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Quantifying impacts of the COVID-19 pandemic through life expectancy losses

A population-level study of 29 countries

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Introduction


This is a repository to accompany 'Quantifying impacts of the COVID-19 pandemic through life expectancy losses: a population-level study of 29 countries'. A link to the open-access version of the paper can be found by clicking here. The replication files for this paper include customised functionality written in the R statistical programming language.

An interactive data visualisation relating to this work can be found here:

https://covid19.demographicscience.ox.ac.uk/lifeexpectancy

Prerequisites


As a pre-requisite to running this locally, you will need a working installation of R with all of the necessary dependencies installed.

Running the Code


To run this code, do something like:

$ git clone https://github.com/OxfordDemSci/ex2020.git

and then execute each of the scripts (0 through 10) which will undertake sequential tasks like defining skeletons, to undertaking the PCLM, cleaning outputs for analysis, and data visualisation

Structure


  • cfg relates to: configuration files
  • dat relates to: input source data
  • out relates to: output data, figures, and sensitivity analysis
  • src relates to: code to replicate the wrangling, analysis and visualisation
  • tmp relates to: a subdir to store temporary files
  • ass relates to: a place to store repo assets

Versioning


This version of the code is pre-publication (v.0.1.0). If you have any suggestions, please don't hesitate to raise an issue here on this repository, or to e-mail one of the corresponding authors of the paper!

License


This work is free. You can redistribute it and/or modify it under the terms of the GNU Public license and subject to all prior terms and licenses imposed by the free, public data sources provided by the HMD-STMF, CoverAge-DB, UK-ONS, and US-CDC (i.e. the 'data originators'). The code comes without any warranty, to the extent permitted by applicable law.

Acknowledgements

We are grateful to the extensive comments provided by Jim Oeppen, Alyson van Raalte, John Ermisch and Christiaan Monden. Funding was generously provided by a British Academy Newton International Fellowship, the Rockwool Foundation’s Excess Deaths grant, a Leverhulme Trust Large Centre Grant, a John Fell Fund grant, a European Research Council grant and the Interdisciplinary Centre on Population Dynamics (CPop).