On age-specific mortality trends since Covid-19 in Switzerland

On age-specific mortality trends since Covid-19 in Switzerland | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article On age-specific mortality trends since Covid-19 in Switzerland Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7327617/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background To study the evolution of age-specific mortality in Switzerland before and after the Covid-19 pandemic, in order to determine whether pre-pandemic trends have been recovered in 2023-24. Study design: Statistical analysis of official mortality data in Switzerland. Methods Standardized mortality rates by age group since Covid-19 were compared with those expected by continuing trends estimated over the pre-pandemic years 2000-19 by log-linear Poisson models, resulting in estimates of excess mortality for the period 2020-24. Overall mortality trends were also compared with official statistics of specific causes of death. Results Mortality in Switzerland showed in 2024 a complete return to pre-pandemic trends. However, there were marked differences between age groups. While mortality in age groups 0–14 and 45–64 was not affected by the pandemic, mortality in age groups 65–84 and 85+, after a significant increase during the pandemic, have partially, respectively completely, returned to pre-pandemic trends in 2024. In contrast, mortality in age group 15–44, especially for men, began to stagnate even before the pandemic, and has been consistently and significantly above trend in recent years. This is related to the fact that all leading causes of death seem to have stopped declining in this age group. Discussion While mortality in Switzerland has globally returned to its downward trend after the COVID-19 pandemic, this is not the case for all age groups, particularly among men aged 15 to 44, for whom all major causes of death have recently stabilized. Conclusions After a long period of decline, mortality among young adults has stagnated in Switzerland for the past decade, appearing to have reached a certain minimum. This should be taken into account when developing future mortality and life expectancy scenarios. Age-specific mortality all-cause mortality Covid-19 mortality trends standardized mortality rates Figures Figure 1 Figure 2 Background Mortality is a fundamental indicator of a country's general state of health and of its evolution over time [ 1 ]. During the Covid-19 years, excess all-cause mortality rapidly became the gold standard for measuring the impact of the pandemic, being considered a more reliable and informative indicator than Covid-19-specific mortality itself [ 2 ]. Using overall mortality, an excess of 15 to 18 million deaths worldwide for the period 2020-21 has been estimated by [ 3 – 4 ], around three times the number of deaths officially attributed to Covid-19. The impact of the pandemic on overall mortality in Europe and the US has also been quantified by [ 5 – 6 ] in terms of life expectancy losses induced by excess mortality, highlighting great variability between countries, with some Western European countries recovering their pre-pandemic levels by 2021 (e.g. Switzerland and Sweden) and others cumulating a loss in 2020 and a further worsening in 2021 (Eastern Europe and the US). In more recent years, there is evidence of a general recovery to pre-pandemic mortality levels and mortality trends in Europe. For example, the European mortality monitoring system EuroMOMO stated that “By spring 2023, overall European mortality had returned to expected levels in all age groups”, where expected levels were estimated on the basis of pre-pandemic trends (EUROMOMO), and the Eurostat agency pointed to an overall recovery of pre-pandemic life expectancy levels in Europe (Mortality and life expectancy statistics - Statistics Explained - Eurostat). However, the situation seems less optimistic in the US, where a recent study estimated for 2023 a significant excess mortality among young Americans aged 25 to 44 [ 7 ]. Also in Europe, some countries appear to experience less favorable mortality trends for certain age groups. In the UK, for example, an increase in all-cause mortality rates for middle-aged adults (30–54 years) was observed since 2012 [ 8 ]. Impact of Covid-19 pandemic on mortality in Switzerland was studied in [ 9 – 11 ] for years 2020-22, using standardized mortality rates to account for changes over time in the population size and age structure [ 12 – 13 ], where an overall excess of about 7 thousand deaths has been estimated for 2020. While the year 2021 was characterized by an approximate recovery to pre-pandemic levels, as also shown by [ 6 ] in terms of life expectancy, the year 2022 was marked by a new worsening, mainly referable to the summer heatwave that year, with nearly 2 thousand deaths in excess compared to 2019, and close to 5 thousand compared to what would be expected based on the pre-pandemic decreasing mortality trend. In the present study, we further analysed standardized mortality rates for the post-pandemic years 2023-24 in Switzerland to answer the question of whether pre-pandemic levels and trends have now been recovered five years after the onset of the pandemic. In addition, mortality trends were also analysed for five age groups (0–14 / 15–44 / 45–64 / 65–84 / 85+), to determine whether recent mortality trends depend on age. Finally, the understanding of those trends has been enhanced by looking at age-specific causes of death official statistics. Data and methods We considered data by the Swiss Federal Statistical Office (FSO) on annual numbers of deaths by 1 year of age and sex for the period 2000-24 (Décès selon l'âge et le sexe, de 1970 à 2024–1970-2024 | Tableau) and the size of the Swiss population by 1 year of age and by sex as of January 1 for the same period (Bilan démographique selon l'âge. PX-Web). Using these data and adopting an approach similar to that described in [ 9 – 11 ], we obtained (directly) standardized mortality rates (SMR) for the period 2000-24 in Switzerland, separately for both sexes. Standardization was made at the Swiss population as of January 1st, 2024. In order to estimate a pre-pandemic SMR trend, a log-linear Poisson model was applied for each sex to the age-specific mortality rates of the period 2000-19. By continuing this trend until 2024, we were able to estimate the SMR that would have been observed in 2020-24 if the pandemic had not occurred, i.e. what we might call the counterfactual , or expected mortality. Comparing observed SMR with expected SMR allowed us to estimate for each sex an absolute excess death (ED) and a % excess mortality (EM) for the years 2020-24, globally and by age groups 0–14 / 15–44 / 45–64 / 65–84 / 85+. The latter are considered statistically significant a given year if observed SMR lies beyond the limits of a 95% prediction interval (95%PI). Details about the formulation of the Poisson log-linear model, as well as the method used to calculate associated 95%PI can be found in Additional file 1. Finally, our results were compared with official FSO statistics on specific causes of death available for the period 2000-23 and the same age groups (Causes spécifiques de décès). All analyses were performed within the software R [ 14 ]. Results Observed and expected SMR per 1000 inhabitants over the period 2000-24 are presented in Figs. 1 and 2 for men and women, respectively, globally and for the five age groups 0–14 / 15–44 / 45–64 / 65–84 / 85+, while Table 1 contains the corresponding estimates of excess death ED (absolute numbers) and excess mortality EM (%) for years 2020-24. Looking first at mortality all ages combined, although men suffered a greater impact from the pandemic in 2020, SMR trends were largely the same for both sexes. After a relatively strong impact in 2020, with more than 7 thousand ED (EM = 12.2% for men and EM = 7.9% for women), followed by a complete recovery in 2021 for women and an approximate for men, both sexes, but especially women, experienced a worsening in 2022, a year marked by the summer heatwave and marginally by a “final” Covid-19 tail stroke. On the other hand, the years 2023 and 2024 saw a complete return to the pre-pandemic trend, with ED (and EM) close to zero in 2024. If we look at mortality trends by age group, we see marked differences. Understandably, age group 85+, which accounts for the majority of deaths, shows a quite similar pattern as the global mortality, except that trend was fully recovered in 2021 and the worsening was similar in 2022 for both sexes. The trend was again recovered in 2023, and the observed mortality was even significantly lower than expected in 2024, with almost 1.5 thousand saved deaths over both sexes. Each age group under 85 shows a very specific mortality pattern, similar for both sexes, but (much) more pronounced for men than for women. The 65–84 age group, after suffering a relatively sharp increase in mortality in 2020 (ED = 2362, EM = 14% for men; ED = 1125, EM = 8.8% for women), showed a slow and gradual recovery in the following years, which is not yet completed in 2024 (ED = 767, EM = 4.9% for men; ED = 630, EM = 5.2% for women). Mortality in the 45–64 age group was slightly affected in 2020-22 for men and unaffected for women, who never deviated from the trend during the pandemic (Figs. 1 – 2 ). In contrast, the 15–44 age group experienced a mortality stabilization, which began just before the start of the pandemic, and which resulted in significantly more deaths than expected in recent years (in 2024, ED = 260, EM = 36.8% for men; ED = 79, EM = 20.8% for women). Mortality in the age group 0–14, although already low, did not significantly deviate from the declining trend, also in recent years. Crude mortality rates associated with the four main causes of death for each sex and age group are represented graphically in Additional file 2 for the period 2000-23. Official Covid-19 mortality since 2020 has also been added to the graphs, showing an almost complete resorption by 2023. None of the main causes of death have increased in recent years. However, some have stabilized in certain age groups, in particular cancer after age 65, and notably in age group 65–84, where it became the leading cause of death from the mid-2000s. In age group 15–44, accidents and suicides, the main causes of death for men, have also recently stabilized after a declining period, while cancer-related deaths, the main cause of death for women, appear to be continuing to decline among women, while levelling off among men, as are cardiovascular related deaths. In age group 85+, cardiovascular mortality, the leading cause of death in this age group and globally, continues to decline in men, while it recently tended to stabilize in women. On the other hand, deaths attributed to dementia, which were rising since the 2000s, are now stabilizing or declining. Table 1 Excess death ED (absolute values) and excess mortality EM (%) for men and women, globally and by five age groups between 2020 and 2024 in Switzerland (FSO data). Bold figures represent significant deviations from expected mortality. ED (EM) 2020 2021 2022 2023 2024 MEN All 4552 (12.2%) 1601 (4.4%) 2475 (6.9%) 698 (2.0%) 306 (0.9%) 0–14 28 (13.8%) 5 (2.5%) 20 (10.3%) 24 (12.5%) 1 (0.5%) 15–44 113 (13.8%) 163 (20.7%) 214 (28.2%) 177 (24.1%) 260 (36.8%) 45–64 154 (3.4%) 274 (6.1%) 155 (3.6%) -58 (-1.4%) -105 (-2.5%) 65–84 2362 (13.9%) 1255 (7.6%) 1555 (9.5%) 869 (5.4%) 767 (4.9%) 85+ 1895 (13.0%) -96 (-0.7%) 531 (3.7) -315 (-2.2%) -617 (-4.4%) WOMEN All 3014 (7.9%) 303 (0.8%) 1800 (4.8%) 256 (0.7%) -157 (-0.4%) 0–14 6 (3.5%) -8 (-4.7%) 8 (4.7%) -4 (-2.4%) 4 (2.4%) 15–44 57 (13.3%) 33 (8.0%) 90 (22.4%) 93 (23.8%) 79 (20.8%) 45–64 -69 (-2.5%) 34 (1.2%) -39 (-1.5%) -170 (-6.5%) -66 (-2.5%) 65–84 1125 (8.8%) 684 (5.4%) 1110 (8.9%) 582 (4.7%) 630 (5.2%) 85+ 1895 (8.5%) -440 (-2.0%) 632 (2.9%) -245 (-1.1%) -804 (-3.7%) Discussion Excess mortality related to the Covid-19 pandemic in Switzerland was described in [ 9 – 11 ]. The main question of the present study was whether this excess mortality has now been recovered five years after the start of the pandemic, and the same question was investigated for different age groups. Using data from the Swiss Federal Statistical Office (FSO), we were able to report a full recovery by 2024 of the pre-pandemic downward mortality trend for both sexes. Looking at age groups of 0–14 / 15–44 / 45–64 / 65–84 / 85+, however, we observed a remarkably different mortality pattern in each age group. Age groups 0–14 and 45–64 have not at all, respectively little suffered from the pandemic and (almost) never deviated significantly from the pre-pandemic mortality trends. Age group 85+, after a significant increase of mortality during the pandemic and the heatwave of summer 2022, has more than fully recovered pre-pandemic mortality trends by 2024, possibly due to some harvesting effect [ 15 ]. Age group 65–84 also suffered from the pandemic and is still struggling to recover downward trends. It is not yet clear whether this represents simply a further delay in recovery or a more structural change of mortality trend. In contrast, age group 15–44 seems to have completely lost its declining trend, mortality beginning to stagnate even before the pandemic. These results are consistent with what has been observed in the US and the UK, where a departure from previous downward trends has been reported for young adults, although with some increase, rather than just stagnation of mortality [ 7 – 8 ]. For an attempt to understand why mortality has returned to the downward trend for some age groups and deviated for others, we have examined the official statistics on mortality by cause of death. Cause-of-death statistics are one of Switzerland's oldest federal statistics, dating back to 1876. Diagnoses are classified according to World Health Organization (WHO) rules, focusing on the underlying cause of death, i.e. “the disease or injury that initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury” [ 16 ]. Despite the limitations of the official definition, which does not take into account multiple causes of deaths [ 17 – 18 ], and the fact that these statistics only contain crude and non-standardized mortality rates, with the latest year 2024 not yet available, their examination enabled us to gain a better understanding of recent trends in age-specific mortality, or at least to rule out some a priori possible explanations for some trends deviations. Firstly, the reason for the slow and incomplete recovery in the 65–84 age group by 2024, as well as for the stagnant mortality in the 15–44 age group in recent years after a prolonged mortality decline, cannot be directly attributed to Covid-19. In fact, the 15–44 age group was virtually unaffected by the pandemic, while Covid-19 mortality in the 65–84 age group has almost completely disappeared by 2023 (and probably completely by 2024). Secondly, these deviations were not due to the increase of some cause of death during this period, but to a stagnation in several leading causes of mortality, such as accidents and suicides in the 15–44 age group, and cancers for ages 65 and beyond. Thirdly, most of these stagnations cannot be considered as indirect consequences of the pandemic or its management, since they had already begun a few years before, as had the levelling off for overall mortality in some age groups, and in particular in young adults of 15–44. Recently, a question was raised as to whether mortality during the Covid-19 pandemic should be compared with previous levels (e.g. the year 2019) or with previous trends in order to estimate an excess mortality [ 11 ]. Given that pre-pandemic trends were downward, a comparison with mortality trends will result in more “pessimistic” estimates of excess mortality than a comparison with mortality levels. Despite the speculative aspects inherent in a comparison with previous trends, which might be strongly model-dependent [ 19 ], as opposed to the entirely factual nature of a comparison with previous levels, five years after the onset of the pandemic, we have opted here for the second approach. However, the stagnation of mortality in some age groups suggests that it might be important to re-estimate some trends using more recent data. As major demographic studies have pointed out, mortality rates have been falling in developed countries since the mid-1800s [ 20 – 21 ]. For several decades, most of the progress in mortality, and the consequent increase in life expectancy, was due to improvements in mortality among children and young people. Since the middle of the last century, improvements among people over 60, and then over 80, have begun to contribute significantly to progress in life expectancy [ 22 ], leading to very optimistic claims about the prospect of unlimited human lifespans [ 23 ]. The present study shows for Switzerland what has already been shown for other countries such as the US and the UK, namely that while mortality among the oldest people continues to fall, mainly due to downward trends in cardiovascular mortality [ 24 ], progress slows or even halts at younger ages, where mortality seems to have reached some kind of minimum. Conclusion In conclusion, while mortality in Switzerland has globally returned to its downward trend after the COVID-19 pandemic, this is not the case among young adults, for whom mortality has stagnated for the past decade. If these new trends are confirmed over the next few years, they will need to be taken into account in forecasts of future life expectancy [ 25 – 26 ], as this indicator is particularly affected by a possible stagnation in mortality among young or relatively young age groups, which will potentially lead to less optimistic life expectancy scenarios. Realistic scenarios regarding life expectancy are themselves essential for decision-making in the areas of insurance, retirement plans, and healthcare cost management. Declarations Consent for publication: “Not applicable” Competing interest: “The authors declare that they have not competing interest” Fundings: “Not applicable” Author Contribution Conceptualization: Isabella Locatelli, Valentin Rousson.Data curation: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Formal analysis: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Investigation: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Methodology: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Writing – original draft: Isabella LocatelliWriting – review & editing: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson. Acknowledgement: “Not applicable” Data Availability All data are publicly available and can be accessed on the websites mentioned in the Data and Methods section. References Choi J, Ki M, Kwon HJ, Park B, Bae S, Oh CM, Chun BC, Oh GJ, Lee YH, Lee TY, Cheong HK, Choi BY, Park JH, Park SK. (2019). Health Indicators Related to Disease, Death, and Reproduction. J Prev Med Public Health. 2019;52(1):14–20. 10.3961/jpmph.18.250 Beaney T, Clarke JM, Jain V, Golestaneh AK, Lyons G, Salman D et al. (2020). Excess mortality: the gold standard in measuring the impact of COVID-19 worldwide? J R Soc Med 113(9):329–334. https://doi.org/10.1177/0141076820956802 PMID: 32910871. COVID-19 Excess Mortality Collaborators. Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020–21 (2022). Lancet 16: 399(10334):1513–36. https://doi.org/10.1016/S0140-6736(21)02796-3 Msemburi W, Karlinsky A, Knutson V, Aleshin-Guendel S, Chatterji S, Wakefield J. The WHO estimates of excess mortality associated with the COVID-19 pandemic. Nature. 2023;613(7942):130–7. https://doi.org/10.1038/s41586-022-05522-2 . Aburto JM, Schöley J, Kashnitsky I, Zhang L, Rahal C, Missov TI et al. (2022). Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries. Int J Epidemiol . https://doi.org/10.1093/ije/dyab207 PMID: 34564730. Schöley J, Aburto JM, Kashnitsky I, Kniffka MS, Zhang L, Jaadla H et al. Life expectancy changes since COVID-19 (2022). Nat Hum Behav . 6(12):1649–1659. https://doi.org/10.1038/s41562-022-01450-3 PMID: 36253520. Wrigley-Field E, Raquib RV, Berry KM, Morris KJ, Stokes AC. Mortality Trends Among Early Adults in the United States, 1999–2023. JAMA Netw Open. 2025;8(1):e2457538. 10.1001/jamanetworkopen.2024.57538 . Pérez-Reche FJ. Age-specific all-cause mortality trends in the UK: Pre-pandemic increases and the complex impact of COVID-19. Public Health. 2024;236:0033–3506. https://doi.org/10.1016/j.puhe.2024.09.007 . Locatelli I, Rousson V. A first analysis of excess mortality in Switzerland in 2020. PLoS ONE. 2021;16(6):e0253505. https://doi.org/10.1371/journal.pone.0253505 . Locatelli I, Rousson V. Mortality in Switzerland in 2021. PLoS ONE. 2022;17(9):e0274295. https://doi.org/10.1371/journal.pone.0274295 . Locatelli I, Rousson V. Two complementary approaches to estimate an excess of mortality: The case of Switzerland 2022. PLoS ONE. 2023;18(8):e0290160. https://doi.org/10.1371/journal.pone.0290160 . Neison F. On a method recently proposed for conducting inquiries into the comparative sanatory condition of various districts. J Royal Stat Soc Lond (now Royal Stat Society). 1844;7:40–68. Fleiss JL, Levin B, Cho PM. Statistical methods for rates and proportions. Wiley Series in Probability and Statistics Eds; 2003. R Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2024. Riou J, Hauser A, Fesser A, et al. Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland. Nat Commun. 2023;14:90. https://doi.org/10.1038/s41467-022-35770-9 . World Health Organization WHO, Geneva. (1977). Manual of the International Statistical Classification of Diseases, Injuries, and Causes of Death. Vol. 1. Israel RA, Rosenberg HM, Curtin L. (1986). Analytical potential for multiple cause-of-death data. American Journal of Epidemiology 124: 161 – 79. Lindahl BIB, Johansson LA. Multiple cause-of-death data as a tool for detecting artificial trends in the underlying cause statistics: a methodological study. Scand J Soc Med. 1994;2:145–58. Ferenci T. Comparing methods to predict baseline mortality for excess mortality calculations–unravelling ‘the German puzzle’ and its implications for spline-regression. MedRxiv. 2023. https://doi.org/10.1101/2022.07.18.22277746 . Christensen K, Doblhammer G, Rau R, Vaupel JW. Ageing populations: The challenges ahead. Lancet. 2009;374. 10.1016/S0140-6736(09)61460-4 . Oeppen J, Vaupel JW. Broken limits to life expectancy. Science. 2002;296. 10.1126/science.1069675 . Vallin J, Meslé F. (2009). The segmented trend line of highest life expectancies. Popul Dev Rev 35. Vaupel JW. Biodemography of human ageing. Nature. 2010;464. 10.1038/nature08984 . Beltrán-Sánchez H, Preston SH, Canudas-Romo V. An integrated approach to cause-of-death analysis: Cause-deleted life tables and decompositions of life expectancy. Demographic Res. 2008;19. 10.4054/DemRes.2008.19.35 . Denney JT, McNown R, Rogers RG, Doubilet S. Stagnating Life Expectancies and Future Prospects in an Age of Uncertainty. Soc Sci Q. 2013;94(2):445–61. https://doi.org/10.1111/j.1540-6237.2012 . Vaupel JW, Villavicencio F, Bergeron-Boucher MP. Demographic perspectives on the rise of longevity. Proc Natl Acad Sci USA. 2021. https://doi.org/10.1073/pnas.2019536118 . Additional Declarations No competing interests reported. Supplementary Files Additionalfile1.docx Additionalfile2.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7327617","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":500383507,"identity":"582eb967-55c1-4436-b4de-287e41c3a5ec","order_by":0,"name":"Isabella Locatelli","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABK0lEQVRIie3Qv2rCQBzA8V84OJdfzXol0rzCLxRiobG+ykkgk4NbO4kgZFJcfYxM0m6Rg7j0Dbro4tTBLqIg2EtTSiFn5w735Za748P9AbDZ/mH8awzuABrVQqvJWA5A3/vO6AIhAcDKqQTkjMuKcDOBOgGknw0Tabpqu96R8IGx5e54iJA3cO8NBkO/7Y9zOD7XjxBJO5iTCEaMx9cTmeiLXS28OangJeXSmb4aCIQeknBGDENAqSqClDtZgcSctE7c1d47keiWxDnJsya41WTYzQp3ZyTQDz39/F5JGMq8JFwT1tOngJGI/mMwIRGn+i1eK4nLT769R1JxViS0nNaJP1st1oenqDNrjJcf79HDjeuqzRuehp1Mqc36WCe/bmgqvwxsNpvN9kef6stUjuIYkg0AAAAASUVORK5CYII=","orcid":"","institution":"University of Lausanne","correspondingAuthor":true,"prefix":"","firstName":"Isabella","middleName":"","lastName":"Locatelli","suffix":""},{"id":500383509,"identity":"92c8f301-9d56-4b8f-899a-ae95c282a150","order_by":1,"name":"Djuly Asumpta Pierre-Paul","email":"","orcid":"","institution":"University of Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Djuly","middleName":"Asumpta","lastName":"Pierre-Paul","suffix":""},{"id":500383511,"identity":"0ce471c9-0aed-4274-9c56-1f68d31c6f01","order_by":2,"name":"Valentin Rousson","email":"","orcid":"","institution":"University of Lausanne","correspondingAuthor":false,"prefix":"","firstName":"Valentin","middleName":"","lastName":"Rousson","suffix":""}],"badges":[],"createdAt":"2025-08-08 13:23:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7327617/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7327617/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89273876,"identity":"36c9da0a-290e-4d97-8b06-6a341fb33cc0","added_by":"auto","created_at":"2025-08-18 09:11:22","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":580266,"visible":true,"origin":"","legend":"\u003cp\u003eSMR for 1000 inhabitants in Switzerland, globally and by five age groups. Standardization at the Swiss population as of January 1\u003csup\u003est\u003c/sup\u003e, 2024. Men (FSO data) \u0026nbsp;\u003c/p\u003e","description":"","filename":"image1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7327617/v1/7a8ef56dac286a2ed046744c.jpeg"},{"id":89273878,"identity":"79859346-6e77-4c6b-9256-33fa3902daf4","added_by":"auto","created_at":"2025-08-18 09:11:22","extension":"jpeg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":558071,"visible":true,"origin":"","legend":"\u003cp\u003eSMR for 1000 inhabitants in Switzerland, globally and by five age groups. Standardization at the Swiss population as of January 1\u003csup\u003est\u003c/sup\u003e, 2024. Women (FSO data)\u003c/p\u003e","description":"","filename":"image2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-7327617/v1/dbc915c1cada87a09e23095a.jpeg"},{"id":90026037,"identity":"7c04e1da-7bff-44fe-9c36-b81eb43c48fb","added_by":"auto","created_at":"2025-08-27 14:08:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1736636,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7327617/v1/27f0f1fd-1431-4081-a9aa-66d347ce6777.pdf"},{"id":89274345,"identity":"1507a2d2-af2f-442c-a183-ad87fd176a09","added_by":"auto","created_at":"2025-08-18 09:19:22","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":24194,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-7327617/v1/7d5ded29ca07847d03f99e98.docx"},{"id":89273885,"identity":"b3dbafaf-2ce2-43cf-9867-4e5c73fad88c","added_by":"auto","created_at":"2025-08-18 09:11:22","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":538999,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile2.docx","url":"https://assets-eu.researchsquare.com/files/rs-7327617/v1/25d0c8df23722c46b9846c88.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"On age-specific mortality trends since Covid-19 in Switzerland","fulltext":[{"header":"Background","content":"\u003cp\u003eMortality is a fundamental indicator of a country's general state of health and of its evolution over time [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. During the Covid-19 years, excess all-cause mortality rapidly became the gold standard for measuring the impact of the pandemic, being considered a more reliable and informative indicator than Covid-19-specific mortality itself [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Using overall mortality, an excess of 15 to 18\u0026nbsp;million deaths worldwide for the period 2020-21 has been estimated by [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], around three times the number of deaths officially attributed to Covid-19. The impact of the pandemic on overall mortality in Europe and the US has also been quantified by [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] in terms of life expectancy losses induced by excess mortality, highlighting great variability between countries, with some Western European countries recovering their pre-pandemic levels by 2021 (e.g. Switzerland and Sweden) and others cumulating a loss in 2020 and a further worsening in 2021 (Eastern Europe and the US).\u003c/p\u003e\u003cp\u003eIn more recent years, there is evidence of a general recovery to pre-pandemic mortality levels and mortality trends in Europe. For example, the European mortality monitoring system EuroMOMO stated that \u0026ldquo;By spring 2023, overall European mortality had returned to expected levels in all age groups\u0026rdquo;, where expected levels were estimated on the basis of pre-pandemic trends (EUROMOMO), and the Eurostat agency pointed to an overall recovery of pre-pandemic life expectancy levels in Europe (Mortality and life expectancy statistics - Statistics Explained - Eurostat). However, the situation seems less optimistic in the US, where a recent study estimated for 2023 a significant excess mortality among young Americans aged 25 to 44 [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Also in Europe, some countries appear to experience less favorable mortality trends for certain age groups. In the UK, for example, an increase in all-cause mortality rates for middle-aged adults (30\u0026ndash;54 years) was observed since 2012 [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eImpact of Covid-19 pandemic on mortality in Switzerland was studied in [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] for years 2020-22, using standardized mortality rates to account for changes over time in the population size and age structure [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], where an overall excess of about 7 thousand deaths has been estimated for 2020. While the year 2021 was characterized by an approximate recovery to pre-pandemic levels, as also shown by [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e] in terms of life expectancy, the year 2022 was marked by a new worsening, mainly referable to the summer heatwave that year, with nearly 2 thousand deaths in excess compared to 2019, and close to 5 thousand compared to what would be expected based on the pre-pandemic decreasing mortality trend.\u003c/p\u003e\u003cp\u003eIn the present study, we further analysed standardized mortality rates for the post-pandemic years 2023-24 in Switzerland to answer the question of whether pre-pandemic levels and trends have now been recovered five years after the onset of the pandemic. In addition, mortality trends were also analysed for five age groups (0\u0026ndash;14 / 15\u0026ndash;44 / 45\u0026ndash;64 / 65\u0026ndash;84 / 85+), to determine whether recent mortality trends depend on age. Finally, the understanding of those trends has been enhanced by looking at age-specific causes of death official statistics.\u003c/p\u003e"},{"header":"Data and methods","content":"\u003cp\u003eWe considered data by the Swiss Federal Statistical Office (FSO) on annual numbers of deaths by 1 year of age and sex for the period 2000-24 (D\u0026eacute;c\u0026egrave;s selon l'\u0026acirc;ge et le sexe, de 1970 \u0026agrave; 2024\u0026ndash;1970-2024 | Tableau) and the size of the Swiss population by 1 year of age and by sex as of January 1 for the same period (Bilan d\u0026eacute;mographique selon l'\u0026acirc;ge. PX-Web).\u003c/p\u003e\u003cp\u003eUsing these data and adopting an approach similar to that described in [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], we obtained (directly) standardized mortality rates (SMR) for the period 2000-24 in Switzerland, separately for both sexes. Standardization was made at the Swiss population as of January 1st, 2024. In order to estimate a pre-pandemic SMR trend, a log-linear Poisson model was applied for each sex to the age-specific mortality rates of the period 2000-19. By continuing this trend until 2024, we were able to estimate the SMR that would have been observed in 2020-24 if the pandemic had not occurred, i.e. what we might call the \u003cem\u003ecounterfactual\u003c/em\u003e, or expected mortality. Comparing observed SMR with expected SMR allowed us to estimate for each sex an absolute excess death (ED) and a % excess mortality (EM) for the years 2020-24, globally and by age groups 0\u0026ndash;14 / 15\u0026ndash;44 / 45\u0026ndash;64 / 65\u0026ndash;84 / 85+. The latter are considered statistically significant a given year if observed SMR lies beyond the limits of a 95% prediction interval (95%PI). Details about the formulation of the Poisson log-linear model, as well as the method used to calculate associated 95%PI can be found in Additional file 1.\u003c/p\u003e\u003cp\u003eFinally, our results were compared with official FSO statistics on specific causes of death available for the period 2000-23 and the same age groups (Causes sp\u0026eacute;cifiques de d\u0026eacute;c\u0026egrave;s). All analyses were performed within the software R [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eObserved and expected SMR per 1000 inhabitants over the period 2000-24 are presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e for men and women, respectively, globally and for the five age groups 0\u0026ndash;14 / 15\u0026ndash;44 / 45\u0026ndash;64 / 65\u0026ndash;84 / 85+, while Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e contains the corresponding estimates of excess death ED (absolute numbers) and excess mortality EM (%) for years 2020-24.\u003c/p\u003e\u003cp\u003eLooking first at mortality all ages combined, although men suffered a greater impact from the pandemic in 2020, SMR trends were largely the same for both sexes. After a relatively strong impact in 2020, with more than 7 thousand ED (EM\u0026thinsp;=\u0026thinsp;12.2% for men and EM\u0026thinsp;=\u0026thinsp;7.9% for women), followed by a complete recovery in 2021 for women and an approximate for men, both sexes, but especially women, experienced a worsening in 2022, a year marked by the summer heatwave and marginally by a \u0026ldquo;final\u0026rdquo; Covid-19 tail stroke. On the other hand, the years 2023 and 2024 saw a complete return to the pre-pandemic trend, with ED (and EM) close to zero in 2024.\u003c/p\u003e\u003cp\u003eIf we look at mortality trends by age group, we see marked differences. Understandably, age group 85+, which accounts for the majority of deaths, shows a quite similar pattern as the global mortality, except that trend was fully recovered in 2021 and the worsening was similar in 2022 for both sexes. The trend was again recovered in 2023, and the observed mortality was even significantly lower than expected in 2024, with almost 1.5 thousand saved deaths over both sexes.\u003c/p\u003e\u003cp\u003eEach age group under 85 shows a very specific mortality pattern, similar for both sexes, but (much) more pronounced for men than for women. The 65\u0026ndash;84 age group, after suffering a relatively sharp increase in mortality in 2020 (ED\u0026thinsp;=\u0026thinsp;2362, EM\u0026thinsp;=\u0026thinsp;14% for men; ED\u0026thinsp;=\u0026thinsp;1125, EM\u0026thinsp;=\u0026thinsp;8.8% for women), showed a slow and gradual recovery in the following years, which is not yet completed in 2024 (ED\u0026thinsp;=\u0026thinsp;767, EM\u0026thinsp;=\u0026thinsp;4.9% for men; ED\u0026thinsp;=\u0026thinsp;630, EM\u0026thinsp;=\u0026thinsp;5.2% for women). Mortality in the 45\u0026ndash;64 age group was slightly affected in 2020-22 for men and unaffected for women, who never deviated from the trend during the pandemic (Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). In contrast, the 15\u0026ndash;44 age group experienced a mortality stabilization, which began just before the start of the pandemic, and which resulted in significantly more deaths than expected in recent years (in 2024, ED\u0026thinsp;=\u0026thinsp;260, EM\u0026thinsp;=\u0026thinsp;36.8% for men; ED\u0026thinsp;=\u0026thinsp;79, EM\u0026thinsp;=\u0026thinsp;20.8% for women). Mortality in the age group 0\u0026ndash;14, although already low, did not significantly deviate from the declining trend, also in recent years.\u003c/p\u003e\u003cp\u003eCrude mortality rates associated with the four main causes of death for each sex and age group are represented graphically in Additional file 2 for the period 2000-23. Official Covid-19 mortality since 2020 has also been added to the graphs, showing an almost complete resorption by 2023. None of the main causes of death have increased in recent years. However, some have stabilized in certain age groups, in particular cancer after age 65, and notably in age group 65\u0026ndash;84, where it became the leading cause of death from the mid-2000s. In age group 15\u0026ndash;44, accidents and suicides, the main causes of death for men, have also recently stabilized after a declining period, while cancer-related deaths, the main cause of death for women, appear to be continuing to decline among women, while levelling off among men, as are cardiovascular related deaths. In age group 85+, cardiovascular mortality, the leading cause of death in this age group and globally, continues to decline in men, while it recently tended to stabilize in women. On the other hand, deaths attributed to dementia, which were rising since the 2000s, are now stabilizing or declining.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eExcess death ED (absolute values) and excess mortality EM (%) for men and women, globally and by five age groups between 2020 and 2024 in Switzerland (FSO data). Bold figures represent significant deviations from expected mortality.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c7\" namest=\"c3\"\u003e\u003cp\u003eED (EM)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2020\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2023\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2024\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eMEN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAll\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e4552 (12.2%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1601 (4.4%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e2475 (6.9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e698 (2.0%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e306 (0.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (13.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5 (2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 (10.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e24 (12.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e1 (0.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e113 (13.8%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e163 (20.7%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e214 (28.2%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e177 (24.1%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e260 (36.8%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e154 (3.4%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e274 (6.1%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e155 (3.6%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-58 (-1.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-105 (-2.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u0026ndash;84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e2362 (13.9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e1255 (7.6%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e1555 (9.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e869 (5.4%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e767 (4.9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1895 (13.0%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-96 (-0.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e531 (3.7)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e-315 (-2.2%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e-617 (-4.4%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003eWOMEN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAll\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e3014 (7.9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e303 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e1800 (4.8%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e256 (0.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-157 (-0.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u0026ndash;14\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (3.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-8 (-4.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e8 (4.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-4 (-2.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e4 (2.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e57 (13.3%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (8.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e90 (22.4%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e93 (23.8%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e79 (20.8%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u0026ndash;64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-69 (-2.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34 (1.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-39 (-1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e-170 (-6.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e-66 (-2.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e65\u0026ndash;84\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1125 (8.8%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e684 (5.4%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e1110 (8.9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e582 (4.7%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e630 (5.2%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e\u003cb\u003e1895 (8.5%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e\u003cb\u003e-440 (-2.0%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u003cb\u003e632 (2.9%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e-245 (-1.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u003cb\u003e-804 (-3.7%)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eExcess mortality related to the Covid-19 pandemic in Switzerland was described in [\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. The main question of the present study was whether this excess mortality has now been recovered five years after the start of the pandemic, and the same question was investigated for different age groups. Using data from the Swiss Federal Statistical Office (FSO), we were able to report a full recovery by 2024 of the pre-pandemic downward mortality trend for both sexes. Looking at age groups of 0\u0026ndash;14 / 15\u0026ndash;44 / 45\u0026ndash;64 / 65\u0026ndash;84 / 85+, however, we observed a remarkably different mortality pattern in each age group.\u003c/p\u003e\u003cp\u003eAge groups 0\u0026ndash;14 and 45\u0026ndash;64 have not at all, respectively little suffered from the pandemic and (almost) never deviated significantly from the pre-pandemic mortality trends. Age group 85+, after a significant increase of mortality during the pandemic and the heatwave of summer 2022, has more than fully recovered pre-pandemic mortality trends by 2024, possibly due to some harvesting effect [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Age group 65\u0026ndash;84 also suffered from the pandemic and is still struggling to recover downward trends. It is not yet clear whether this represents simply a further delay in recovery or a more structural change of mortality trend. In contrast, age group 15\u0026ndash;44 seems to have completely lost its declining trend, mortality beginning to stagnate even before the pandemic. These results are consistent with what has been observed in the US and the UK, where a departure from previous downward trends has been reported for young adults, although with some increase, rather than just stagnation of mortality [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eFor an attempt to understand why mortality has returned to the downward trend for some age groups and deviated for others, we have examined the official statistics on mortality by cause of death. Cause-of-death statistics are one of Switzerland's oldest federal statistics, dating back to 1876. Diagnoses are classified according to World Health Organization (WHO) rules, focusing on the underlying cause of death, i.e. \u0026ldquo;the disease or injury that initiated the train of morbid events leading directly to death, or the circumstances of the accident or violence which produced the fatal injury\u0026rdquo; [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Despite the limitations of the official definition, which does not take into account multiple causes of deaths [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e], and the fact that these statistics only contain crude and non-standardized mortality rates, with the latest year 2024 not yet available, their examination enabled us to gain a better understanding of recent trends in age-specific mortality, or at least to rule out some \u003cem\u003ea priori\u003c/em\u003e possible explanations for some trends deviations.\u003c/p\u003e\u003cp\u003eFirstly, the reason for the slow and incomplete recovery in the 65\u0026ndash;84 age group by 2024, as well as for the stagnant mortality in the 15\u0026ndash;44 age group in recent years after a prolonged mortality decline, cannot be directly attributed to Covid-19. In fact, the 15\u0026ndash;44 age group was virtually unaffected by the pandemic, while Covid-19 mortality in the 65\u0026ndash;84 age group has almost completely disappeared by 2023 (and probably completely by 2024). Secondly, these deviations were not due to the increase of some cause of death during this period, but to a stagnation in several leading causes of mortality, such as accidents and suicides in the 15\u0026ndash;44 age group, and cancers for ages 65 and beyond. Thirdly, most of these stagnations cannot be considered as indirect consequences of the pandemic or its management, since they had already begun a few years before, as had the levelling off for overall mortality in some age groups, and in particular in young adults of 15\u0026ndash;44.\u003c/p\u003e\u003cp\u003eRecently, a question was raised as to whether mortality during the Covid-19 pandemic should be compared with previous levels (e.g. the year 2019) or with previous trends in order to estimate an excess mortality [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Given that pre-pandemic trends were downward, a comparison with mortality trends will result in more \u0026ldquo;pessimistic\u0026rdquo; estimates of excess mortality than a comparison with mortality levels. Despite the speculative aspects inherent in a comparison with previous trends, which might be strongly model-dependent [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], as opposed to the entirely factual nature of a comparison with previous levels, five years after the onset of the pandemic, we have opted here for the second approach. However, the stagnation of mortality in some age groups suggests that it might be important to re-estimate some trends using more recent data.\u003c/p\u003e\u003cp\u003eAs major demographic studies have pointed out, mortality rates have been falling in developed countries since the mid-1800s [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. For several decades, most of the progress in mortality, and the consequent increase in life expectancy, was due to improvements in mortality among children and young people. Since the middle of the last century, improvements among people over 60, and then over 80, have begun to contribute significantly to progress in life expectancy [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], leading to very optimistic claims about the prospect of unlimited human lifespans [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The present study shows for Switzerland what has already been shown for other countries such as the US and the UK, namely that while mortality among the oldest people continues to fall, mainly due to downward trends in cardiovascular mortality [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], progress slows or even halts at younger ages, where mortality seems to have reached some kind of minimum.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, while mortality in Switzerland has globally returned to its downward trend after the COVID-19 pandemic, this is not the case among young adults, for whom mortality has stagnated for the past decade. If these new trends are confirmed over the next few years, they will need to be taken into account in forecasts of future life expectancy [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], as this indicator is particularly affected by a possible stagnation in mortality among young or relatively young age groups, which will potentially lead to less optimistic life expectancy scenarios. Realistic scenarios regarding life expectancy are themselves essential for decision-making in the areas of insurance, retirement plans, and healthcare cost management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eConsent for publication:\u003c/h2\u003e\n\u003cp\u003e\u0026ldquo;Not applicable\u0026rdquo;\u003c/p\u003e\n\u003ch2\u003eCompeting interest:\u003c/h2\u003e\n\u003cp\u003e\u0026ldquo;The authors declare that they have not competing interest\u0026rdquo;\u003c/p\u003e\n\u003ch2\u003eFundings:\u003c/h2\u003e\n\u003cp\u003e\u0026ldquo;Not applicable\u0026rdquo;\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eConceptualization: Isabella Locatelli, Valentin Rousson.Data curation: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Formal analysis: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Investigation: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Methodology: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.Writing \u0026ndash; original draft: Isabella LocatelliWriting \u0026ndash; review \u0026amp; editing: Isabella Locatelli, Djuly Asumpta Pierre-Paul, Valentin Rousson.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement:\u003c/h2\u003e\n\u003cp\u003e\u0026ldquo;Not applicable\u0026rdquo;\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eAll data are publicly available and can be accessed on the websites mentioned in the Data and Methods section.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eChoi J, Ki M, Kwon HJ, Park B, Bae S, Oh CM, Chun BC, Oh GJ, Lee YH, Lee TY, Cheong HK, Choi BY, Park JH, Park SK. (2019). Health Indicators Related to Disease, Death, and Reproduction. J Prev Med Public Health. 2019;52(1):14\u0026ndash;20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3961/jpmph.18.250\u003c/span\u003e\u003cspan address=\"10.3961/jpmph.18.250\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeaney T, Clarke JM, Jain V, Golestaneh AK, Lyons G, Salman D et al. (2020). Excess mortality: the gold standard in measuring the impact of COVID-19 worldwide? \u003cem\u003eJ R Soc Med\u003c/em\u003e 113(9):329\u0026ndash;334. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1177/0141076820956802\u003c/span\u003e\u003cspan address=\"10.1177/0141076820956802\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e PMID: 32910871.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eCOVID-19 Excess Mortality Collaborators. Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020\u0026ndash;21 (2022). Lancet 16: 399(10334):1513\u0026ndash;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(21)02796-3\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(21)02796-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMsemburi W, Karlinsky A, Knutson V, Aleshin-Guendel S, Chatterji S, Wakefield J. The WHO estimates of excess mortality associated with the COVID-19 pandemic. Nature. 2023;613(7942):130\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41586-022-05522-2\u003c/span\u003e\u003cspan address=\"10.1038/s41586-022-05522-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAburto JM, Sch\u0026ouml;ley J, Kashnitsky I, Zhang L, Rahal C, Missov TI et al. (2022). Quantifying impacts of the COVID-19 pandemic through life-expectancy losses: a population-level study of 29 countries. \u003cem\u003eInt J Epidemiol\u003c/em\u003e. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1093/ije/dyab207\u003c/span\u003e\u003cspan address=\"10.1093/ije/dyab207\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e PMID: 34564730.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSch\u0026ouml;ley J, Aburto JM, Kashnitsky I, Kniffka MS, Zhang L, Jaadla H et al. Life expectancy changes since COVID-19 (2022). \u003cem\u003eNat Hum Behav\u003c/em\u003e. 6(12):1649\u0026ndash;1659. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41562-022-01450-3\u003c/span\u003e\u003cspan address=\"10.1038/s41562-022-01450-3\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e PMID: 36253520.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWrigley-Field E, Raquib RV, Berry KM, Morris KJ, Stokes AC. Mortality Trends Among Early Adults in the United States, 1999\u0026ndash;2023. JAMA Netw Open. 2025;8(1):e2457538. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1001/jamanetworkopen.2024.57538\u003c/span\u003e\u003cspan address=\"10.1001/jamanetworkopen.2024.57538\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eP\u0026eacute;rez-Reche FJ. Age-specific all-cause mortality trends in the UK: Pre-pandemic increases and the complex impact of COVID-19. Public Health. 2024;236:0033\u0026ndash;3506. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.puhe.2024.09.007\u003c/span\u003e\u003cspan address=\"10.1016/j.puhe.2024.09.007\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLocatelli I, Rousson V. A first analysis of excess mortality in Switzerland in 2020. PLoS ONE. 2021;16(6):e0253505. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0253505\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0253505\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLocatelli I, Rousson V. Mortality in Switzerland in 2021. PLoS ONE. 2022;17(9):e0274295. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0274295\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0274295\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLocatelli I, Rousson V. Two complementary approaches to estimate an excess of mortality: The case of Switzerland 2022. PLoS ONE. 2023;18(8):e0290160. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1371/journal.pone.0290160\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0290160\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eNeison F. On a method recently proposed for conducting inquiries into the comparative sanatory condition of various districts. J Royal Stat Soc Lond (now Royal Stat Society). 1844;7:40\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFleiss JL, Levin B, Cho PM. Statistical methods for rates and proportions. Wiley Series in Probability and Statistics Eds; 2003.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eR Core Team. R: A Language and Environment for Statistical Computing. Vienna, Austria: R Foundation for Statistical Computing; 2024.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eRiou J, Hauser A, Fesser A, et al. Direct and indirect effects of the COVID-19 pandemic on mortality in Switzerland. Nat Commun. 2023;14:90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41467-022-35770-9\u003c/span\u003e\u003cspan address=\"10.1038/s41467-022-35770-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization WHO, Geneva. (1977). Manual of the International Statistical Classification of Diseases, Injuries, and Causes of Death. Vol. 1.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eIsrael RA, Rosenberg HM, Curtin L. (1986). Analytical potential for multiple cause-of-death data. \u003cem\u003eAmerican Journal of Epidemiology\u003c/em\u003e 124: 161\u0026thinsp;\u0026ndash;\u0026thinsp;79.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eLindahl BIB, Johansson LA. Multiple cause-of-death data as a tool for detecting artificial trends in the underlying cause statistics: a methodological study. Scand J Soc Med. 1994;2:145\u0026ndash;58.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eFerenci T. Comparing methods to predict baseline mortality for excess mortality calculations\u0026ndash;unravelling \u0026lsquo;the German puzzle\u0026rsquo; and its implications for spline-regression. MedRxiv. 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1101/2022.07.18.22277746\u003c/span\u003e\u003cspan address=\"10.1101/2022.07.18.22277746\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eChristensen K, Doblhammer G, Rau R, Vaupel JW. Ageing populations: The challenges ahead. Lancet. 2009;374. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/S0140-6736(09)61460-4\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(09)61460-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eOeppen J, Vaupel JW. Broken limits to life expectancy. Science. 2002;296. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1126/science.1069675\u003c/span\u003e\u003cspan address=\"10.1126/science.1069675\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVallin J, Mesl\u0026eacute; F. (2009). The segmented trend line of highest life expectancies. Popul Dev Rev 35.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVaupel JW. Biodemography of human ageing. Nature. 2010;464. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/nature08984\u003c/span\u003e\u003cspan address=\"10.1038/nature08984\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBeltr\u0026aacute;n-S\u0026aacute;nchez H, Preston SH, Canudas-Romo V. An integrated approach to cause-of-death analysis: Cause-deleted life tables and decompositions of life expectancy. Demographic Res. 2008;19. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4054/DemRes.2008.19.35\u003c/span\u003e\u003cspan address=\"10.4054/DemRes.2008.19.35\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eDenney JT, McNown R, Rogers RG, Doubilet S. Stagnating Life Expectancies and Future Prospects in an Age of Uncertainty. Soc Sci Q. 2013;94(2):445\u0026ndash;61. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/j.1540-6237.2012\u003c/span\u003e\u003cspan address=\"10.1111/j.1540-6237.2012\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eVaupel JW, Villavicencio F, Bergeron-Boucher MP. Demographic perspectives on the rise of longevity. Proc Natl Acad Sci USA. 2021. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1073/pnas.2019536118\u003c/span\u003e\u003cspan address=\"10.1073/pnas.2019536118\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Age-specific mortality, all-cause mortality, Covid-19, mortality trends, standardized mortality rates","lastPublishedDoi":"10.21203/rs.3.rs-7327617/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7327617/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eTo study the evolution of age-specific mortality in Switzerland before and after the Covid-19 pandemic, in order to determine whether pre-pandemic trends have been recovered in 2023-24.\u003c/p\u003e\u003ch2\u003eStudy design:\u003c/h2\u003e\u003cp\u003eStatistical analysis of official mortality data in Switzerland.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eStandardized mortality rates by age group since Covid-19 were compared with those expected by continuing trends estimated over the pre-pandemic years 2000-19 by log-linear Poisson models, resulting in estimates of excess mortality for the period 2020-24. Overall mortality trends were also compared with official statistics of specific causes of death.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eMortality in Switzerland showed in 2024 a complete return to pre-pandemic trends. However, there were marked differences between age groups. While mortality in age groups 0\u0026ndash;14 and 45\u0026ndash;64 was not affected by the pandemic, mortality in age groups 65\u0026ndash;84 and 85+, after a significant increase during the pandemic, have partially, respectively completely, returned to pre-pandemic trends in 2024. In contrast, mortality in age group 15\u0026ndash;44, especially for men, began to stagnate even before the pandemic, and has been consistently and significantly above trend in recent years. This is related to the fact that all leading causes of death seem to have stopped declining in this age group.\u003c/p\u003e\u003ch2\u003eDiscussion\u003c/h2\u003e\u003cp\u003eWhile mortality in Switzerland has globally returned to its downward trend after the COVID-19 pandemic, this is not the case for all age groups, particularly among men aged 15 to 44, for whom all major causes of death have recently stabilized.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eAfter a long period of decline, mortality among young adults has stagnated in Switzerland for the past decade, appearing to have reached a certain minimum. This should be taken into account when developing future mortality and life expectancy scenarios.\u003c/p\u003e","manuscriptTitle":"On age-specific mortality trends since Covid-19 in Switzerland","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-18 09:11:17","doi":"10.21203/rs.3.rs-7327617/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6dcd0110-03d4-4eb3-87bf-f1b1dc41aeaf","owner":[],"postedDate":"August 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-08-27T14:08:11+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-18 09:11:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7327617","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7327617","identity":"rs-7327617","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}