Spatio-temporal Bayesian analysis of excess mortality in 5 European countries in 2020

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B9 L2 H2

Abstract

The COVID-19 pandemic produced excess mortality in many countries in 2020. In my talk, I will illustrate our use of Bayesian models and R software for the analysis of total deaths and population data, combined with environmental data, to the study of excess mortality in 2020. The study analyzes total deaths by age groups and sex in 5 European countries, and provides estimates of excess mortality at different levels of aggregation (province, autonomous community and country). For both data analysis and visualization of the results we have used the statistical software R. In addition, to explore the results we have developed an application in Shiny.

Brief Biography

Prof. Virgilio Gómez-Rubio is Full Professor in the Department of Mathematics, Universidad de Castilla-La Mancha (Spain). He has ample experience in Bayesian inference and statistical modeling as well as developing packages for the R programming language.  His book Bayesian inference with INLA has been widely adopted for Bayesian modeling and it has been awarded the 2022 SEIO-BBVA Foundation Award in the category of Data Science and Big Data. You can find more information about him is his website.

Presenters

Prof. Virgilio Gómez-Rubio, Department of Mathematics, Universidad de Castilla-La Mancha, Spain