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ee-vax's Introduction

ee-vax

This repository contains the code for the analysis presented in The COVID-19 vaccination campaign in Switzerland and its impact on disease spread

Ensuring you have the raw data

Please first run the script download-data-sets.R such that the correct data is downloaded to your machine

Conducting the pre-processing of data

Provided you do not wish to use ProjectTemplate::load.project(), you should first load the packages listed in config/global.dcf

library(knitr)
library(surveillance)
library(hhh4contacts)
library(ggplot2)
library(patchwork)
library(viridis)
library(ggthemes)
library(kableExtra)
library(openxlsx)
library(reshape2)
library(maptools)
library(sp)
library(spdep)
library(sf)
library(tmap)
library(tmaptools)
library(wrapr)
library(zoo)
library(ggforce)
library(hhh4addon)
library(MASS)

and then execute in order the following scripts before running the code

source("lib/globals.R")
source("lib/function-AIC-correction.R")
source("lib/function-change-vaccine-distribution.R")
source("lib/function-date-to-text.R")
source("lib/function-format-coef-for-table.R")
source("lib/function-Hannah-Quinn.R")
source("lib/function-include-uncertainty-predictions.R")
source("lib/function-iso-fix.R")
source("lib/function-normalise-indicator.R")
source("lib/function-outcome-counts.R")
source("lib/function-plot-matrices.R")
source("lib/function-plot-models.R")
source("lib/function-plot-predictions.R")
source("lib/function-sine-cosine-wave-data.R")
source("lib/function-skip-plot-labels.R")
source("lib/function-surveillance-time-series.R")
source("lib/function-table-models.R")
source("lib/function-waning.R")

source("munge/01_manual-cantons.R")
source("munge/02_manual-adjacency.R")
source("munge/03_load-data-map.R")
source("munge/04_load-data-mobility.R")
source("munge/05_load-data-contact-and-policy.R")
source("munge/06_load-data-vaccines-and-population.R")
source("munge/07_load-data-cases.R")
source("munge/08_create-coverage-covariate.R")
source("munge/09_models-setup.R")
source("munge/10_scenario-analysis-alternative-covariate.R")
source("munge/11_sensitivity-vaccination-coverage.R")

Data we have created

Manually created data sets are contained in the folder output and described in the folder metadata

Conducting the analysis

Following this, you should be able to execute the code in folder reports/code, see above if you do not wish to use load.project() and ensure you have run the pre-processing scripts first

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