prisons-vacc-strategies

Analysis of the impact of seven different vaccination scenarios on cases, QALY loss and deaths from COVID-19 in a category B local prison in England and Wales.

This involved adapting CovidM, a transmission-dynamic model for SARS-CoV-2 transmission developed by Davies et al., which has previously been used to evaluate the impact of vaccination in the UK at the population level.

Quick start guide

1. Install all required packages using R/packages. The version of CovidM used and instructions for installation can be found in the covidm_for_fitting folder.

2. Set file paths within set-up-upgrading script. cm_path defines where covidm is stored e.g.

cm_path = "C:/Users/CiaraMcCarthy/covidm-twodose/covidm_for_fitting/"

pris_path defines where the contents of the prisons-vacc-strategies Github directory are stored e.g.

pris_path <- "~/prisons-vacc-strategies""

save_path defines where the generated figures will be saved.

3. Run scripts/set-up-upgrading.R. This loads all dependencies, including covidm. It sources the following other scripts in the repository:

   • R/functions_may21.R - required functions
   • R/sensitivity.R - assigns values for vaccine- and prison-related parameters; scales susceptibility to achieve desired R0.

4. Code for all plots is included in the scripts folder. These scripts sources the following other scripts in the repository:

   • scripts/vacc-scenarios.R - runs model for each of the seven vaccination scenarios
   • scripts/psa_define.R - defines values for all parameters varied in probabilistic sensitivity analysis, based on values generated from Latin hypercube sampling
   • scripts/vacc_short.R - shortened version of scripts/vacc-scenarios.R script
   • scripts/sensitivity.R - as above

The sources for the QALY values used in data/qalycalc-prisoners.xlsx and data/qalycalc-staff.xlsx are described in McCarthy et al. [will include link to manuscript here]

Citation

McCarthy et al., Impact of COVID-19 vaccination in prisons in England and Wales: a metapopulation model [will include link to manuscript here]

Citing CovidM:

Davies NG, Kucharski AJ, Eggo RM, Gimma A, Edmunds WJ, Jombart T, et al. Effects of non-pharmaceutical interventions on COVID-19 cases, deaths, and demand for hospital services in the UK: a modelling study. Lancet Public Health 2020.

Sandmann FG, Davies NG, Vassall A, Edmunds WJ, Jit M, Sun FY, et al. The potential health and economic value of SARS-CoV-2 vaccination alongside physical distancing in the UK: a transmission model-based future scenario analysis and economic evaluation. Lancet Infect Dis. 2021.