A polynomial regression model for excess mortality in Mexico 2020-2022 due to the COVID-19 pandemic

Authors: Andreu Comas-García & Arturo Erdely

Preprint: arXiv

Instructions for reproducibility

1. Download and install the Julia programming language.
2. Download and unzip the data from the following Google Drive link in a working directory of your election.
3. Open the Julia terminal and change to the working directory where you unzipped the files. You may do this by defining a string variable path with the path to the files directory and then execute in the terminal cd(path). For example, in the operating system Windows it may look something like:

   path = "D:/MyFiles/rawdata2022mx"
   cd(path)
   readdir()

4. Download the code files clicking in the green button <> Code of this GitHub repository and DownloadZIP. Unzip the downloaded file and move the following files into the same working directory as the downloaded data in the previous step: 0auxfunctions.jl, 1packages.jl, 2deaths.jl, 3population.jl, 4figures.jl, 5tables.jl, and 6other.jl
5. Install the required packages by executing the following command in the Julia terminal. This may take a while:

   include("1packages.jl")

6. Process deaths data. This will take several hours (4 approx) and will generate several new .csv data files:

   include("2deaths.jl")

7. Process population data. This is quite fast and will generate several new .csv data files:

   include("3population.jl")

8. Create 4 figures as .png image files:

   include("4figures.jl")

   • Figure1.png: % of non-illnes deaths & observed illness-related deaths 1998-2019
   • Figure2.png: illness-related excess mortality 2020 | 2021 | 2022
   • Figure3.png: % illness-related excess of mortality 2020-2022 males vs females
   • Figure4.png: illness-related excess mortality 2020-2022 by sex and age groups
9. Create 6 tables in .csv file format:

   include("5tables.jl")

   • Table1.csv: Excess mortality in Mexico 2020
   • Table2.csv: Excess mortality in Mexico 2021
   • Table3.csv: Excess mortality in Mexico 2022
   • Table4.csv: Excess mortality in Mexico 2020-2022
   • Table5.csv: Excess mortality in Mexico 2020-2022 (males)
   • Table6.csv: Excess mortality in Mexico 2020-2022 (females)
10. Generate supplementary figures and calculations:

    include("6other.jl")

    • FigureExtra1.png: illness-related deaths evolution of fitted parameters
    • FigureExtra2.png: adjusted R-squared and Anderson-Darling test for normality of residuals
    • FigureExtra3.png: some examples of the fitted model