Using a Dynamic Causal Model to validate previous predictions and offer a 12-month forecast of the long-term effects of the COVID-19 epidemic in the UK
- DOI
- 10.3389/fpubh.2022.1108886
- Published
- 2023-01-06
- Container
- Frontiers in Public Health
- Publisher
- Frontiers Media SA
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.3389/fpubh.2022.1108886,
title = {Using a Dynamic Causal Model to validate previous predictions and offer a 12-month forecast of the long-term effects of the COVID-19 epidemic in the UK},
author = {Cam Bowie and Karl Friston},
year = {2023},
journal = {Frontiers in Public Health},
doi = {10.3389/fpubh.2022.1108886},
url = {https://doi.org/10.3389/fpubh.2022.1108886}
}RIS
TY - JOUR TI - Using a Dynamic Causal Model to validate previous predictions and offer a 12-month forecast of the long-term effects of the COVID-19 epidemic in the UK AU - Cam Bowie AU - Karl Friston PY - 2023 JO - Frontiers in Public Health DO - 10.3389/fpubh.2022.1108886 UR - https://doi.org/10.3389/fpubh.2022.1108886 ER -
APA
Bowie, C., & Friston, K. (2023). Using a Dynamic Causal Model to validate previous predictions and offer a 12-month forecast of the long-term effects of the COVID-19 epidemic in the UK. Frontiers in Public Health. https://doi.org/10.3389/fpubh.2022.1108886
Source records
- crossref · retrieved 2026-09-25T08:38:13.558Z