Efficient Uncertainty Quantification and Variance-Based Sensitivity Analysis in Epidemic Modelling Using Polynomial Chaos

DOI10.1051/mmnp/2022014zbMath1491.92112OpenAlexW4224237235MaRDI QIDQ5079575

Allan P. Engsig-Karup, Bjørn Christian Skov Jensen, Kim Knudsen

Publication date: 27 May 2022

Published in: Mathematical Modelling of Natural Phenomena (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1051/mmnp/2022014

zbMATH Keywords

epidemic modellinguncertainty quantificationSobol indicesCovid-19global statistics

Mathematics Subject Classification ID

Epidemiology (92D30)

Uses Software

• NumPy

Cites Work

• The Mathematics of Infectious Diseases
• Mathematical Structures of Epidemic Systems
• Polynomial Chaos in Stochastic Finite Elements
• The Wiener--Askey Polynomial Chaos for Stochastic Differential Equations
• Spectral Methods
• Monte Carlo strategies in scientific computing
• The elements of statistical learning. Data mining, inference, and prediction
• Unnamed Item

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