Socio-demographic determinants of COVID-19 vaccine uptake in Ontario: Exploring differences across the Health Region model

This repository contains files used to create the manuscript, which is available as a preprint here. This paper explores COVID-19 vaccination in the Health Regions of the province of Ontario, Canada.

How to use this repository

$\color{red}{\textnormal{IMPORTANT}}$: The original dataset (the Survey of COVID-19 related Behaviours and Attitudes dataset) is necessary to recreate the results, tables, and figures included in this paper. The Fields Institute has requested that the file is not to be publicly shared and therefore, anyone interested in obtaining this dataset should contact the Fields Institue directly to request access. Once obtained, the raw dataset file (in csv format) should be placed in the data directory in order for the scripts included in this repository to work. With the exception of the raw dataset, this repository currently contains all of the necessary files required to create the paper. Details for each directory are provided below.

Repository organization

The repository contains different directories that work in conjunction to create the final manuscript. The directories are:

code: Contains all R scripts for statistical analyses, map creation, and data cleaning.
data: Contains files (in csv format) with the data used for analysis.
manuscript: Quarto files (*.qmd) used to create the different manuscript sections.

Code

The directory code contains scripts used to create the manuscript. All these files require the libraries that appear in the first chunk in main.qmd in the manuscript directory to work. Therefore if individual scripts need to be run, the required libraries need to be loaded first.

data_reparation.R: script to clean the raw data file and prepare it for analysis.
raking.R: script to correct the data using estimates from the 2016 Census.
regression.R: script that uses the clean data to run two logistic regression models (corrected and uncorrected).
uncorr_model.R: from the model for uncorrected data in regression.R this script creates the figure from the paper.
corr_model.R: from the model for corrected data in regression.R this script creates the figure from the paper.

Data

This directory contains the data files used to create models, obtain geographical information. The files in this directory are:

municipalities_clean.csv: File with the name of the majority of the municipalities in the raw datafile, along with their full title (e.g. Township, Municipality), and the geographical region the municipality belongs to (District, County, etc).
missing_municipalities_updated_May_05_2023.csv: this file has the municipalities that were missing from municipalities_clean.csv and that were in the survey dataset, with the information in each case manually added so all the cities analyzed could be placed within their corresponding Health Region.
geographic_areas.csv: Contains information for all the geographical areas of Ontario, indicating the type of area (County, Regional Municipality, District).
Consolidated_LTC_dataset.csv: Data from this website on Long-Term Care Homes for seniors in Ontario, from this site. This file was used to match each city from the Fields Survey to its corresponding Local Health Integration Network (LHIN).
missing_health_regions_updated_May_05_2023.csv: File created manually for those cities from the Fields Survey dataset that were not present in Long-Term Care Home dataset. The corresponding LHIN in each case was manually added.

Additionally, the sub-directory map_data can be found here, where the map created in the paper (in PDF) is located. The shp files needed to create the map in the manuscript are to be placed in this sub-directory as well (note that these files are not included in the repository because of their size, but the script map_June_01.R in the code directory contains instructions on how to download and process the data to re-create the map.

Manuscript

The different manuscript sections can be found in the manuscript directory, which contains:

01-background.qmd: first part of the manuscript.
02-methods.qmd: describes the methods used in the paper and imports a map of Ontario where the different Health Regions and the observations obtained from each city are presented.
03-results.qmd : contains a descriptive table of the data used in the manuscript, and the results of the statistical analyses.
04-discussion.qmd: discussion.
05-conclusion.Rmd: conclusion to the manuscript.

The PDF versions of the manuscript and the Appendix can be found in this directory as well, with names main.pdf and appendix.pdf, respectively.

This directory also contains sub-directories references (for the references used in the main manuscript), and latex (which contains files required for LaTeX compilation).

Instructions

This work was created using R. Therefore, you need to install the latest version of R. Additionally, it is recommended that and IDE such as RStudio is installed as well. Directions to install R and RStudio can be found here.

After installing R and RStudio, you need to install the {quarto} and {tinytex} (a LaTeX distribution) packages in order to be able to compile the manuscript in PDF. Instructions to install quarto can be found here.
Instructions to install {tinytex} can be found here. Note that you have to install the package and then run the command install_tinytex() to make it work.

All the required libraries to run the code and create the manuscript can be found in the first code chunk in the file main.qmd,which calls all the files to generate the main manuscript). If using RStudio, the first time you open main.qmd you should automatically receive a warning about the missing packages that need to be installed; you can choose to install all the missing packages then.

Although individual code chunks can be run, it is advised to first generate a document by knitting main.qmd. If individual chunks of code want to be examined, it is best to open the .qmd file of interest and see the code structure to the different functions scripts found in the code directory.

This work has an Appendix, which can be re-created by knitting the file appendix.qmd, which can be found in the manuscript directory.

The appendix is a stand-alone document that can be compiled independently from the main manuscript. In this way, the reader chooses the section of interest and can examine and run the code independently.

License

This entire repository is licensed under a CC BY 4.0 License, which allows reuse with attribution. However, certain files are released under the CC0 1.0 public domain dedication. The files indicated below are dual licensed under CC BY 4.0 and CC0 1.0:

01-background.qmd
02-methods.qmd
03-results.qmd
04-discussion.qmd
05-conclusion.qmd

All other files are under CC BY 4.0.

Contact

If you have questions or comments please contact Ariel Mundo (ariel.mundo.ortiz@umontreal.ca)

aimundo/COVID-19_vaccination