The coronavirus disease 2019 (COVID-19) pandemic caused substantial health losses but not much is known about how these are distributed across the population. We aimed to estimate the distribution of years of life lost (YLL) due to COVID-19 and investigate its variation across the Dutch population, taking into account preexisting differences in health.

We used linked administrative data covering the entire 50+ Dutch population over 2012-2018 (n = 6,102,334) to estimate counterfactual individual-level life expectancy for those who died from COVID-19 in 2020 and 2021. We estimated survival models and used Cox-LASSO and Cox-Elastic Net to perform variable selection among the large set of potential predictors in our data. Using individual-level life expectancy predictions, we generated the distribution of YLL due to COVID-19 for the entire 50+ population by age and income.

On average, we estimate that individuals who died of COVID-19 had a counterfactual life expectancy about 28% lower than that of the rest of the population. Within this average, there was substantial heterogeneity, with 20% of all individuals who died of COVID-19 having an estimated life expectancy exceeding that of the age-specific population average. Both the richest and poorest COVID-19 decedents lost the same average number of YLL, which were similarly dispersed.

Accounting for preexisting health problems is crucial when estimating YLL due to COVID-19. While average life expectancy among COVID-19 decedents was substantially lower than for the rest of the population, the popular notion that only the frail died from COVID-19 is not true.

Vaccination campaigns were rolled out primarily to limit the impact of COVID-19 on severe health outcomes, including mortality.

We aimed to estimate the number of averted deaths by COVID-19 vaccination in the Belgian population aged 65 years and older, between January 2021 and January 2023.

Nationwide data on COVID-19 infections, vaccine administrations and all-cause mortality were individually linked. We estimated Vaccine Effectiveness against COVID-19 mortality (VE) among persons having received a vaccine dose in the last 6 months, using a Cox proportional hazards model adjusted for age, sex, time since vaccination, previous infection, underlying health conditions, province and income. COVID-19 death was defined as a person with a laboratory-confirmed SARS-CoV-2 infection who died within a specified interval. Based on obtained VE estimates, vaccine coverage and national COVID-19 mortality data, we estimated the number of averted deaths.

We estimated VE (confidence interval (CI)) at 0-59 days after vaccination, for 65-79 year and ≥ 80 year-olds respectively, at 81.9 % (CI 78.1 %-85.1 %) and 74.7 % (CI 71.2 %-77.7 %) during Alpha, at 90.5 % (CI 88.8 %-91.9 %) and 91.4 % (CI 90.4 %-92.4 %) during Delta and at 84.0 % (CI 81.8 %-85.9 %) and 74.5 % (CI 72.4 %-76.5 %) during Omicron period. Among the Belgian population aged 65 years and older, we estimated 12,806 deaths averted (CI 11,633-13,982), representing a 54 % reduction (CI 51 %-56 %) in the expected deaths (without vaccination). During the Delta period COVID-19 deaths were reduced by 68 %, during Omicron by 54 % and during Alpha by 31 %.

Vaccinating against COVID-19 reduced deaths by 54 % among the Belgian population aged 65 years and older, underscoring the importance of COVID-19 vaccines in reducing mortality.

Life expectancy in high-income countries remained lower in 2022 compared to pre-pandemic levels in 2019. This study explores the deficit of life expectancy and excess of years of life lost (YLL) in Spain from 2020 to 2022, assessing both direct effects of infectious diseases and indirect effects of other causes of death.

Data on life expectancy and YLL from 2010 to 2022 were obtained from the Spanish Institute for Statistics (INE). Using linear regression, we estimated expected life expectancy and YLL for 2020-2022 under the assumption that pre-pandemic trends (2010-2019) had continued.

During the first year of the pandemic, Spanish women lost 1.10 years and men lost 1.40 years in life expectancy. By 2022, life expectancy remained lower than in 2019 for both sexes. The excess YLL was similar across 2020 (2.40 million YLL and 5.3 YLL/100 people), 2021 (2.35 million YLL, 5.1 YLL/100 people), and 2022 (2.35 million YLL, 5.0 YLL/100 people). Approximately 70% of this excess was attributable to infectious diseases (87% in 2020, 78% in 2021, and 43% in 2022). Other major contributors to excess YLL included external causes, circulatory diseases, digestive diseases, and endocrine, nutritional, and metabolic diseases, while cancer mortality did not show an excess during the pandemic period.

Mortality in Spain in 2022 remained elevated compared to pre-pandemic expectations. The contribution of non-infectious diseases to excess mortality increased over time.

Not applicable.

Before the COVID-19 pandemic, life expectancy in Mexico stagnated from the early 2000s, mainly due to increased homicides. During the pandemic, Mexico experienced sizable excess mortality. We aimed to assess the contribution of violence, COVID-19, and causes of death that were amenable to healthcare to life-expectancy changes between 2015 and 2022 in Mexico.

We used administrative mortality and adjusted population estimates to construct life tables. We applied demographic methods to untangle contributions of causes of death to life-expectancy changes by year and sex at the subnational level.

Between 2015 and 2019, life expectancy declined from 71.8 to 71.1 years for males and stagnated at 77.6 years for females. Violence among young males explains most of the decline (54.3%). Between 2019 and 2020, life expectancy decreased by 7.1 and 4.4 years for males and females, respectively. COVID-19 accounted for 55.4% of that change for males and 57.7% for females. In 2021, male life expectancy stagnated but continued to decline for females by 0.44 years due to COVID-19 deaths. In 2022, we observed unequal recovery patterns in life expectancy across regions, as northern states experienced larger improvements than central and southern states.

We documented large variations in life-expectancy losses across Mexican states before, during, and after the COVID-19 pandemic. Before the pandemic, violence accounted for most of the male life-expectancy losses. During the pandemic, following COVID-19 deaths, mortality due to diabetes and causes that were amenable to healthcare contributed considerably to observed losses, with an uneven impact on the sexes.

Screening participants with a positive fecal immunochemical test (FIT) result and a subsequent negative colonoscopy are quarantined from the Danish bowel cancer screening program for 8 years. This recommendation is based on evidence from settings other than FIT-based screening, but referral of this evidence is not necessarily sufficient. We estimated the colorectal cancer (CRC) risk among these FIT-positive/colonoscopy-negative individuals and compared it with the risk in a historical unscreened population.Using national health registers in Denmark, we compared 29 936 participants with a positive FIT but negative colonoscopy with 720 850 randomly selected unscreened controls born 9 years earlier (ratio 1:24). Controls were assigned a pseudo-colonoscopy date 9 years prior to the negative colonoscopy group. We examined cases per 10 000 person-years and estimated relative risks (RR) and 95%CIs for CRC.After 8 years' follow-up, CRC risk was lower among FIT-positive/colonoscopy-negative participants compared with controls (RR 0.72, 95%CI 0.61-0.84). By age group and sex, the lower risk was only evident for women and men in their 60s (RR 0.67 [95%CI 0.47-0.96] and RR 0.65 [95%CI 0.48-0.88], respectively) and men in their 70s (RR 0.60 [95%CI 0.44-0.84]).The overall risk for CRC was lower for individuals with a positive FIT but negative colonoscopy compared with unscreened controls. However, the lower risk might not justify 8 years of quarantine, especially for women and younger age groups. Individualized screening is warranted and transfer of evidence from non-FIT screening should be done carefully.

In response to the rapid global transmission of COVID-19, governments worldwide enacted lockdowns and other non-pharmaceutical interventions (NPI) to control the disease. In this study, we aim to quantify the influence of NPIs on the transmission of COVID-19 within selected European regions, specifically Spain (including the Basque Country) and Italy (including Tuscany), during the period of February to December 2020, which predates the initiation of COVID-19 vaccinations. We investigate potential correlations and associations between the implementation of NPIs, changes in COVID-19 transmission rates, and alterations in life expectancy across different age and sex categories from the year 2019 to 2020.

We use a Susceptible-Hospitalized-Asymptomatic/Mild-Recovered-Deceased (SHARD) ordinary differential equations model to analyze COVID-19 dynamics in the studied regions. The model calibration process was performed with empirical data on hospitalization and death to estimate the weekly transmission and death rates. To quantify reductions in life expectancy, we used established survival analysis techniques.

The SHARD model effectively captures multiple waves of COVID-19, accurately representing peaks and aligning with the instantaneous reproduction number. Our analysis reveals a 66-78% reduction in transmission rates during the initial set of NPIs in March 2020, followed by a 34-55% reduction during the subsequent NPIs in October 2020. Additionally, the elderly and individuals with comorbidities experienced the most pronounced reductions in life expectancy.

Our model calibration approach provides a valuable tool for evaluating the effectiveness of interventions across multiple waves of an epidemic. By applying this method to COVID-19 dynamics, we have demonstrated the capacity to quantify the impact of non-pharmaceutical interventions (NPIs) on transmission rates. These findings offer practical insights into the effectiveness of NPIs in mitigating COVID-19 spread and contribute to the broader understanding of epidemic control strategies.

The burden of disease measures the total impact of diseases on a population, considering incidence, prevalence, disability, and premature mortality. This study analyzes the burden of ischemic heart disease (IHD) in Tabasco, Mexico, from 2013 to 2021. Ischemic heart disease has a significant incidence of 21,203,479 cases worldwide, and nationally (inside Mexico) a total of 221,747 cases, with more than 9,137,791 deaths due to this pathology globally.

To analyze the burden of ischemic heart disease in Tabasco, Mexico, during the 2013-2021 period.

An observational, descriptive, longitudinal, and retrospective study was conducted in Tabasco. The study population consisted of 2,402,598 people according to INEGI, with a sample of 927,000 adults (462,000 men and 465,000 women). Data were used from the General Directorate of Health Information, IHME, and the World Bank. Analyses were performed in Microsoft Excel, calculating measures of central tendency, dispersion, and Disability-Adjusted Life Years (DALYs).

The DALYs in the adult population of Tabasco were: 2013-23,932; 2014-28,132; 2015-30,197; 2016-30,683; 2017-31,839; 2018-38,599; 2019-40,046; 2020-42,307; and 2021-55,723, totaling 297,576 DALYs from 2013 to 2021.

Ischemic heart disease increased in incidence and mortality in both men and women during the years analyzed. The increase in DALYs indicates a greater impact of ischemic heart disease in Tabasco compared to countries like Costa Rica.

The burden of ischemic heart disease from 2013 to 2021 represents a significant loss of quality and years of life in the population of Tabasco, Mexico.

Studies have indicated that COVID-19 infection may accelerate the aging process in organisms. However, it remains unknown whether contracting COVID-19 affects life expectancy. Furthermore, the underlying biological mechanisms behind these findings are still unclear.

We conducted a prospective cohort study on 56,504 participants of European ancestry from the UK Biobank who reported the time and number of COVID-19 infection between January 2020 and September 2023. The parental average longevity was used as a proxy for their own longevity. Linear regression was used to assess the relationship between COVID-19 infection and longevity. Furthermore, we investigated the shared genetic basis between COVID-19 and longevity using large-scale genome-wide association studies (GWAS) for COVID-19 (122,616 cases and 2,475,240 controls) and longevity (3,484 cases and 25,483 controls). Mendelian randomization (MR) and mediation analysis were utilized to assess causal relationships and potential mediators between COVID-19 susceptibility and longevity. Shared genetic loci between the two phenotypes were identified using conjunctional false discovery rate (conjFDR) statistical frameworks.

After controlling for relevant covariates, COVID-19 infection might not be significantly correlated with longevity. In all MR methods, generalized summary-data-based Mendelian randomization (GSMR) analysis revealed a significant decrease in longevity due to severe COVID-19 infection (OR = 0.91, 95%CI: 0.84-0.98, P = 0.015). Mediation analysis identified stroke and myocardial infarction as potential mediators between COVID-19 susceptibility and reduced longevity. At conjFDR < 0.05, we identified rs62062323 (KANSL1) and rs9530111 (PIBF1) as shared loci between COVID-19 and longevity.

Together, our findings provided preliminary evidence for the shared genetic basics between COVID-19 and aging. This discovery may have implications for personalized medicine and preventive strategies, helping identify individuals who may be more vulnerable to severe outcomes from COVID-19 due to their genetic makeup.

Life expectancy is a vital indicator of a country's health and progress. Low-income countries face uncertainty regarding the long-term impact of the COVID-19 pandemic, driven by health expenditure levels, concerns over rising child mortality rates, and decreasing per capita income. These factors challenge life expectancy and demand urgent attention. This study aims to identify patterns, challenges, and opportunities to improve life expectancy in these countries through better health policies and resource allocation.

The research investigates the impact of the COVID-19 pandemic, health expenditure, per capita income, and child mortality rates on life expectancy in low-income countries. By examining 22 years of data from 20 countries, using a comprehensive dataset from the Our World in Data database, this study employs panel regression and time series analysis to explore how these factors influence life expectancy.

The findings indicate a significant negative effect of COVID-19 on life expectancy, while health expenditure and per capita income show a positive impact. Conversely, child mortality rates exert a negative effect on life expectancy in low-income countries.

This research contributes to the existing body of knowledge by analysing how COVID-19, health expenditure, per capita income, and child mortality collectively affect life expectancy in low-income countries. The insights gained may inform policymakers and health consultants about the need for targeted interventions, prioritising healthcare investment and child health. By addressing these critical areas, it may be possible to improve life expectancy and overall health outcomes, thus contributing to global health equity.

The coronavirus disease-2019 (COVID-19) pandemic significantly impacted global mortality, albeit Türkiye has been largely excluded from mortality studies owing to delayed data release and a lack of nationwide analyses.

To identify the excess mortality rates in Türkiye between 2020 and 2022, analyze the temporal trends and regional differences, and determine factors associated with excess deaths at the regional level.

A cross-sectional ecological analysis.

We analyzed all-cause mortality data from the Turkish Statistical Institute from January 2015 to December 2022. The projected deaths during 2020-2022 were derived from Quasi-Poisson Regression models applied to the 2015-2019 provincial mortality data, adjusting for seasonal trends, population offsets, and overdispersion. The results were aggregated to national and socioeconomic levels for comparative analyses. Excess deaths were calculated as the difference between observed and projected deaths. P-scores and excess mortality per 100,000 inhabitants were utilized as standardized metrics. Socioeconomic disparities were examined using the Socioeconomic Development Ranking of Provinces and Regions (SEGE-2017). We assessed the associations between excess mortality and vaccination coverage, elderly population ratio, intensive care unit beds per 100,000 population, and population per family physician.

Türkiye experienced 247,640 excess deaths [95% confidence interval (CI): 176,405-315,204] from 2020 to 2022. Excess mortality peaked in 2021 with 121,426 excess deaths (27.2% P-score, 143.5 per 100,000 population). Lower vaccination coverage [estimate: -0.51, 95% CI: (-0.81, -0.20), p = 0.001] and higher population per family physician [estimate: 0.01, 95% CI: (0.00, 0.02), p = 0.005] were significantly associated with higher excess mortality. A higher elderly population ratio was positively associated with excess deaths [estimate: 1.41, 95% CI: (0.50, 2.32), p = 0.003]. Socioeconomically less developed regions (SEGE 5 and SEGE 6) exhibited higher P-scores (21.3% and 20.2%, respectively), indicating greater relative increases in mortality when compared with the relatively more developed regions.

Excess mortality in Türkiye during the COVID-19 pandemic was substantial, particularly in 2021, and was influenced by regional socioeconomic disparities, vaccination coverage, and healthcare access. These findings underscore the importance of addressing sociodemographic factors and strengthening primary healthcare services in pandemic responses.

The overall impact of the COVID-19 pandemic on mortality can be estimated by the assessment of excess deaths from all causes because the reported number of deaths due to COVID-19 do not accurately reflect the true death toll. We assessed excess mortality in 2020 and 2021 in the Netherlands.

All analyses were performed on data from comprehensive nationwide registers provided by Statistics Netherlands (Centraal Bureau voor de Statistiek), including demographic characteristics and mortality. All-cause mortality incidence rates were calculated per calendar month and compared against COVID-19 infections and preventive strategies. The all-cause mortality incidence rate ratios (IRRs) with 95% confidence intervals (95% CIs) were estimated per calendar year using Poisson regression (overall and for subgroups).

Compared with predicted mortality based on 2019 rates, the overall excess mortality was 8.9% (IRR 1.089, 95% CI 1.081-1.097) in 2020 and 8.5% (IRR 1.085, 95% CI 1.077-1.092) in 2021. Relative excess mortality was higher for men, people with low household income, first-generation immigrants, and individuals living in extremely urbanized areas. In 2020, excess mortality was highest in age groups above 75 years (over 10%.); in 2021, it was clearly present even in the 20-39 years age group (6.6%).

Our results quantify excess mortality during the first 2 years of the COVID-19 pandemic in the Netherlands. We show that the extent of excess mortality varies considerably across demographic groups, which may help in identifying target groups for preventive strategies during future health crises.

Accurate measurement of exposure to SARS-CoV-2 in the population is crucial for understanding the dynamics of disease transmission and evaluating the impacts of interventions. However, it was particularly challenging to achieve this in the early phase of a pandemic because of the sparsity of epidemiological data. We previously developed an early pandemic diagnostic tool that linked minimum datasets: seroprevalence, mortality and infection testing data to estimate the true exposure in different regions of England and found levels of SARS-CoV-2 population exposure to be considerably higher than suggested by seroprevalence surveys. Here, we re-examine and evaluate the model in the context of reconstructing the first COVID-19 epidemic wave in England from three perspectives: validation against the Office for National Statistics (ONS) Coronavirus Infection Survey, relationship among model performance and data abundance and time-varying case detection ratios. We find that our model can recover the first, unobserved, epidemic wave of COVID-19 in England from March 2020 to June 2020 if two or three serological measurements are given as additional model inputs, while the second wave during winter of 2020 is validated by estimates from the ONS Coronavirus Infection Survey. Moreover, the model estimates that by the end of October in 2020 the UK government's official COVID-9 online dashboard reported COVID-19 cases only accounted for 9.1 % of cumulative exposure, dramatically varying across the two epidemic waves in England in 2020, 4.3 % vs 43.7 %.

Recent studies have shown that there are some advantages to forecasting mortality with indicators other than age-specific death rates. The mean, median, and modal ages at death can be directly estimated from the age-at-death distribution, as can information on lifespan variation. The modal age at death has been increasing linearly since the second half of the twentieth century, providing a strong basis from which to extrapolate past trends. The aim of this paper is to develop a forecasting model that is based on the regularity of the modal age at death and that can also account for changes in lifespan variation. We forecast mortality at ages 40 and above in 10 West European countries. The model we introduce increases forecast accuracy compared with other forecasting models and provides consistent trends in life expectancy and lifespan variation at age 40 over time.

The direct and indirect impacts of the COVID-19 pandemic on life expectancy (LE) and years of life lost with and without disability remain unclear. Accounting for pre-pandemic trends in morbidity and mortality, we assessed these impacts in 18 European countries, for the years 2020-2022.

We used multi-state Markov modeling based on several data sources to track transitions of the population aged 35 or older between eight health states from disease-free, combinations of cardiovascular disease, cognitive impairment, dementia, and disability, through to death. We quantified separately numbers and rates of deaths attributable to COVID-19 from those related to mortality from other causes during 2020-2022, and estimated the proportion of loss of life expectancy and years of life with and without disability that could have been avoided if the pandemic had not occurred. Estimates were disaggregated by COVID-19 versus non-COVID causes of deaths, calendar year, age, sex, disability status, and country. We generated the 95% uncertainty intervals (UIs) using Monte Carlo simulations with 500 iterations. Among the 289 million adult population in the 18 countries, person-years of life lost (PYLL) in millions were 4.7 (95% UI 3.4-6.0) in 2020, 7.1 (95% UI 6.6-7.9) in 2021, and 5.0 (95% UI 4.1-6.2) in 2022, totaling 16.8 (95% UI 12.0-21.8) million. PYLL per capita varied considerably between the 18 countries ranging between 20 and 109 per 1,000 population. About 60% of the total PYLL occurred among persons aged over 80, and 30% in those aged 65-80. If the pandemic were avoided, over half (9.8 million (95% UI 4.7-15.1)) of the 16.8 million PYLL were estimated to have been lived without disability. Of the total PYLL, 11.6-13.2 million were due to registered COVID-19 deaths and 3.6-5.3 million due to non-COVID mortality. Despite a decrease in PYLL attributable to COVID-19 after 2021, PYLL associated with other causes of death continued to increase from 2020 to 2022 in most countries. Lower income countries had higher PYLL per capita as well as a greater proportion of disability-free PYLL during 2020-2022. Similar patterns were observed for life expectancy. In 2021, LE at age 35 (LE-35) declined by up to 2.8 (95% UI 2.3-3.3) years, with over two-thirds being disability-free. With the exception of Sweden, LE-35 in the studied countries did not recover to 2019 levels by 2022.

The considerable loss of life without disability and the rise in premature mortality not directly linked to COVID-19 deaths during 2020-2022 suggest a potential broader, longer-term and partially indirect impact of the pandemic, possibly resulting from disruptions in healthcare delivery and services for non-COVID conditions and unintended consequences of COVID-19 containment measures. These findings highlight a need for better pandemic preparedness in Europe, ideally, as part of a more comprehensive global public health agenda.

In countries with limited civil registration and vital statistics systems, assessing the impact of health crises requires precise retrospective mortality data. We tested whether calendar methods improve survey or census data on dates of recent household deaths registered in a Health and Demographic Surveillance System (HDSS).

Between April and June 2023, we randomized 578 households with HDSS-registered deaths in Guinea-Bissau to interviews by using (i) a standard questionnaire with close-ended questions about dates of deaths, or similar questionnaires supplemented with (ii) a physical calendar of local events printed on paper or (iii) a digital calendar implemented on tablets. We evaluated the accuracy of reported dates through record linkages to HDSS data.

No deaths were reported in 11.8% of the 508 participating households. In other households (n = 448), informants reported 574 deaths since January 2020. Relative to the standard questionnaire, neither the physical calendar nor the digital calendar improved the proportion of deaths reported in the same month and year as recorded by using surveillance data. The physical and digital calendars reduced the share of missing data on dates of deaths (6.1% and 3.2%, respectively, versus 13.1% with the standard questionnaire). Reported dates of deaths obtained by using the digital calendar were more weakly correlated with surveillance data than those collected in other arms. Using the digital calendar also added 1.15 minutes to the data collection.

Digital calendars do not improve the reporting of dates of deaths in surveys or censuses. Further trials of the use of a physical calendar in retrospective interviews about recent household deaths are warranted.

This study investigated changes in life expectancy due to the COVID-19 pandemic by analyzing the contributions of age, sex, and cause of death in 2019 and 2022.

Korea's simplified life table and cause-of-death statistics from 2019 to 2022 were used to assess mortality changes by age, sex, and cause of death during the pandemic. Joinpoint regression analysis was applied to detect trends, and the Arriaga decomposition method was used to quantify the contributions of age, sex, and cause of death to life expectancy changes.

Joinpoint regression identified a slow increase in life expectancy in 2007 and a decline in 2020, coinciding with the COVID-19 pandemic. Life expectancy decreased markedly for men (-0.36 years per year, 95%CI: -0.68 to -0.03) and women (-0.45 years per year, 95%CI: -0.71 to -0.18). Age-specific contributions revealed declines across age groups, with the steepest reductions in the older population (80 years or older: -0.35 years for men; -0.52 years for women). Women (-0.68 years) contributed more to the decline in life expectancy than men (-0.41 years). COVID-19 ranked as the third leading cause of death in 2022, significantly contributing to the decline in life expectancy among the older population (aged 80 years or older: -0.306 years for men, -0.408 years for women). Women in Korea were more affected than men, reducing the sex-specific gap in life expectancy by 0.3 years.

The COVID-19 pandemic significantly impacted the life expectancy in Korea, particularly among older adults, with women experiencing a greater decline than men. These findings emphasize the need for targeted public health strategies to address age and sex disparities in future pandemics. Before the pandemic, non-communicable diseases such as malignant neoplasms, heart disease, and cerebrovascular disease dominated Korea's top 10 causes of death. During the pandemic, however, COVID-19 rose to third place by 2022. Notably, intentional self-harm (suicide) contributed to an increase in life expectancy, suggesting shifts in the relative impact of various causes of death.

Worldwide, mortality was strongly affected by the COVID-19 pandemic, both directly through COVID-19 deaths and indirectly through changes in other causes of death. Here, we examine the impact of the pandemic on COVID-19 and non-COVID-19 mortality in 24 countries: Australia, Austria, Brazil, Bulgaria, Canada, Chile, Croatia, Czechia, Denmark, England and Wales, Hungary, Japan, Latvia, Lithuania, The Netherlands, Northern Ireland, Poland, Russia, Scotland, South Korea, Spain, Sweden, Switzerland, and the United States. Using demographic decomposition methods, we compare age- and cause-specific contributions to changes in female and male life expectancy at birth in 2019-2020, 2020-2021, and 2021-2022 with those before the COVID-19 pandemic (2015-2019). We observe large life expectancy losses due to COVID-19 in most countries, usually followed by partial recoveries. Life expectancy losses due to cardiovascular disease (CVD) mortality were widespread during the pandemic, including in countries with substantial (Russia, Central and Eastern Europe, and the Baltic countries) and more modest (United States) improvements in CVD mortality before the pandemic. Many Anglo-Saxon countries, including Canada, Scotland, and the United States, continued their prepandemic trajectories of rising drug-related mortality. Most countries saw small changes in suicide mortality during the pandemic, while alcohol mortality increased and cancer mortality continued to decline. Patterns for other causes were more variable. By 2022, life expectancy had still not returned to prepandemic levels in several countries. Our results suggest important indirect effects of the pandemic on non-COVID-19 mortality through the consequences of COVID-19 infection, nonpharmaceutical interventions, and underreporting of COVID-19-related deaths.

The COVID-19 pandemic disrupted global economies, social structures, and public health systems. However, Denmark stood out as an exception, maintaining steady life expectancy during this period. This raises important questions about the factors that strengthened the Danish healthcare system and society against the pandemic's challenges.

The Danish healthcare system serves 5.8 million citizens with free care, advanced digital infrastructure, and comprehensive health registers. Under the auspices of the Danish Society for Patient Safety, insights from Denmark's response to COVID-19 were collected from the onset of the pandemic. This paper builds on these collected experiences, covering crucial areas such as strategies to reduce transmission, digitalization, management of non-COVID diseases, tracking adverse events, workplace well-being, development and use of predictive models, and maintaining public trust. Patient-level data on contacts, contact types, and clinical procedures were obtained from health administrative systems and clinical quality registries. All results were reported as raw counts, with no statistical analyses applied.

During COVID-19, Denmark's healthcare system demonstrated resilience by adapting swiftly, achieving a high vaccination rate, shifting to virtual care, enhancing response capacity through real-time adverse event tracking, and supporting healthcare workers through crisis teams minimizing prolonged sick leave. Predictive models accurately forecasted healthcare demands, while public health strategies focused on monitoring public behavior and trust in authorities.

A key lesson from Denmark's handling of COVID-19 is that much of the observed resilience stemmed from pre-existing structures that could be reused, further developed, and expanded. This resilience was further enhanced by an unprecedented readiness for change, cross-sectoral and interdisciplinary collaboration, and the removal of typical barriers. These experiences aim to further improve the quality and resilience of healthcare in Denmark and inspire other countries' healthcare systems. Moving forward, acknowledging chronic conflicts as the new normal, coupled with the reminder that "hope is not a strategy", could serve as a pivotal approach.

We aimed to estimate regional inequalities in excess deaths and premature mortality in Spain during 2020 and 2021, before high vaccination coverage against COVID-19.

With data from the National Institute of Statistics, within each region, sex, and age group, we estimated the excess deaths, the change in life expectancy at birth (e0) and age 65 (e65) and years of life lost as the difference between the observed and expected deaths using a time series analysis of 2015-2019 data and life expectancies based on Lee-Carter forecasting using 2010-2019 data.

From January 2020 to June 2021, an estimated 89,200 (men: 48,000; women: 41,200) excess deaths occurred in Spain with a substantial regional variability (highest in Madrid: 22,000, lowest in Canary Islands: -210). The highest reductions in e0 in 2020 were observed in Madrid (men -3.58 years, women -2.25), Castile-La Mancha (-2.72, -2.38), and Castile and Leon (-2.13, -1.39). During the first half of 2021, the highest reduction in e0 was observed in Madrid for men (-2.09; -2.37 to -1.84) and Valencian Community for women (-1.63; -1.97 to -1.3). The highest excess years of life lost in 2020 was in Castile-La Mancha (men: 5370; women: 3600, per 100 000). We observed large differences between reported COVID-19 deaths and estimated excess deaths across the Spanish regions.

Regions performed highly unequally on excess deaths, life expectancy and years of life lost. The investigation of the root causes of these regional inequalities might inform future pandemic policy in Spain and elsewhere.

By March, 2023, 54 countries, areas, and territories (hereafter CAT) in the WHO European Region had reported more than 2·2 million COVID-19-related deaths to the WHO Regional Office for Europe. Here, we estimated how many lives were directly saved by vaccinating adults in the WHO European Region from December, 2020, to March, 2023.

In this retrospective surveillance study, we estimated the number of lives directly saved by age group, vaccine dose, and circulating variant-of-concern (VOC) period, regionally and nationally, using weekly data on COVID-19 mortality and infection, COVID-19 vaccination uptake, and SARS-CoV-2 virus characterisations by lineage downloaded from The European Surveillance System on June 11, 2023, as well as vaccine effectiveness data from the literature. We included data for six age groups (25-49 years, 50-59 years, ≥60 years, 60-69 years, 70-79 years, and ≥80 years). To be included in the analysis, CAT needed to have reported both COVID-19 vaccination and mortality data for at least one of the four older age groups. Only CAT that reported weekly data for both COVID-19 vaccination and mortality by age group for 90% of study weeks or more in the full study period were included. We calculated the percentage reduction in the number of expected and reported deaths.

Between December, 2020, and March, 2023, in 34 of 54 CAT included in the analysis, COVID-19 vaccines reduced deaths by 59% overall (CAT range 17-82%), representing approximately 1·6 million lives saved (range 1·5-1·7 million) in those aged 25 years or older: 96% of lives saved were aged 60 years or older and 52% were aged 80 years or older; first boosters saved 51% of lives, and 60% were saved during the Omicron period.

Over nearly 2·5 years, most lives saved by COVID-19 vaccination were in older adults by first booster dose and during the Omicron period, reinforcing the importance of up-to-date vaccination among the most at-risk individuals. Further modelling work should evaluate indirect effects of vaccination and public health and social measures.

US Centers for Disease Control and Prevention.

This study examines demographic disparities in COVID-19 exposures across older adults age 60-79 and older adults age 80 and over, and explores the factors driving these dynamics in the United States (U.S.) from January 2020 to July 2022. Spatial clusters were identified, and 14 main health determinants were synthesized from 62 pre-existing county-level variables. The study also assessed the correlation between these health determinants and COVID-19 incidence rates for both age groups during the pandemic years. Further examination of incidence rates in relation to health determinants was carried out through statistical and spatial regression models. Results show that individuals aged 80 and over had much higher hospitalization rates, death rates, and case-fatality rates in 2020-2022. Spatial results indicate that the geographical cluster of high incidence rates for both groups shifted from the Midwest at the beginning of the pandemic to the Southwest in 2022. The study revealed marked spatial, temporal, and demographic nonstationary dynamics in COVID-19 exposures, indicating that the health effects of contextual factors vary across age groups. COVID-19 incidence rates in older adults were strongly influenced by race, healthcare access, social capital, environment, household composition, and mobility. Future public health policies and mitigations should further their efforts by considering temporal and demographic nonstationarity as well as local conditions.

The Nordic countries represent a unique case study for the COVID-19 pandemic due to socioeconomic and cultural similarities, high-quality comparable administrative register data and notable differences in mitigation policies during the pandemic. We aimed to compare weekly excess mortality in the Nordic countries across the three full pandemic years 2020-2022.

Using data on weekly all-cause mortality from official administrative registers in Denmark, Finland, Norway and Sweden, we employed time series regression models to assess mortality developments within each pandemic year, with the period 2010-2019 used as reference period. We then compared excess mortality across the countries in 2020-2022, taking differences in population size and age- and sex-distribution into account. Results were age- and sex-standardized to the Danish population of 2020. Robustness was examined with a variety of sensitivity analyses.

While Sweden experienced excess mortality in 2020 [75 excess deaths per 100 000 population (95% prediction interval 29-122)], Denmark, Finland and Norway experienced excess mortality in 2022 [52 (14-90), 130 (83-177) and 88 (48-128), respectively]. Weekly death data reveal how mortality started to increase in mid-2021 in Denmark, Finland and Norway, and continued above the expected level through 2022.

Although the Nordic countries experienced relatively low pandemic excess mortality, the impact and timing of excess mortality differed substantially. These estimates-arguably the most accurate available for any region in capturing pandemic-related excess deaths-may inform future research and policy regarding the complex mortality dynamics in times of a health crisis such as the COVID-19 pandemic.

Industrial and human activities contribute significantly to the environmental contamination of heavy metal ions (HMIs), which have detrimental effects on aquatic life, plants, and animals, causing major toxicological problems. The commercially available 4,4'-diamino-2,2'-stilbenedisulfonic acid (DSD) has been playing a vital role in the detection of heavy metal ions and has significantly inhibited a variety of cancer cells in numerous field of modern science. The current investigation aimed to ensure the detection of heavy metals ions from the environment and fluorescence imaging of DSD in the treatment of cancer cells. Fluorescence and UV-Visible spectroscopic analysis was performed to sense the selective behavior of the probe DSD with several heavy metal ions, including Fe2+, K1+, Co2+, Ni2+, Zn2+, Cd2+, Pb2+, Mn2+, Sn2+, and Cr3+. Furthermore, DSD was subjected to examine enzyme inhibition such as anti-Alzheimer, anti-inflammatory, antioxidant, anticancer, and antimicrobial activities in search of multifaceted drugs. Test compounds have demonstrated dose-dependent responses in the in-vitro enzyme inhibition assays for acetylcholinesterase (AChE), butyrylcholinesterase (BChE), cyclooxygenase (COX), and lipoxygenase (LOX), as well as antioxidant [DPPH = 2,2-diphenyl-1-picrylhydrazyl and ABTS = 2,2'-azino-bis (3-ethylbenzothiazoline-6-sulfonic acid]. The DSD were shown to be more effective than the conventional medication galantamine in inhibiting acetylcholinesterase (AChE) and butyrylcholinesterase (BChE), with an IC50 value of 12.18 and 20.87 μM, which is equivalent to the standard drug. The results obtained has revealed that DSD has the potential to become an effective sensor for the detection of Sn2+ ions over competing metal ions due to the inhibition of photo-induced electron transfer pathway (PET). The MTT (3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazoliumbromide tetrazolium) test, demonstrated that DSD had strong anticancer effects against the brain cancer cell line NIH/3T3, HeLa and MCF-7 with an IC50 value of 32.59, 15.31 and 96.46 μM respectively. The antimicrobial testing has shown that DSD outperforms the standard drug cefixime against Candida albicans and Pseudomonas aeruginosa, respectively. This study makes a substantial contribution to the ongoing search for efficient treatments for breast cancer.

Keyfitz and Leser's life table entropy was proposed to serve as a relative inequality in mortality measure. Entropy considers the variation around the age at death relative to the length of lifespan in a population, allowing comparisons across time and populations. It is used widely in period and cohort applications. Here, we propose extending this measure and present an index that incorporates the history of survival of all cohorts present at a given time, namely the cross-sectional average length of life entropy, or CAL-entropy ( H CAL ). We decompose cross-population differences of CAL-entropy into the contribution of longevity and lifespan variation, and the change of those differences across time. Our illustrations show that populations are converging regarding lifespan inequality. Lifespan variation holds a noticeable share in the CAL-entropy gap among selected European populations. Longevity held once a pronounced share in CAL-entropy differences and their change, but its influence has receded over the years. The US demonstrates a unique trend where it performs worse across time compared to the selected European populations, and lifespan variation has played a major role in this process. This study signals the importance of lifespan variation in reducing inequality in mortality among developed and longevous populations.

Global population health during the COVID-19 pandemic is poorly understood because of weak mortality monitoring in low- and middle-income countries. High-quality survey data on 765,180 individuals, representative of one-fourth of India's population, uncover patterns missed by incomplete vital statistics and disease surveillance. Compared to 2019, life expectancy at birth was 2.6 years lower and mortality was 17% higher in 2020, implying 1.19 million excess deaths in 2020. Life expectancy declines in India were larger and had a younger age profile than in high-income countries. Increases in mortality were greater than expected based on observed seroprevalence and international infection fatality rates, most prominently among the youngest and older age groups. In contrast to global patterns, females in India experienced a life expectancy decline that was 1 year larger than losses for males. Marginalized social groups experienced greater declines than the most privileged social group. These findings uncover large and unequal mortality impacts during the pandemic in the world's most populous country.

To measure the burden of the COVID-19 pandemic in 2020 at the subnational level by estimating excess mortality, defined as the increase in all-cause mortality relative to an expected baseline mortality level.

Statistical and demographic analyses of regional all-cause mortality data provided by the vital statistics systems of 21 European countries for 561 regions in Central and Western Europe. Life expectancy losses at ages 0 and 60 for males and females were estimated.

We found evidence of a loss in life expectancy in 391 regions, whilst only three regions exhibit notable gains in life expectancy in 2020. For 12 regions, losses of life expectancy amounted to more than 2 years and three regions showed losses greater than 3 years. We highlight geographical clusters of high mortality in Northern Italy, Spain and Poland, whilst clusters of low mortality were found in Western France, Germany/Denmark and Norway/Sweden.

Regional differences of loss of life expectancy are impressive, ranging from a loss of more than 4 years to a gain of 8 months. These findings provide a strong rationale for regional analysis, as national estimates hide significant regional disparities.

Background: Long COVID, characterized by a persistent symptom spectrum following SARS-CoV-2 infection, poses significant health, social, and economic challenges. This review aims to consolidate knowledge on its epidemiology, clinical features, and underlying mechanisms to guide global responses; Methods: We conducted a literature review, analyzing peer-reviewed articles and reports to gather comprehensive data on long COVID's epidemiology, symptomatology, and management approaches; Results: Our analysis revealed a wide array of long COVID symptoms and risk factors, with notable demographic variability. The current understanding of its pathophysiology suggests a multifactorial origin yet remains partially understood. Emerging diagnostic criteria and potential therapeutic strategies were identified, highlighting advancements in long COVID management; Conclusions: This review highlights the multifaceted nature of long COVID, revealing a broad spectrum of symptoms, diverse risk factors, and the complex interplay of physiological mechanisms underpinning the condition. Long COVID symptoms and disorders will continue to weigh on healthcare systems in years to come. Addressing long COVID requires a holistic management strategy that integrates clinical care, social support, and policy initiatives. The findings underscore the need for increased international cooperation in research and health planning to address the complex challenges of long COVID. There is a call for continued refinement of diagnostic and treatment modalities, emphasizing a multidisciplinary approach to manage the ongoing and evolving impacts of the condition.

This article shows the direct and indirect impacts of COVID-19 on life expectancy in Chile in 2020, based on mortality statistics published in March 2023. To this end, a counterfactual mortality was estimated for 2020 without COVID-19; based on the pattern of mortality by cause of death from 1997 to 2019, mortality charts were created to calculate life expectancy from 2015 to 2020 and an estimation for 2020, and the difference between expected and observed life expectancy in 2020 was then separated by age group and cause of death. Life expectancy in 2020 interrupted the upward trend from 2015 to 2019, showing a decline of 1.32 years in men and 0.75 years in women compared to 2019. Compared to the estimated 2020, life expectancy was 1.51 years lower in men and 0.92 years lower in women, but the direct impact of COVID-19 on the decrease in life expectancy was greater (1.89 for men and 1.5 for women) in the 60-84 age group in men and the 60-89 age group in women. The direct negative impact of COVID-19 on life expectancy was partially mitigated by significant positive indirect impacts on two groups of causes of death: diseases of the respiratory system and infectious and parasitic diseases. This study shows the need to differentiate direct and indirect impacts of COVID-19, due to the implications for public health when the intensity of COVID-19 decreases and mobility restrictions are suspended.

Since its emergence in December 2019, the COVID-19 pandemic has resulted in a significant increase in deaths worldwide. This article presents a detailed analysis of the mortality burden of the COVID-19 pandemic across 569 regions in 25 European countries. We produce age and sex-specific excess mortality and present our results using Age-Standardised Years of Life Lost in 2020 and 2021, as well as the cumulative impact over the two pandemic years. Employing a forecasting approach based on CP-splines that considers regional diversity and provides confidence intervals, we find notable losses in 362 regions in 2020 (440 regions in 2021). Conversely, only seven regions experienced gains in 2020 (four regions in 2021). We also estimate that eight regions suffered losses exceeding 20 years of life per 1000 population in 2020, whereas this number increased to 75 regions in 2021. The contiguity of the regions investigated in our study also reveals the changing geographical patterns of the pandemic. While the highest excess mortality values were concentrated in the early COVID-19 outbreak areas during the initial pandemic year, a clear East-West gradient appeared in 2021, with regions of Slovakia, Hungary, and Latvia experiencing the highest losses. This research underscores the importance of regional analyses for a nuanced comprehension of the pandemic's impact.

Determining 'excess mortality' makes it possible to compare the burden of disasters between countries and over time, and thus also to evaluate the success of mitigation measures. However, the debate on coronavirus disease 2019 (Covid-19) has exposed that calculations of excess mortalities vary considerably depending on the method and its specification. Moreover, it is often unclear what exactly is meant by 'excess mortality'. We define excess mortality as the excess over the number of deaths that would have been expected counter-factually, that is without the catastrophic event in question. Based on this definition, we use a very parsimonious calculation method, namely the linear extrapolation of death figures from previous years to determine the excess mortality during the Covid-19 pandemic. But unlike most other literature on this topic, we first evaluated and optimized the specification of our method using a larger historical data set in order to identify and minimize estimation errors and biases. The result shows that excess mortality rates in the literature are often inflated. Moreover, they would have exhibited considerable excess mortalities in the period before Covid-19, if this value had already been of public interest at that time. Three conclusions can be drawn from this study and its findings: (i) All calculation methods for current figures should first be evaluated against past figures. (ii) To avoid alarm fatigue, thresholds should be introduced which would differentiate between 'usual fluctuations' and 'remarkable excess'. (iii) Statistical offices could provide more realistic estimates.

Earlier death among people in socioeconomically deprived circumstances has been found internationally and for various causes of death, resulting in a considerable life-expectancy gap between socioeconomic groups. We examined how age-specific and cause-specific mortality contributions to the socioeconomic gap in life expectancy have changed at the area level in Germany over time.

In this ecological study, official German population and cause-of-death statistics provided by the Federal Statistical Office of Germany for the period Jan 1, 2003, to Dec 31, 2021, were linked to district-level data of the German Index of Socioeconomic Deprivation. Life-table and decomposition methods were applied to calculate life expectancy by area-level deprivation quintile and decompose the life-expectancy gap between the most and least deprived quintiles into age-specific and cause-specific mortality contributions.

Over the study period, population numbers varied between 80 million and 83 million people per year, with the number of deaths ranging from 818 000 to 1 024 000, covering the entire German population. Between Jan 1, 2003, and Dec 31, 2019, the gap in life expectancy between the most and least deprived quintiles of districts increased by 0·7 years among females (from 1·1 to 1·8 years) and by 0·1 years among males (from 3·0 to 3·1 years). Thereafter, during the COVID-19 pandemic, the gap increased more rapidly to 2·2 years in females and 3·5 years in males in 2021. Between 2003 and 2021, the causes of death that contributed the most to the life-expectancy gap were cardiovascular diseases and cancer, with declining contributions of cardiovascular disease deaths among those aged 70 years and older and increasing contributions of cancer deaths among those aged 40-74 years over this period. COVID-19 mortality among individuals aged 45 years and older was the strongest contributor to the increase in life-expectancy gap after 2019.

To reduce the socioeconomic gap in life expectancy, effective efforts are needed to prevent early deaths from cardiovascular disease and cancer in socioeconomically deprived populations, with cancer prevention and control becoming an increasingly important field of action in this respect.

German Cancer Aid and European Research Council.

Over half of Australia's disease burden is due to morbidity, predominantly chronic conditions. Health-related quality of life instruments provide measures of morbidity and health status across different dimensions with EQ-5D being one of the most widely used. This study reports EQ-5D-5L general population norms for Queensland, Australia using the recently published Australian value set.

Population survey results from cross-sectional computer-assisted telephone interviews for Queensland adults in 2022 and 2023 were analyzed. EQ-5D-5L, as well as modifiable risk factors and sociodemographic data were collected. Using the recently published final Australian EQ-5D-5L value set, mean utility scores were calculated for Queensland, as well as by sociodemographic characteristics, including remoteness and socioeconomic area-based measures, and modifiable risk factors, such as smoking and body mass index. Results were combined with life tables to estimate quality-adjusted life expectancy (QALE) for subgroups with different lifestyles.

The EQ-5D utility score for the Queensland adult population was 0.916. Smoking daily, being obese or older in age, or living in the most disadvantaged socioeconomic area were associated with lower mean scores. QALE was 6.1 and 7.9 years shorter than the life expectancy for Queensland males and females, respectively, but generally, those who reported having healthier lifestyles had higher mean utility scores and thus longer QALE.

In addition to reporting Queensland EQ-5D-5L general population norms, these results demonstrate potential QALE gains in people following healthier lifestyles. The results support investment in prevention and may motivate further studies in this important area.

To examine the impact of the COVID-19 pandemic on mortality, we estimated excess all-cause mortality in 24 countries for 2020 and 2021, overall and stratified by sex and age.

Total, age-specific and sex-specific weekly all-cause mortality was collected for 2015-2021 and excess mortality for 2020 and 2021 was calculated by comparing weekly 2020 and 2021 age-standardised mortality rates against expected mortality, estimated based on historical data (2015-2019), accounting for seasonality, and long-term and short-term trends. Age-specific weekly excess mortality was similarly calculated using crude mortality rates. The association of country and pandemic-related variables with excess mortality was investigated using simple and multilevel regression models.

Excess cumulative mortality for both 2020 and 2021 was found in Austria, Brazil, Belgium, Cyprus, England and Wales, Estonia, France, Georgia, Greece, Israel, Italy, Kazakhstan, Mauritius, Northern Ireland, Norway, Peru, Poland, Slovenia, Spain, Sweden, Ukraine, and the USA. Australia and Denmark experienced excess mortality only in 2021. Mauritius demonstrated a statistically significant decrease in all-cause mortality during both years. Weekly incidence of COVID-19 was significantly positively associated with excess mortality for both years, but the positive association was attenuated in 2021 as percentage of the population fully vaccinated increased. Stringency index of control measures was positively and negatively associated with excess mortality in 2020 and 2021, respectively.

This study provides evidence of substantial excess mortality in most countries investigated during the first 2 years of the pandemic and suggests that COVID-19 incidence, stringency of control measures and vaccination rates interacted in determining the magnitude of excess mortality.