Bayesian model selection for COVID-19 pandemic state estimation using extended Kalman filters: Case study for Saudi Arabia.
Quantifying the uncertainty in data-driven mechanistic models is fundamental in public health applications. COVID-19 is a complex disease that had a significant impact on global health and economies. Several mathematical models were used to understand the complexity of the transmission dynamics unde...
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| Main Authors: | , , |
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| Format: | Book |
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Public Library of Science (PLoS),
2024-01-01T00:00:00Z.
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Internet
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| Call Number: |
A1234.567 |
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| Copy 1 | Available |