Projecting the Long-term Effects of the COVID-19 Pandemic on U.S. Population Structure

Purpose of this Repository

The repository CovPop was created to enable readers to replicate the findings reported in:

A.M. Tilstra, A. Polizzi, S. Wagner, E.T. Akimova. Projecting the long-term effects of the COVID-19 pandemic on U.S. population structure. Nature Communications 15, 2409 (2024). https://doi.org/10.1038/s41467-024-46582-4,

hereafter, our manuscript.

Repository Structure

The repository CovPop contains two main folders, Journal and SocArXiv.

1. Journal

The main folder Journal contains all data and R scripts necessary to replicate the information reported in the journal version of our manuscript. This includes the information reported in the Supplementary Information and the point-by-point responses to the peer reviewers' comments. The data and analysis files are respectively stored in the sub-folders data and scripts.

For our main analysis, we use data from the United Nations World Population Prospects (UNWPP), version 2022, provided by the United Nations Department of Economic and Social Affairs (Ref. 1).

For our supplementary analysis, we also use data from the Human Mortality Database, version 03 April 2023 (Ref. 2), and the Human Fertility Database, deposited on 28 March 2023 (Ref. 3), as well as data published in three National Vital Statistics Reports (Ref. 4–6).

The UNWPP data used for our analysis are distributed under a Creative Commons license CC BY 3.0 IGO. The HMD and HFD data used for our analysis are distributed under a Creative Commons Attribution 4.0 International License. Please note the version or deposited dates of the data used for our analysis, as indicated above.

a. data

Data taken from UNWPP, HMD, and HFD are stored as .zip files in the sub-folder data. These .zip files do not need to be unzipped before running our analysis files, as the code unzips these files automatically. Data from the three National Vital Statistics Reports are hard coded in our analysis files. The sub-folder data also stores data files created during analysis.

b. scripts

The sub-folder scripts contains the R scripts necessary to replicate all findings reported in our main manuscript, Supplementary Information, and/or the point-by-point responses to the peer reviewers' comments:

• 99-functions.R Creates custom functions used to calculate survivorship ratios, conduct stochastic or deterministic population projections, and build some of our plots.

• 01-preparation.R Loads UNWPP data, prepares them for further analysis, and saves them in a combined data file projection-input.RData.

• 02-projections.R Carries out all counterfactual population projections, derives summary indicators from the counterfactual population projections, and saves these summary indicators in a combined data file projection-output.RData.

• 03-out.R, 98-compare-sources-rr1.R, 98-compare-sources-rr2.R These three files create all plots and tables reported in our main manuscript, Supplementary Information, and/or or the point-by-point responses to the peer reviewers' comments. All output is stored in the automatically generated folder out.

• 00-main.R Installs all R packages necessary to replicate our findings, loads user input (such as the selected color palettes and random seeds), and automatically executes all analysis files listed above.

• 03-out-pub.R, 99-functions-pub.R These two stand-alone files create all plots reported in the journal version of our article, following the journal's formatting requirements. The file 03-out-pub.R installs all R packages necessary for plotting and automatically executes the file 99-functions-pub.R.

2. SocArXiv

The main folder SocArXiv contains all materials associated with version 1 of our manuscript preprint, as posted on SocArXiv (Ref. 7). This main folder is just for reference, as the analytical strategy and code have changed following the peer review of our manuscript.

How to Use this Repository

In order to run the R code provided in the repository CovPop, please proceed in the following order:

1. Download the repository from github. If applicable, unzip the downloaded folder and place it in a location convenient for you.
2. Double click on the file CovPop.Rproj in the Journal folder. This should open RStudio on your machine.
3. Within RStudio, click on File/Open File... and select the analysis file 00-main.R located in the scripts sub-folder.
4. You should now be able to run our code without adjusting any directories.

License

This work is licensed under a Creative Commons Attribution 4.0 International License.

References

1. United Nations, Department of Economic and Social Affairs, Population Division, World Population Prospects. https://population.un.org/wpp/. Version 2022.
2. Max Planck Institute for Demographic Research (Germany), University of California, Berkeley (USA), French Institute for Demographic Studies (France), Human Mortality Database (HMD). https://mortality.org. Version 03 April 2023.
3. Max Planck Institute for Demographic Research (Germany) and Vienna Institute of Demography (Austria), Human Fertility Database (HFD). https://humanfertility.org. Deposited 28 March 2023.
4. M.J.K. Osterman, B.E. Hamilton, J.A. Martin, A.K. Driscoll, C.P. Valenzuela, Births: Final Data for 2021. National Vital Statistics Reports 72(1) (2023).
5. E. Arias, J. Xu, United States Life Tables, 2019. National Vital Statistics Reports 70(19) (2022).
6. E. Arias, J. Xu, United States Life Tables, 2020. National Vital Statistics Reports 71(1) (2022).
7. A.M. Tilstra, A. Polizzi, S. Wagner, E.T. Akimova. The Long-term Effects of the COVID-19 Pandemic on U.S. Population Structure. SocArXiv. https://doi.org/10.31235/osf.io/rqn9j. Version 1. Submitted 28 March 2023.