Excess Deaths in Korea During the COVID-19 Pandemic: 2020-2022.

OBJECTIVES: Excess deaths, an indicator that compares total mortality rates before and during a pandemic, offer a comprehensive view of the pandemic's impact. However, discrepancies may arise from variations in estimating expected deaths. This study aims to compare excess deaths in Korea during the coronavirus disease 2019 pandemic using 3 methods and to analyze patterns using the most appropriate method. METHODS: Expected deaths from 2020 to 2022 were estimated using mortality data from 2015-2019 as reference years. This estimation employed 3 approaches: (1) simple average, (2) age-adjusted average, and (3) age-adjusted linear regression. Excess deaths by age, gender, and cause of death were also presented. RESULTS: The number of excess deaths varied depending on the estimation method used, reaching its highest point with the simple average and its lowest with the age-adjusted average. Age-adjusted linear regression, which accounts for both the aging population and declining mortality rates, was considered most appropriate. Using this model, excess deaths were estimated at 0.3% for 2020, 4.0% for 2021, and 20.7% for 2022. Excess deaths surged among individuals in their 20s throughout the pandemic, largely attributed to a rise in self-harm and suicide. Additionally, the results indicated sharp increases in deaths associated with "endocrine, nutritional, and metabolic diseases" and "symptoms, signs, and abnormal clinical and laboratory findings, not elsewhere classified." CONCLUSIONS: Substantial variations in excess deaths were evident based on estimation method, with a notable increase in 2022. The heightened excess deaths among young adults and specific causes underscore key considerations for future pandemic responses.

Understanding excess mortality in 2022: The dual impact of COVID-19 and heatwaves on the Italian elderly population.

In this study, we employ a comprehensive approach to model the concurrent effects of the COVID-19 epidemic and heatwaves on all-cause excess mortality. Our investigation uncovers distinct peaks in excess mortality, notably among individuals aged 80 years and older, revealing a strong positive correlation with excess temperatures (ET) during the summer of 2022 in Italy. Furthermore, we identify a notable role played by COVID-19 hospitalizations, exhibiting regional disparities, particularly during the winter months. Leveraging functional data regression, we offer robust and coherent insights into the excess mortality trends observed in Italy throughout 2022.

Population age structure dependency of the excess mortality P-score.

BACKGROUND: Since the outbreak of the COVID-19 pandemic, the excess mortality P-score has gained prominence as a measure of pandemic burden. The P-score indicates the percentage by which observed deaths deviate from expected deaths. As the P-score is regularly used to compare excess mortality between countries, questions arise regarding the age dependency of the measure. In this paper we present formal and empirical results on the population structure bias of the P-score with a special focus on cross-country comparisons during the COVID-19 pandemic in Europe. METHODS: P-scores were calculated for European countries for 2021, 2022, and 2023 using data from the 2024 revision of the United Nations' World Population Prospects and the HMDs Short Term Mortality Fluctuations data series. The expected deaths for 2021, 2022, and 2023 were estimated using a Lee-Carter forecast model assuming pre-pandemic conditions. P-score differences between countries were decomposed using a Kitagawa-type decomposition into excess-mortality and structural components. To investigate the sensitivity of P-score cross-country rankings to differences in population structure we calculated the rank-correlation between age-standardized and classical P-scores. RESULTS: The P-score is an average of age-specific percent excess deaths weighted by the age-distribution of expected deaths. It can be shown that the effect of differences in the distribution of deaths only plays a marginal role in a European comparison. In most cases, the excess mortality effect is the dominant effect. P-score rankings among European countries during the COVID-19 pandemic are similar under both age-standardized and classical P-scores. CONCLUSIONS: Although the P-score formally depends on the age-distribution of expected deaths, this structural component only plays a minor role in a European comparison, as the distribution of deaths across the continent is similar. Thus, the P-score is suitable as a measure of excess mortality in a European comparison, as it mainly reflects the differences in excess mortality. However, this finding should not be extrapolated to global comparisons, where countries could have very different death distributions. In situations were P-score comparisons are biased age-standardization can be applied as a solution.

An assessment of excess mortality during the COVID-19 pandemic, a retrospective post-mortem surveillance in 12 districts - Zambia, 2020-2022.

BACKGROUND: The number of COVID-19 deaths reported in Zambia (N = 4069) is most likely an underestimate due to limited testing, incomplete death registration and inability to account for indirect deaths due to socioeconomic disruption during the pandemic. We sought to assess excess mortality during the COVID-19 pandemic in Zambia. METHODS: We conducted a retrospective analysis of monthly-death-counts (2017-2022) and individual-daily-deaths (2020-2022) of all reported health facility and community deaths at district referral health facility mortuaries in 12 districts in Zambia. We defined COVID-19 wave periods based on a sustained nationally reported SARS-CoV-2 test positivity of greater than 5%. Excess mortality was calculated as the difference between observed monthly death counts during the pandemic (2020-2022) and the median monthly death counts from the pre-pandemic period (2017-2019), which served as the expected number of deaths. This calculation was conducted using a Microsoft Excel-based tool. We compared median daily death counts, median age at death, and the proportion of deaths by place of death (health facility vs. community) by wave period using the Mann-Whitney-U test and chi-square test respectively in R. RESULTS: A total of 112,768 deaths were reported in the 12 districts between 2020 and 2022, of which 17,111 (15.2%) were excess. Wave periods had higher median daily death counts than non-wave periods (median [IQR], 107 [95-126] versus 96 [85-107], p < 0.001). The median age at death during wave periods was older than non-wave periods (44.0 [25.0-67.0] versus 41.0 [22.0-63.0] years, p < 0.001). Approximately half of all reported deaths occurred in the community, with an even greater proportion during wave periods (50.6% versus 53.1%, p < 0.001), respectively. CONCLUSION: There was excess mortality during the COVID-19 pandemic in Zambia, with more deaths occurring within the community during wave periods. This analysis suggests more COVID-19 deaths likely occurred in Zambia than suggested by officially reported numbers. Mortality surveillance can provide important information to monitor population health and inform public health programming during pandemics.

Impact of organized and opportunistic screening on excess mortality and on social inequalities in breast cancer survival.

In most developed countries, both organized screening (OrgS) and opportunistic screening (OppS) coexist. The literature has extensively covered the impact of organized screening on women's survival after breast cancer. However, the impact of opportunistic screening has been less frequently described due to the challenge of identifying the target population. The aim of this study was to describe the net survival and excess mortality hazard (EMH) in each screening group (OrgS, OppS, or No screening) and to determine whether there is an identical social gradient in each groups. Three data sources (cancer registry, screening coordination centers, and National Health Data System [NHDS]) were used to identify the three screening groups. The European Deprivation Index (EDI) defined the level of deprivation. We modeled excess breast cancer mortality hazard and net survival using penalized flexible models. We observed a higher EMH for "No screening" women compared with the other two groups, regardless of level of deprivation and age at diagnosis. A social gradient appeared for each group at different follow-up times and particularly between 2 and 3 years of follow-up for "OrgS" and "OppS" women. Net survival was higher for "OrgS" women than "OppS" women, especially for the oldest women, and regardless of the deprivation level. This study provides new evidence of the impact of OrgS on net survival and excess mortality hazard after breast cancer, compared with opportunistic screening or no screening, and tends to show that OrgS attenuates the social gradient effect.

Influenza-Associated Excess Mortality and Hospitalization in Germany from 1996 to 2018.

INTRODUCTION: Influenza-associated excess mortality and morbidity is commonly estimated using statistical methods. In Germany, the Robert Koch Institute (RKI) uses the relative mortality distribution method (RMDM) to estimate influenza-associated excess mortality without reporting age-specific values. In order to better differentiate the distribution of the disease burden, a distinction by age is of high relevance. Therefore, we aimed to revise the existing excess mortality model and provide age-specific excess mortality estimates over multiple seasons. We also used the model to determine influenza-associated excess hospitalizations, since the RKI excess hospitalization model is currently based on another approach (i.e., combination of excess physician visits and hospitalized proportion). METHODS: This study was a retrospective data analysis based on secondary data of the German population from 1996-2018. We adapted the RKI's method of estimating influenza-associated excess mortality with the RMDM and also applied this approach to excess hospitalizations. We calculated the number of excess deaths/hospitalizations using weekly and age-specific data. RESULTS: Data available in Germany are suitable for addressing the restrictions of the RKI's mortality model. In total, we estimated 175,858 (176,482 with age stratification) influenza-associated excess all cause deaths between 1995-1996 and 2017-2018 ranging from 0 (17 with age stratification) in 2005-2006 to 25,599 (25,527 with age stratification) in 2017-2018. Total influenza-associated excess deaths were comparable to RKI's estimates in most seasons. Most excess deaths/hospitalizations occurred in patients aged ≥ 60 years (95.42%/57.49%) followed by those aged 35-59 years (3,80%/24,98%). Compared with our model, the RKI hospitalization model implies a substantial underestimation of excess hospitalizations (828,090 vs. 374,200 over all seasons). CONCLUSION: This is the first study that provides age-specific estimates of influenza-associated excess mortality in Germany. The results clearly show that the main burden of influenza is in the elderly, for whom prevention and control measures should be prioritized.

Age-specific all-cause mortality trends in the UK: Pre-pandemic increases and the complex impact of COVID-19.

OBJECTIVES: This study aims to analyse age-specific all-cause mortality trends in the UK before and after COVID-19 emergence to determine if pre-pandemic trends contributed to increased mortality levels in the post-pandemic era. STUDY DESIGN: Statistical analysis of UK mortality data. METHODS: We utilised age-structured population and mortality data for all UK countries from 2005 to 2023. Mortality rates were calculated for each age group, and excess mortality was estimated using the Office for National Statistics (ONS) method. RESULTS: Our most concerning finding is an increase in all-cause mortality rates for middle-aged adults (30-54 years) starting around 2012. The COVID-19 pandemic may have further impacted these rates, but the pre-existing upward trend suggests that current elevated mortality rates might have been reached regardless of the pandemic. This finding is more alarming than the slowdown in the decline of cardiovascular disease death rates for individuals under 75 noted by the British Heart Foundation. CONCLUSION: Our results highlight the importance of considering both immediate pandemic impacts and long-term mortality trends in public health strategies. This underscores the need for targeted interventions and improved healthcare planning to address both ongoing and future challenges.

Cause-specific excess mortality in Denmark, Finland, Norway, and Sweden during the COVID-19 pandemic 2020-2022: a study using nationwide population data.

While there is substantial evidence on excess mortality in the first two years of the COVID-19 pandemic, no study has conducted a cause-specific analysis of excess mortality for the whole period 2020-2022 across multiple countries. We examined cause-specific excess mortality during 2020-2022 in Denmark, Finland, Norway, and Sweden-four countries with similar demographics and welfare provisions, which implemented different pandemic response policies. To this end, we utilized nationwide register-based information on annual cause-specific deaths stratified by age and sex, and applied linear regression models to predict mortality in 2020-2022 based on the reference period 2010-2019. Excess deaths were obtained by contrasting actual and expected deaths. Additional analyses employed standardization to a common population, as well as population adjustments to account for previous deaths. Our results showed that, besides deaths due to COVID-19 (a total of 32,491 during 2020-2022), all countries experienced excess deaths due to cardiovascular diseases (in total 11,610 excess deaths), and under-mortality due to respiratory diseases other than COVID-19 (in total 9878) and dementia (in total 8721). The excess mortality due to cardiovascular diseases was particularly pronounced in Finland and Norway in 2022, and the under-mortality due to dementia was particularly pronounced in Sweden in 2021-2022. In conclusion, while COVID-19 deaths emerge as the most apparent consequence of the pandemic, our findings suggest that mortality has also been influenced by substitutions between different causes of death and over time, as well as indirect consequences of COVID-19 infection and pandemic responses-albeit to different extents in the different countries.

[Excess deaths in Argentina during the COVID-19 pandemic: analysis of mortality between 2020 and 2022]. / Exceso de muertes en Argentina durante la pandemia por COVID-19: análisis de la mortalidad entre 2020 y 2022.

Reports of excess mortality during the COVID-19 pandemic in Argentina have been partial and fragmented so far. This study aimed to quantify excess deaths and explore their demographic, temporal, and geographic distribution during the period 2020-2022. Using data from 1 192 963 death records from vital statistics and population projections, expected mortality was estimated using regression models. Excess death was calculated as the difference between observed and expected mortality. An excess of 160 676 deaths (95% CI 146 861 to 174 491) was estimated, representing a rate of 116.9 (95% CI 115.5 to 118.3) additional deaths per 100 000 personyears. Significant heterogeneity was found among the different argentine provinces. The results indicate an uneven impact of the pandemic, with higher excess mortality rates in some regions and more vulnerable age groups. These patterns suggest the need for differentiated strategies of healthcare response and support to the most vulnerable populations in scenarios of new epidemics.

Los reportes del exceso de mortalidad durante la pandemia por COVID-19 en Argentina han sido parciales y fragmentados hasta el momento. Este estudio se propuso cuantificar el exceso de muertes y explorar su distribución demográfica, temporal y geográfica durante el periodo 2020-2022. Utilizando datos de 1 192 963 registros de muertes de estadísticas vitales y proyecciones poblacionales, se estimó la mortalidad esperada mediante modelos de regresión. El exceso de muertes se calculó como la diferencia entre la mortalidad observada y la esperada. Se estimó un exceso de 160 676 muertes (IC 95% 146 861 a 174 491), representando una tasa de 116.9 muertes (IC 95% 115.5 a 118.3) adicionales por cada 100 000 personas-año. Se verificó una significativa heterogeneidad entre las distintas provincias argentinas. Los resultados indican un impacto desigual de la pandemia, con mayores tasas de exceso de mortalidad en algunas regiones y grupos de edad más vulnerables. Estos patrones sugieren la necesidad de estrategias diferenciadas de respuesta sanitaria y apoyo a las poblaciones más vulnerables en escenarios de nuevas epidemias.

Access to primary care and mortality in excess for patients with cancer in France: Results from 21 French Cancer Registries.

BACKGROUND: The impact of geographical accessibility on cancer survival has been investigated in few studies, with most research focusing on access to reference care centers, using overall mortality and limited to specific cancer sites. This study aims to examine the association of access to primary care with mortality in excess of patients with the 10 most frequent cancers in France, while controlling for socioeconomic deprivation. METHODS: This study included a total of 151,984 cases diagnosed with the 10 most common cancer sites in 21 French cancer registries between 2013 and 2015. Access to primary care was estimated using two indexes: the Accessibilité Potentielle Localisée index (access to general practitioners) and the Scale index (access to a range of primary care clinicians). Mortality in excess was modelized using an additive framework based on expected mortality based on lifetables and observed mortality. FINDINGS: Patients living in areas with less access to primary care had a greater mortality in excess for some very common cancer sites like breast (women), lung (men), liver (men and women), and colorectal cancer (men), representing 46% of patients diagnosed in our sample. The maximum effect was found for breast cancer; the excess hazard ratio was estimated to be 1.69 (95% CI, 1.20-2.38) 1 year after diagnosis and 2.26 (95% CI, 1.07-4.80) 5 years after diagnosis. INTERPRETATION: This study revealed that this differential access to primary care was associated with mortality in excess for patients with cancer and should become a priority for health policymakers to reduce these inequalities in health care accessibility.

Trends in diabetic ketoacidosis- and hyperosmolar hyperglycemic state-related mortality during the COVID-19 pandemic in the United States: A population-based study.

BACKGROUND: During the pandemic, a notable increase in diabetic ketoacidosis (DKA) and hyperosmolar hyperglycemic state (HHS), conditions that warrant emergent management, was reported. We aimed to investigate the trend of DKA- and HHS-related mortality and excess deaths during the pandemic. METHODS: Annual age-standardized mortality rates related to DKA and HHS between 2006 and 2021 were estimated using a nationwide database. Forecast analyses based on prepandemic data were conducted to predict the mortality rates during the pandemic. Excess mortality rates were calculated by comparing the observed versus predicted mortality rates. Subgroup analyses of demographic factors were performed. RESULTS: There were 71 575 DKA-related deaths and 8618 HHS-related deaths documented during 2006-2021. DKA, which showed a steady increase before the pandemic, demonstrated a pronounced excess mortality during the pandemic (36.91% in 2020 and 46.58% in 2021) with an annual percentage change (APC) of 29.4% (95% CI: 16.0%-44.0%). Although HHS incurred a downward trend during 2006-2019, the excess deaths in 2020 (40.60%) and 2021 (56.64%) were profound. Pediatric decedents exhibited the highest excess mortality. More than half of the excess deaths due to DKA were coronavirus disease 2019 (COVID-19) related (51.3% in 2020 and 63.4% in 2021), whereas only less than a quarter of excess deaths due to HHS were COVID-19 related. A widened racial/ethnic disparity was observed, and females exhibited higher excess mortality than males. CONCLUSIONS: The DKA- and HHS-related excess mortality during the pandemic and relevant disparities emphasize the urgent need for targeted strategies to mitigate the escalated risk in these populations during public health crises.

Disentangling the relationship between cancer mortality and COVID-19 in the US.

Cancer is considered a risk factor for COVID-19 mortality, yet several countries have reported that deaths with a primary code of cancer remained within historic levels during the COVID-19 pandemic. Here, we further elucidate the relationship between cancer mortality and COVID-19 on a population level in the US. We compared pandemic-related mortality patterns from underlying and multiple cause (MC) death data for six types of cancer, diabetes, and Alzheimer's. Any pandemic-related changes in coding practices should be eliminated by study of MC data. Nationally in 2020, MC cancer mortality rose by only 3% over a pre-pandemic baseline, corresponding to ~13,600 excess deaths. Mortality elevation was measurably higher for less deadly cancers (breast, colorectal, and hematological, 2-7%) than cancers with a poor survival rate (lung and pancreatic, 0-1%). In comparison, there was substantial elevation in MC deaths from diabetes (37%) and Alzheimer's (19%). To understand these differences, we simulated the expected excess mortality for each condition using COVID-19 attack rates, life expectancy, population size, and mean age of individuals living with each condition. We find that the observed mortality differences are primarily explained by differences in life expectancy, with the risk of death from deadly cancers outcompeting the risk of death from COVID-19.

Establishing the true death toll of a pandemic like COVID-19 is difficult, as laboratory testing is generally too limited to directly count the number of deaths that can be attributed to a particular pathogen. To overcome this, researchers analyse excess mortality ­ that is, they compare the observed number of deaths with the expected level based on trends in prior years. These techniques have been used for over 100 years to estimate the burden of pandemic influenza and became a popular way to estimate deaths due to the COVID-19 pandemic. Excess mortality can also reveal the impact of COVID-19 on sub-populations with chronic conditions. For example, previous studies showed that deaths with diabetes, heart disease and Alzheimer's disease listed as the primary cause of death increased during waves of COVID-19. Cancer deaths did not show such a pattern, however, despite some epidemiological studies identifying cancer as a risk factor for COVID-19 mortality. To understand why this may be the case, Hansen et al. reviewed death certificates from different states in the United States during the first year of the pandemic. Their analyses of multiple-cause death records (listing cancer anywhere on the death certificate, not just as the primary cause of death) showed that death certificate coding practices during the pandemic did not explain the absence of excess cancer mortality. While a low level of excess mortality was detectable for cancers with longer life expectancy (breast cancer, for example), no elevation was observed for cancers with lower life expectancy, such as pancreatic cancer. The analyses demonstrate that the lack of excess mortality for especially deadly cancers can be explained through competing risks ­ in other words, the high risk of dying from the cancer itself vastly outweighs the additional risk posed by COVID-19. These findings shed light on how competing mortality risks might mask the true impact of COVID-19 on cancer mortality and explain the apparent discrepancy between cohort studies and excess mortality studies. To fully comprehend the impact of COVID-19 on patients living with cancers, future research should look at the possibility of longer-term increases in cancer mortality due to late diagnosis during pandemic lockdowns, and an elevated risk of severe illness.

Regional inequalities in excess mortality and its community determinants during the early COVID-19 pandemic in South Korea.

BACKGROUND: Excess mortality during the COVID-19 pandemic provides a comprehensive measure of disease burden, and its local variation highlights regional health inequalities. We investigated local excess mortality in 2020 and its determinants at the community level. METHODS: We collected data from 250 districts in South Korea, including monthly all-cause mortality for 2015-2020 and community characteristics from 2019. Excess mortality rate was defined as the difference between observed and expected mortality rates. A Seasonal Autoregressive Integrated Moving Average model was applied to predict the expected rates for each district. Penalized regression methods were used to derive relevant community predictors of excess mortality based on the elastic net. RESULTS: In 2020, South Korea exhibited significant variation in excess mortality rates across 250 districts, ranging from no excess deaths in 46 districts to more than 100 excess deaths per 100 000 residents in 30 districts. Economic status or the number of medical centres in the community did not correlate with excess mortality rates. The risk was higher in ageing, remote communities with limited cultural and sports infrastructure, a higher density of welfare facilities, and a higher prevalence of hypertension. Physical distancing policies and active social engagement in voluntary activities protected from excess mortality. CONCLUSION: Substantial regional disparities in excess mortality existed within South Korea during the early stages of COVID-19 pandemic. Weaker segments of the community were more vulnerable. Local governments should refine their preparedness for future novel infectious disease outbreaks, considering community circumstances.

Gender-Based Socio-Economic Inequalities in the Pre-Vaccination Era of the COVID-19 Pandemic in Istanbul: A Neighborhood-Level Analysis of Excess Mortality.

Worldwide excess mortality (EM) data have the potential to provide a better estimation of the impact of the pandemic. This study aims to investigate and map the inequalities in EM in Istanbul during the pre-vaccination era of the COVID-19 pandemic in 2020 and its association with selected demographic and socio-economic variables at the neighborhood level according to gender. This ecological study was conducted with the EM data of Istanbul. The EM data were obtained from the Istanbul Metropolitan Municipality (IMM) and analyzed according to socio-demographic indicators (gender, age), neighborhood-level indicators (population density, educational attainment) and neighborhood vulnerability (socio-economic and transportation) for the 808 neighborhoods, then presented separately according to gender to examine gender-specific factors. Socio-economic and transportation vulnerability indexes are provided the IMM. The excess mortality rate per 1000 (EMR) in 2020 has been calculated by using the number of deaths in the years 2018-2019. We have mapped EMRs of each neighborhood and used linear regression analysis in three datasets to examine gender specific factors. EMRs in Istanbul showed two peaks one in April and one in November. Male EMRs were higher compared to females in Istanbul during the pre-vaccination era of the pandemic. Higher EMRs were observed in neighborhoods with a higher share of 50+ year old age groups and higher neighborhood socio-economic vulnerability scores. Neighborhood socio-economic vulnerability was significantly associated with EMRs in males but not in females. Unequal distribution of EM between neighborhoods underlines the need for gender-specific pandemic measures to alleviate the burden of the COVID-19 pandemic, especially in socio-economically vulnerable settings. Increased use of area-based indicators with a gender perspective can enhance pandemic measures.

Sex disparities of the effect of the COVID-19 pandemic on mortality among patients living with tuberculosis in the United States.

Background: We aimed to determine the trend of TB-related deaths during the COVID-19 pandemic. Methods: TB-related mortality data of decedents aged ≥25 years from 2006 to 2021 were analyzed. Excess deaths were estimated by determining the difference between observed and projected mortality rates during the pandemic. Results: A total of 18,628 TB-related deaths were documented from 2006 to 2021. TB-related age-standardized mortality rates (ASMRs) were 0.51 in 2020 and 0.52 in 2021, corresponding to an excess mortality of 10.22 and 9.19%, respectively. Female patients with TB demonstrated a higher relative increase in mortality (26.33 vs. 2.17% in 2020; 21.48 vs. 3.23% in 2021) when compared to male. Female aged 45-64 years old showed a surge in mortality, with an annual percent change (APC) of -2.2% pre-pandemic to 22.8% (95% CI: -1.7 to 68.7%) during the pandemic, corresponding to excess mortalities of 62.165 and 99.16% in 2020 and 2021, respectively; these excess mortality rates were higher than those observed in the overall female population ages 45-64 years in 2020 (17.53%) and 2021 (33.79%). Conclusion: The steady decline in TB-related mortality in the United States has been reversed by COVID-19. Female with TB were disproportionately affected by the pandemic.

Years of Life Lost to COVID-19 and Related Mortality Indicators: An Illustration in 30 Countries.

The concept of (potential) years of life lost is a measure of premature mortality that can be used to compare the impacts of different specific causes of death. However, interpreting a given number of years of life lost at face value is more problematic because of the lack of a sensible reference value. In this paper, we propose three denominators to divide an excess years of life lost, thus obtaining three indicators, called average life lost, increase of life lost, and proportion of life lost, which should facilitate interpretation and comparisons. We study the links between these three indicators and classical mortality indicators, such as life expectancy and standardized mortality rate, introduce the concept of weighted standardized mortality rate, and calculate them in 30 countries to assess the impact of COVID-19 on mortality in the year 2020. Using any of the three indicators, a significant excess loss is found for both genders in 18 of the 30 countries.

Variation in Excess Mortality Across Nursing Homes in the Netherlands During the COVID-19 Pandemic.

OBJECTIVES: Nursing home residents constituted a vulnerable population during the COVID-19 pandemic, and half of all cause-attributed COVID-19 deaths occurred within nursing homes. Yet, given the low life expectancy of nursing home residents, it is unclear to what extent COVID-19 mortality increased overall mortality within this population. Moreover, there might have been differences between nursing homes in their ability to protect residents against excess mortality. This article estimates the number of excess deaths among Dutch nursing home residents during the pandemic, the variation in excess deaths across nursing homes, and its relationship with nursing home characteristics. DESIGN: Retrospective, use of administrative register data. SETTING AND PARTICIPANTS: All residents (N = 194,432) of Dutch nursing homes (n = 1463) in 2016-2021. METHODS: We estimated the difference between actual and predicted mortality, pooled at the nursing home level, which provided an estimate of nursing home-specific excess mortality corrected for resident case-mix differences. We show the variation in excess mortality across nursing homes and relate this to nursing home characteristics. RESULTS: In 2020 and 2021, the mortality probability among nursing home residents was 4.0 and 1.6 per 100 residents higher than expected. There was considerable variation in excess deaths across nursing homes, even after correcting for differences in resident case mix and regional factors. This variation was substantially larger than prepandemic mortality and was in 2020 related to prepandemic spending on external personnel and satisfaction with the building, and in 2021 to prepandemic staff absenteeism. CONCLUSIONS AND IMPLICATIONS: The variation in excess mortality across nursing homes was considerable during the COVID-19 pandemic, and larger compared with prepandemic years. The association of excess mortality with the quality of the building and spending on external personnel indicates the importance of considering differences across nursing home providers when designing policies and guidelines related to pandemic preparedness.

The impact of social cohesion and risk communication on excess mortality due to COVID-19 in 213 countries: a retrospective analysis.

BACKGROUND: Tools for assessing a country's capacity in the face of public health emergencies must be reviewed, as they were not predictive of the COVID-19 pandemic. Social cohesion and risk communication, which are related to trust in government and trust in others, may have influenced adherence to government measures and mortality rates due to COVID-19. OBJECTIVE: To analyse the association between indicators of social cohesion and risk communication and COVID-19 outcomes in 213 countries. RESULTS: Social cohesion and risk communication, in their dimensions (public trust in politicians, trust in others, social safety nets, and equal distribution of resources index), were associated with lower excess mortality due to COVID-19. The number of COVID-19-related disorder events and government transparency were associated with higher excess mortality due to COVID-19. The lower the percentage of unemployed people, the higher the excess mortality due to COVID-19. Most of the social cohesion and risk communication variables were associated with better vaccination indicators, except for social capital and engaged society, which had no statistically significant association. The greater the gender equality, the better the vaccination indicators, such as the number of people who received all doses. CONCLUSION: Public trust in politicians, trust in others, equal distribution of resources and government that cares about the most vulnerable, starting with the implementation of programs, such as cash transfers and combating food insecurity, were factors that reduced the excess mortality due to COVID-19. Countries, especially those with limited resources and marked by social, economic, and health inequalities, must invest in strengthening social cohesion and risk communication, which are robust strategies to better cope with future pandemics.

Excess multi-cause mortality linked to influenza virus infection in China, 2012-2021: a population-based study.

Objectives: The aim of this study is to estimate the excess mortality burden of influenza virus infection in China from 2012 to 2021, with a concurrent analysis of its associated disease manifestations. Methods: Laboratory surveillance data on influenza, relevant population demographics, and mortality records, including cause of death data in China, spanning the years 2012 to 2021, were incorporated into a comprehensive analysis. A negative binomial regression model was utilized to calculate the excess mortality rate associated with influenza, taking into consideration factors such as year, subtype, and cause of death. Results: There was no evidence to indicate a correlation between malignant neoplasms and any subtype of influenza, despite the examination of the effect of influenza on the mortality burden of eight diseases. A total of 327,520 samples testing positive for influenza virus were isolated between 2012 and 2021, with a significant decrease in the positivity rate observed during the periods of 2012-2013 and 2019-2020. China experienced an average annual influenza-associated excess deaths of 201721.78 and an average annual excess mortality rate of 14.53 per 100,000 people during the research period. Among the causes of mortality that were examined, respiratory and circulatory diseases (R&C) accounted for the most significant proportion (58.50%). Fatalities attributed to respiratory and circulatory diseases exhibited discernible temporal patterns, whereas deaths attributable to other causes were dispersed over the course of the year. Conclusion: Theoretically, the contribution of these disease types to excess influenza-related fatalities can serve as a foundation for early warning and targeted influenza surveillance. Additionally, it is possible to assess the costs of prevention and control measures and the public health repercussions of epidemics with greater precision.

Negative excess oral and pharyngeal cancer mortality in Europe during the early pandemic years.

OBJECTIVE: The COVID-19 pandemic had direct and indirect effects on oral and pharyngeal cancer (OPC) mortality due to high COVID-19 mortality risk among cancer patients, and to the COVID-19 response that caused treatment delays and reduced routine visits. This study investigated the excess OPC mortality in Europe during the early pandemic years. METHODS: Mortality and population data were gathered from the Eurostat database. The 2011-2019 mortality rates were used to estimate the 2020-2021 expected rates through joinpoint trend analysis. The excess mortality rates (observed minus expected mortality) with 95% confidence intervals (95 CIs) were assessed. RESULTS: Statistically significant negative excess age-standardized and crude (age strata <65 and ≥65 years) OPC mortality rates in males and females, in the European Union (EU, 27 countries) and Europe were reported. The estimated OPC missing deaths in EU were 831 (95 CI, 630-985) and 1240 (95 CI, 1039-1394) in 2020 and 2021, respectively, with differences between sexes, age strata, and countries. The OPC deaths in the EU and Europe were 3.6% and 3.5% lower than expected. CONCLUSION: Missing OPC deaths reported in Europe in 2020-2021 could be explained by changes in death certification of OPC patients who developed COVID-19, rather than a real OPC mortality decline.