sarscov2-roadmap-england

This is an orderly repository which contains the analysis to our preprint

Non-pharmaceutical interventions, vaccination and the Delta variant: epidemiological insights from modelling England's COVID-19 roadmap out of lockdown

Running

A sequence of tasks needs to be run with a set of parameters to generate the final results. This is sketched out in the run.R script, though this is provided only as a form of documentation. In practice these were run over several days on a HPC.

• regions: c("north_west", "north_east_and_yorkshire", "midlands", "east_of_england", "london", "south_west", "south_east")
• assumptions: c("central", "optimistic", "pessimistic")

1. Run the vaccine_fits_regional task with each region and assumption level (21 fits, each about 5 hours)
2. Run the vaccine_fits_combined task with each assumption level (3, collecting all regions)
3. Run the vaccine_restart_fits_regional task with each region and assumption level (21 fits, each about 10 hours)
4. Run the vaccine_restart_fits_combined task with each assumption level (3, collecting all regions)
5. Run the vaccine_simulation task with each assuption level, with a restart_date of march, june and july with sensitivity=FALSE, and also with sensitivity=TRUE for restart_date="july" . The full runs use n_par = 200 but this can be reduced at the cost of more noise. Because of the large number of scenarios used, these were run across a set of 32 core nodes (up to 10 at a time).
6. Run the vaccine_simulation_plots task
7. Run the vaccine_simulation_plots_sens task

Running even the short run, as in run.R will take ~7 hours of CPU time, less in wall time if you have more cores available.

Requirements

The core requirement is our sircovid package and its dependencies. Because that package is in constant development you will probably want to pin your versions of the software to the versions we used for preparation:

remotes::install_github(c(
  "mrc-ide/dust@v0.9.11",
  "mrc-ide/mcstate@0.6.6",
  "mrc-ide/sircovid@v0.11.30",
  "mrc-ide/spimalot@v0.3.0"))

However, you can always install the versions that we are using with

drat:::add("ncov-ic")
install.packages(c("sircovid", "spimalot"))

You will also need a recent orderly which can be installed with

drat:::add("vimc")
install.packages("orderly")

To install all required packages, you can use remotes:

remotes::install_deps()

License

MIT © Imperial College of Science, Technology and Medicine