Following catastrophic events such as pandemics or wars, a systematic loss in life expectancy at birth ( \(\:{e}_{0}\) ) can be observed. This study aims to estimate the time required for \(\:{e}_{0}\) to recover after mortality crises and to identify which age groups contribute to the decline and assist in restoring pre-crisis levels. Focusing on major European pandemics and wars of the 19th and 20th centuries, we used data from the Human Mortality Database (HMD). Arriaga’s decomposition was applied to analyze \(\:{e}_{0}\) values before the sharpest decline and at the recovery point. Events were categorized into pandemics and non-pandemics, and further stratified by sex. Various statistical tests were used to ensure valid comparisons. The analysis is grounded in demographic resilience, understood as the capacity of a population to return to previous \(\:{e}_{0}\) levels after a mortality shock. This approach enables comparison between events of different types and historical contexts. Our findings show that the largest \(\:{e}_{0}\) declines occurred during the World Wars. No significant differences were found by event type or sex. Youth and children emerged as the main contributors to the decline and recovery of \(\:{e}_{0}\) following catastrophic events.
