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Comparing successive COVID-19 Waves within and between Countries: A challenge when dealing with imperfect Data

Catalina Torres, Muséum National D'histoire Naturelle
France Meslé, Institut National d'Études Démographiques (INED)
Magali Barbieri, Institut National d'Études Démographiques (INED)
Florian Bonnet, Institut National d'Études Démographiques (INED)
Carlo Giovanni Camarda, Institut National d'Études Démographiques (INED)
Emmanuelle Cambois, Institut National d'Études Démographiques (INED)
Arianna Caporali, Institut National d'Études Démographiques (INED)
Etienne Couppié, Institut national d'études démographiques (INED)
jenny garcia, Institut National d'Études Démographiques (INED)
Iris Hourani, Institut national d'études démographiques INED
Svitlana Poniakina, Insitut National D'Études Démographiques
Jean-Marie Robine, Institut National de la Santé et de la Recherche Médicale (INSERM)

The COVID-19 pandemic is characterized by a succession of waves which developed differently over time and space. Comparing the demographic characteristics of people who died during these different waves across various countries could provide valuable insights into the efficiency of the health measures implemented by the governments. However, such comparisons are not so straightforward given the heterogeneity of available data between countries/data sources. In a recently published paper, we discussed a number of issues to take into consideration when carrying out international comparisons of COVID-19 mortality. These issues were illustrated with concrete examples, using data from the “Demography of COVID-19 deaths” database for the first phase of the epidemic. The purpose of the present paper is to extend those analyses to the second and third waves, especially in those countries with comparable death counts. Further analyses will answer the following questions: How did mortality change from one wave to the next? Were age patterns modified? Was there convergence between male and female mortality? For which ages? Can these changes be explained by health policies and, for the most recent, vaccination ? Some preliminary results are included in this extended abstract.

Keywords: COVID-19, Age structure, Mortality

See extended abstract.

Presented in Session 186. Demographic Analysis of the Covid-19 Pandemic