Dynamic calibration with approximate Bayesian computation for a microsimulation of disease spread
Abstract The global COVID-19 pandemic brought considerable public and policy attention to the field of infectious disease modelling. A major hurdle that modellers must overcome, particularly when models are used to develop policy, is quantifying the uncertainty in a model’s predictions. By including...
Main Authors: | Molly Asher, Nik Lomax, Karyn Morrissey, Fiona Spooner, Nick Malleson |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-05-01
|
Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-35580-z |
Similar Items
-
Calibrated approximate Bayesian inference
by: Xing, H, et al.
Published: (2019) -
Microsimulation of organised car sharing: description of the models and calibration/
by: 241318 Bonsall, Peter W., et al.
Published: (1980) -
Possibility of Microsimulation Models Calibration – Case Study in the City of Split
by: Dražen Cvitanić, et al.
Published: (2012-05-01) -
Characterization and Valuation of the Uncertainty of Calibrated Parameters in Microsimulation Decision Models
by: Fernando Alarid-Escudero, et al.
Published: (2022-05-01) -
The spread of agriculture in Iberia through Approximate Bayesian Computation and Neolithic projectile tools.
by: Alfredo Cortell-Nicolau, et al.
Published: (2021-01-01)