ADM's APPLE: The Accelerated Deaths Model with an Application to the Covid-19 Pandemic

The Accelerated Deaths Model (ADM) builds on the hypothesis that, within a given age cohort, those who are less healthy are more likely to die if infected with Covid-19 than healthier people, leaving a pool of on-average healthier survivors. We use the term ‘detrimental selection’ which has two complementary aspects: the lower years of life lost by those who experienced an accelerated death; and the higher average life expectancy of survivors which we call their ‘adjusted post-pandemic life expectancy’ (ADM's APPLE). Our model represents a novel synthesis of recent advances in our understanding of mortality heterogeneity and the development of the Proportionality Hypothesis – both of which have improved our understanding of the Covid-19 pandemic. In particular, we identify an important positive relationship between mortality heterogeneity and accelerated deaths. We find, in the case of the Covid-19 pandemic in England, that the years of life lost by those who experienced an accelerated death, while significantly lower than pre-Covid life expectancy, was greater than reported in the media at the time. We also find that the increase in the mean life expectancy of survivors was very small. As a result, the impact on annuity providers (e.g., in terms of potentially higher annuity prices), pension schemes and life insurers was also very small. In contrast, we find that the impact on life expectancy of a general change in future mortality assumptions post-pandemic (i.e., the base mortality table and improvement rate) would be much greater. The ADM has potentially wide application, e.g., to other types of contagion and to climate-related deaths, where we would expect there to be a positive correlation between deaths and all-cause mortality (consistent with the Proportionality Hypothesis), but where the degree of detrimental selection might be different.

Authors

Institutions

Publication Details

Journal
Insurance Mathematics and Economics
Published
2026-02-14
DOI
https://doi.org/10.1016/j.insmatheco.2026.103231
Primary Topic
Insurance, Mortality, Demography, Risk Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ADM's APPLE: The Accelerated Deaths Model with an Application to the Covid-19 Pandemic

Andrew Cairns, David Blake
Insurance Mathematics and Economics
Insurance, Mortality, Demography, Risk Management
article

ADM's APPLE: The Accelerated Deaths Model with an Application to the Covid-19 Pandemic

Andrew Cairns, David Blake
article en

Abstract

The Accelerated Deaths Model (ADM) builds on the hypothesis that, within a given age cohort, those who are less healthy are more likely to die if infected with Covid-19 than healthier people, leaving a pool of on-average healthier survivors. We use the term ‘detrimental selection’ which has two complementary aspects: the lower years of life lost by those who experienced an accelerated death; and the higher average life expectancy of survivors which we call their ‘adjusted post-pandemic life expectancy’ (ADM's APPLE). Our model represents a novel synthesis of recent advances in our understanding of mortality heterogeneity and the development of the Proportionality Hypothesis – both of which have improved our understanding of the Covid-19 pandemic. In particular, we identify an important positive relationship between mortality heterogeneity and accelerated deaths. We find, in the case of the Covid-19 pandemic in England, that the years of life lost by those who experienced an accelerated death, while significantly lower than pre-Covid life expectancy, was greater than reported in the media at the time. We also find that the increase in the mean life expectancy of survivors was very small. As a result, the impact on annuity providers (e.g., in terms of potentially higher annuity prices), pension schemes and life insurers was also very small. In contrast, we find that the impact on life expectancy of a general change in future mortality assumptions post-pandemic (i.e., the base mortality table and improvement rate) would be much greater. The ADM has potentially wide application, e.g., to other types of contagion and to climate-related deaths, where we would expect there to be a positive correlation between deaths and all-cause mortality (consistent with the Proportionality Hypothesis), but where the degree of detrimental selection might be different.

Insurance Mathematics and EconomicsVol. 128
St George's, University of London (GB), Maxwell Institute for Mathematical Sciences (GB), City St George's, University of London (GB)
Good health and well-being
Openalex Percentile: Top 64%
Insurance, Mortality, Demography, Risk Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.