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

Latest findings in modelling the COVID-19 epidemic in Scotland, both in terms of the spread of the disease through the population (epidemiological modelling) and of the demands it will place on the system, for example in terms of health care requirement

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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)

Contact

Email: modellingcoronavirus@gov.scot

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