerprint.Activities
- 5 Peer review responsibility, including review panel or committee
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PLoS One (Journal)
Li, J. (Reviewer)
01 Mar 2023 → 20 Mar 2023Activity: Publication peer-review and editorial work › Peer review responsibility, including review panel or committee
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PLoS One (Journal)
Li, J. (Reviewer)
01 May 2023 → 20 May 2023Activity: Publication peer-review and editorial work › Peer review responsibility, including review panel or committee
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PLoS One (Journal)
Li, J. (Reviewer)
01 Feb 2023 → 28 Feb 2023Activity: Publication peer-review and editorial work › Peer review responsibility, including review panel or committee