Related Experiment Video
Updated: Aug 29, 2025

10:00
Measurement of Lifespan in Drosophila melanogaster
Published on: January 7, 2013
34.6K
Mortality in Switzerland in 2021
Isabella Locatelli1, Valentin Rousson1
1Center for Primary Care and Public Health (Unisanté), University of Lausanne, Lausanne, Switzerland.
Plos One
|September 9, 2022
Summary
In 2021, Swiss mortality returned to pre-pandemic levels after a COVID-19 surge in late 2020. Life expectancy recovered for women but remained slightly below 2019 levels for men, particularly those aged 50-70.
Area of Science:
- Public Health
- Demography
- Epidemiology
Background:
- The COVID-19 pandemic significantly impacted global mortality trends in 2020.
- Understanding the second year of the pandemic's effect on mortality is crucial for public health planning.
Purpose of the Study:
- To analyze mortality trends in Switzerland during 2021, the second year of the COVID-19 pandemic.
- To compare 2021 mortality data with previous years to assess pandemic impact.
Main Methods:
- Utilized data from the Swiss Federal Statistical Office.
- Analyzed standardized weekly deaths, annual mortality rates (overall and stratified by age/sex), and life expectancy.
- Compared 2021 data against pre-pandemic years and 2020.
Main Results:
- Switzerland experienced a moderate COVID-19 wave in late 2021.
- Overall mortality in 2021 nearly returned to 2019 levels (+0.8%), a significant recovery from the 2020 increase (+9.2%).
- Life expectancy for women returned to 2019 levels, while men's life expectancy recovered to 2018 levels, with a slight deficit from 2019, primarily affecting the 50-70 age group.
Conclusions:
- Mortality levels in Switzerland approximated pre-pandemic levels in the second year of COVID-19.
- Mortality recovery was faster for women than for men compared to 2020 levels.
Related Concept Videos
Actuarial Approach
117
The actuarial approach, a statistical method originally developed for life insurance risk assessment, is widely used to calculate survival rates in clinical and population studies. This method accounts for participants lost to follow-up or those who die from causes unrelated to the study, ensuring a more accurate representation of survival probabilities.
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
117
Life Tables
167
A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
167
Survival Curves
267
Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
267
Applications of Life Tables
107
Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
107
Cancer Survival Analysis
429
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
429
Hazard Rate
170
The hazard rate, also known as the hazard function or failure rate, is a statistical measure used to describe the instantaneous rate at which an event occurs, given that the event has not yet happened. From a probabilistic perspective, it represents the likelihood that a subject will experience the event in a very small time interval, conditional on surviving up to the beginning of that interval. In terms of frequency, the hazard rate can be viewed as the ratio of the number of events to the...
170

