Coronavirus (COVID-19): modelling the epidemic (issue no. 37)

Footnotes

1. Based on S gene dropout, which is a proxy for the new variant.

2. The hazard ratio, adjusted for demographic and clinical characteristics.

3. The Early Pandemic Evaluation and Enhanced Surveillance of COVID-19 (EAVE) 2 Study Group.

4. https://beta.isdscotland.org/find-publications-and-data/population-health/covid-19/covid-19-statistical-report/

5. Coronavirus (COVID-19): modelling the epidemic - gov.scot (www.gov.scot)

6. Better assumes a vaccine effect based on current roll-out plans. Worse is without this vaccine effect. The real-world effectiveness of vaccines, particularly against infection, is not yet known.

7. Actual data does not include full numbers of CPAP or people staying longer than 28 days.

8. A four week projection is provided here.

9. Optimising the COVID-19 vaccination programme for maximum short-term impact - GOV.UK (www.gov.uk)

10. Based at Edinburgh University, Strathclyde University Aberdeen University and Public Health Scotland.

11. Investigation of novel SARS-COV-2

12. Based on S gene dropout, which is a proxy for the new variant.

13. https://www.medrxiv.org/content/10.1101/2020.11.24.20236661v1

14. 10.5281/zenodo.4246047

15. COVID viral RNA

16. Flaxman, S., Mishra, S., Gandy, A. et al. Estimating the effects of non-pharmaceutical interventions on COVID-19 in Europe. Nature 584, 257–261 (2020). https://doi.org/10.1038/s41586-020-2405-7

17. https://arxiv.org/pdf/2004.11342.pdf

18. Modelling of Epidemics using Hierarchical Bayesian Models • epidemia (imperialcollegelondon.github.io)