A Workflow for Estimating and Visualising Excess Mortality During the COVID-19 Pandemic

COVID-19 related deaths estimates underestimate the pandemic burden on mortality because they suffer from completeness and accuracy issues. Excess mortality is a popular alternative, as it compares the observed number of deaths versus the number that would be expected if the pandemic did not occur. The expected number of deaths depends on population trends, temperature, and spatio-temporal patterns. In addition to this, high geographical resolution is required to examine within country trends and the effectiveness of the different public health policies. In this tutorial, we propose a workflow using R for estimating and visualising excess mortality at high geographical resolution. We show a case study estimating excess deaths during 2020 in Italy. The proposed workflow is fast to implement and allows for combining different models and presenting aggregated results based on factors such as age, sex, and spatial location. This makes it a particularly powerful and appealing workflow for online monitoring of the pandemic burden and timely policy making.

Garyfallos Konstantinoudis (MRC Centre for Environment and Health, Imperial College London,) , Virgilio Gómez-Rubio (Departamento de Matemáticas, Escuela Técnica Superior de Ingenier\(\acute{\imath}\)a Industrial-Albacete, Universidad de Castilla-La Mancha,) , Michela Cameletti (Department of Economics, University of Bergamo,) , Monica Pirani (MRC Centre for Environment and Health, Imperial College London,) , Gianluca Baio (Department of Statistical Sciences, University College London,) , Marta Blangiardo (MRC Centre for Environment and Health, Imperial College London,)
2023-11-08

0.1 Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2023-055.zip

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Konstantinoudis, et al., "A Workflow for Estimating and Visualising Excess Mortality During the COVID-19 Pandemic", The R Journal, 2023

BibTeX citation

@article{RJ-2023-055,
  author = {Konstantinoudis, Garyfallos and Gómez-Rubio, Virgilio and Cameletti, Michela and Pirani, Monica and Baio, Gianluca and Blangiardo, Marta},
  title = {A Workflow for Estimating and Visualising Excess Mortality During the COVID-19 Pandemic},
  journal = {The R Journal},
  year = {2023},
  note = {https://doi.org/10.32614/RJ-2023-055},
  doi = {10.32614/RJ-2023-055},
  volume = {15},
  issue = {2},
  issn = {2073-4859},
  pages = {89-104}
}

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