Speaker
Description
The COVID-19 pandemic has led to excess mortality worldwide. Notably, the reported numbers of excess deaths are different from the numbers of deaths from COVID-19. Evaluating pandemic-related mortality should therefore not only be based on cause-of-death data but also on external life tables to enable calculation of population-based measures of the difference between observed and expected mortality. We investigated the impact of infection with and vaccination against COVID-19 on excess mortality during 2020-2021 in persons aged 65 years or older in the Netherlands.
We did this by incorporating relative survival modelling into a multi-state model considering vaccination, the acute and post-acute phase of (re)infection, and death based on the recent methodology by Manevski et al (2022). The key assumption of relative survival is that the observed hazard of death is the sum of the (unobserved) background and excess hazards where the former is derived from life tables or other historical data. The multi-state model is a time-inhomogeneous Markov model, stratified by sex and age. In this model, transition probabilities can be estimated by the Aalen-Johansen estimator. Different from the standard relative survival setting, the excess ‘hazard’ was a negative quantity for some groups during some periods, making regression modelling by means of a proportional hazards model infeasible. Instead, we explored additive hazards models. Modelling a pandemic made the choice of calendar time as timescale the most obvious, the consequences of which will be discussed, especially violation of the Markov property. In an extended model, we split different reported causes of death into a background and an excess part. We applied the model on real-world, nationwide and unselected individual data from Statistics Netherlands (CBS).
From 1 January 2020 until the end of 2021, the total cumulative probability of excess mortality was 0.3%, 4.4% of all mortality. This percentage was markedly higher for older persons, especially men, both in absolute terms and as a percentage of subgroup-specific observed mortality. Almost all excess mortality took place after an infection but its probability was much lower for persons who had received a vaccination.
The novel multi-state model incorporating relative survival enables to split all mortality in background and excess mortality with and without intermediate events. The current application shows the value outside the traditional context of relative survival for cancer patients. Further extensions incorporating, a.o., regression modelling of background and excess hazard, underreported infections and a mechanistic model for disease transmission are under development.
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