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@article{Konstantinoudis:2023:10.32614/rj-2023-055,
author = {Konstantinoudis, G and Gómez-Rubio, V and Cameletti, M and Pirani, M and Baio, G and Blangiardo, M},
doi = {10.32614/rj-2023-055},
journal = {The R Journal},
pages = {89--104},
title = {A workflow for estimating and visualising excess mortality during the COVID-19 pandemic},
url = {http://dx.doi.org/10.32614/rj-2023-055},
volume = {15},
year = {2023}
}
TY - JOUR
AB - 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.
AU - Konstantinoudis,G
AU - Gómez-Rubio,V
AU - Cameletti,M
AU - Pirani,M
AU - Baio,G
AU - Blangiardo,M
DO - 10.32614/rj-2023-055
EP - 104
PY - 2023///
SN - 2073-4859
SP - 89
TI - A workflow for estimating and visualising excess mortality during the COVID-19 pandemic
T2 - The R Journal
UR - http://dx.doi.org/10.32614/rj-2023-055
VL - 15
ER -
Climate Science
Earth and Life Sciences
Energy and Low-Carbon Futures
Resources and Pollution
Economics and Finance
Health
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