Computational forecasting using Swedish data in the vaccination phase of the COVID-19 pandemic: a systematic literature review deliberating modelling relevance for public health and healthcare
- DOI
- 10.1186/s12913-026-15076-y
- Published
- 2026-07-10
- Container
- BMC Health Services Research
- Publisher
- Springer Science and Business Media LLC
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1186/s12913-026-15076-y,
title = {Computational forecasting using Swedish data in the vaccination phase of the COVID-19 pandemic: a systematic literature review deliberating modelling relevance for public health and healthcare},
author = {Anna Saxne Jöud and Henrik Thorén and Armin Spreco and Torbjörn Lundh and Toomas Timpka and Philip Gerlee},
year = {2026},
journal = {BMC Health Services Research},
doi = {10.1186/s12913-026-15076-y},
url = {https://doi.org/10.1186/s12913-026-15076-y}
}RIS
TY - JOUR TI - Computational forecasting using Swedish data in the vaccination phase of the COVID-19 pandemic: a systematic literature review deliberating modelling relevance for public health and healthcare AU - Anna Saxne Jöud AU - Henrik Thorén AU - Armin Spreco AU - Torbjörn Lundh AU - Toomas Timpka AU - Philip Gerlee PY - 2026 JO - BMC Health Services Research DO - 10.1186/s12913-026-15076-y UR - https://doi.org/10.1186/s12913-026-15076-y ER -
APA
Jöud, A. S., Thorén, H., Spreco, A., Lundh, T., Timpka, T., & Gerlee, P. (2026). Computational forecasting using Swedish data in the vaccination phase of the COVID-19 pandemic: a systematic literature review deliberating modelling relevance for public health and healthcare. BMC Health Services Research. https://doi.org/10.1186/s12913-026-15076-y
Source records
- crossref · retrieved 2026-09-25T17:31:48.959Z