# Cohort-resolved excess mortality in Germany (2000-2024): Patterns and implications for the SARS-CoV-2 era

## TL;DR

This study examines age-specific mortality patterns in Germany from 2000 to 2024, revealing hidden trends during the SARS-CoV-2 pandemic that are not visible in overall population data.

## Contribution

The paper introduces a cohort-resolved framework to detect age-specific excess and under-mortality patterns in Germany over two decades.

## Key findings

- Sustained excess mortality was observed in adults aged 75-79 and 35-49 from late 2021 to 2024.
- Persistent under-mortality was found in cohorts aged 30-34 and 55-59.
- Excess mortality in older age groups in previous years suggests generational vulnerabilities linked to early-life adversity.

## Abstract

Understanding the impact of the SARS-CoV-2 pandemic on mortality requires more than aggregate statistics. While whole-population indicators have informed policy, they risk concealing subgroup-specific patterns. We analysed all-cause mortality in Germany from 2000 to 2024 using a weekly, cohort-resolved framework across 15 age groups to detect excess and under-mortality before, during, and after the pandemic.

Expected mortality was modelled using exponential trends from two decades of pre-pandemic data. Deviations from expectation were quantified as normalised excess all-cause mortality rates (NEAMR), enabling the identification of significant, age-specific anomalies.

We found sustained NEAMR in adults aged 75-79 and 35-49 from late 2021 through 2024—patterns absent in whole-population trends. Conversely, cohorts aged 30-34 and 55-59 showed persistent under-mortality. Earlier excess peaks in older cohorts (e.g., 85-89 in 2003, 95+ in 2013) suggest generational vulnerabilities potentially linked to early-life adversity. Cross-correlation analyses indicate that associations between NEAMR and SARS-CoV-2 mRNA injection rates diverge from expected protective patterns in most age cohorts, especially during the 2021 ‘alpha-to-delta’ transition. These findings highlight the need for further hypothesis-driven investigations as well as a high-resolution mortality surveillance. Cohort-resolved analysis reveals NEAMR signals that aggregate data obscure, offering a more accurate assessment of public health outcomes across demographic groups.