Clustering of age standardised COVID-19 infection fatality ratios and death trajectories

Thu Lan Kelly, Greer Humphrey, Caroline Miller, Jacqueline A. Bowden, Joanne Dono, Paddy A. Phillips

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Background An accurate measure of the impact of COVID-19 is the infection fatality ratio, or the proportion of deaths among those infected, which does not depend on variable testing rates between nations. The risk of mortality from COVID-19 depends strongly on age and current estimates of the infection fatality ratio do not account for differences in national age profiles. Comparisons of cumulative death trajectories allow the effect and timing of public health interventions to be assessed. Our purpose is to (1) determine whether countries are clustered according to infection fatality ratios and (2) compare interventions to slow the spread of the disease by clustering death trajectories. Methods National age standardised infection fatality ratios were derived from age stratified estimates from China and population estimates from the World Health Organisation. The IFRs were clustered into groups using Gaussian mixture models. Trajectory analysis clustered cumulative death rates in two time windows, 50 and 100 days after the first reported death. Findings Infection fatality ratios from 201 nations were clustered into three groups: young, medium and older, with corresponding means (SD) of 0.20% (0.03%), 0.38% (0.11%) and 0.93% (0.21%). At 50 and 100 days after the first reported death, there were two clusters of cumulative death trajectories from 113 nations with at least 25 deaths reported at 100 days. The first group had slowly increasing or stable cumulative death rates, while the second group had accelerating rates at the end of the time window. Fifty-two nations changed group membership between the time windows. Conclusion A cluster of younger nations have a lower estimated infection fatality ratio than older nations. The effect and timing of public health interventions in preventing the spread of the disease can be tracked by clustering death rate trajectories into stable or accelerating and comparing changes over time.

Original languageEnglish
JournalUnknown Journal
Publication statusPublished or Issued - 20 Nov 2020

ASJC Scopus subject areas

  • Medicine(all)

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