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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. 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. 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. [ABSTRACT FROM AUTHOR]

Lifespan in schizophrenia spectrum disorders (SSD) is up to 20 years shorter than average. Introduction of new antipsychotic pharmaceuticals has not made any major improvement. Parallel care is provided as usual standard care (USD) in out-patients settings. The study aim was to evaluate if inclusion of Measurement Based Care (MBC) may prolong patients' lifespan. In total, 171 patients were followed with annual semi-structured examinations of psychiatric status, social situation, and somatic illnesses over 20 years, by case managers. Findings indicate that MBC contributed to prolonged lifespan in SSD from 55.6 to 69.4 years from beginning to end of the study. • Measurement Based Care may narrow gap in lifespan between SSD and general population. • Annual regular collection of psychiatric and somatic data increases vital information. • Individualized treatment based on structured data is vital for patients with SSD. [ABSTRACT FROM AUTHOR]

In Alaska, the 1918–20 influenza pandemic was devastating, with mortality rates up to 90% of the population, while in other arctic regions in northern Sweden and Norway mortality was considerably lower. We investigated the timing and age-patterns in excess mortality in Greenland during the period 1918–21 and compare these to other epidemics and the 1889–92 pandemic. We accessed the Greenlandic National Archives and transcribed all deaths from 1880 to 1921 by age, geography, and cause of death. We estimated monthly excess mortality and studied the spatial-temporal patterns of the pandemics and compared them to other mortality crises in the 40-year period. The 1918–21 influenza pandemic arrived in Greenland in the summer of 1919, one year delayed due to ship traffic interruptions during the winter months. We found that 5.2% of the Greenland population died of the pandemic with substantial variability between counties (range, 0.1% to 11%). We did not see the typical pandemic age-pattern of high young-adult mortality, possibly due to high baseline mortality in this age-group or remoteness. However, despite substantial mortality, the mortality impact was not standing out relative to other mortality crises, or of similar devastation reported in Alaskan populations. [ABSTRACT FROM AUTHOR]

Background: This study aims to assess which population groups experienced the heaviest mortality burden during the first three COVID-19 waves in Belgium; and investigate potential changes in social differences in all-cause mortality during the epidemic and compared to the pre-COVID period. Methods: Exhaustive all-cause mortality information (2015–2021) from the Belgian population register was linked to demographic and socioeconomic census and register data. Annual cohorts consisting of 6.5 million to 6.8 million persons were created selecting persons aged 35 and older. Excess mortality was investigated comparing the 137,354 deaths observed during the first three COVID-19 waves with mortality in the reference period 2015–2019. Methods of analysis include direct standardization and Poisson regression analyses. Results: Elderly men experienced the highest absolute mortality burden during all three COVID-waves, followed by elderly women, middle-aged men, and middle-aged women. Care home residents consistently experienced higher mortality rates during the first and second wave compared to peers living in other living arrangements. In wave 3, care home residents showed significant absolute mortality deficits compared to the reference period. When adjusting for all demographic and socioeconomic factors, the traditional pattern of educational and income mortality inequalities was found among the elderly population during the COVID-waves. In contrast, the educational mortality gap among middle-aged persons deepened during COVID-waves 2 and 3 with excess mortality between 19 and 30% observed among mainly lower-educated persons. Income mortality inequalities among middle-aged women and men remained stable or even diminished for some specific groups in some waves. Conclusion: The widening educational mortality gap among middle-aged persons in successive waves suggest an important role of knowledge and associated educational resources during the COVID-19 epidemic. Belgium's broad implementation of public health control and prevention measures may have successfully averted a further widening of social mortality inequality between income groups and among the elderly population. [ABSTRACT FROM AUTHOR]

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. Statistical analysis of UK mortality data. 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. 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. 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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Over the past four years, the COVID-19 pandemic has exerted a profound impact on public health, including on mortality trends. This study investigates mortality patterns in Belgium by examining all-cause mortality, excess mortality, and cause-specific mortality. Methods: We retrieved all-cause mortality data from January 1, 2009, to December 31, 2022, stratified by age group and sex. A linear mixed model, informed by all-cause mortality from 2009 to 2019, was used to predict non-pandemic all-cause mortality rates in 2020–2022 and estimate excess mortality. Further, we also analyzed trends in cause-specific and premature mortality. Results: Different all-cause mortality patterns could be observed between the younger (<45 years) and older age groups. The impact of the COVID-19 pandemic was particularly evident among older age groups. The highest excess mortality occurred in 2020, while a reversal in this trend was evident in 2022. We observed a notable effect of COVID-19 on cause-specific and premature mortality patterns over the three-year period. Conclusions: Despite a consistent decline in COVID-19 reported mortality over this three-year period, it remains imperative to meticulously monitor mortality trends in the years ahead. [ABSTRACT FROM AUTHOR]

Abstract Background This study aims to assess which population groups experienced the heaviest mortality burden during the first three COVID-19 waves in Belgium; and investigate potential changes in social differences in all-cause mortality during the epidemic and compared to the pre-COVID period. Methods Exhaustive all-cause mortality information (2015–2021) from the Belgian population register was linked to demographic and socioeconomic census and register data. Annual cohorts consisting of 6.5 million to 6.8 million persons were created selecting persons aged 35 and older. Excess mortality was investigated comparing the 137,354 deaths observed during the first three COVID-19 waves with mortality in the reference period 2015–2019. Methods of analysis include direct standardization and Poisson regression analyses. Results Elderly men experienced the highest absolute mortality burden during all three COVID-waves, followed by elderly women, middle-aged men, and middle-aged women. Care home residents consistently experienced higher mortality rates during the first and second wave compared to peers living in other living arrangements. In wave 3, care home residents showed significant absolute mortality deficits compared to the reference period. When adjusting for all demographic and socioeconomic factors, the traditional pattern of educational and income mortality inequalities was found among the elderly population during the COVID-waves. In contrast, the educational mortality gap among middle-aged persons deepened during COVID-waves 2 and 3 with excess mortality between 19 and 30% observed among mainly lower-educated persons. Income mortality inequalities among middle-aged women and men remained stable or even diminished for some specific groups in some waves. Conclusion The widening educational mortality gap among middle-aged persons in successive waves suggest an important role of knowledge and associated educational resources during the COVID-19 epidemic. Belgium’s broad implementation of public health control and prevention measures may have successfully averted a further widening of social mortality inequality between income groups and among the elderly population.

Abstract Background Over the past four years, the COVID-19 pandemic has exerted a profound impact on public health, including on mortality trends. This study investigates mortality patterns in Belgium by examining all-cause mortality, excess mortality, and cause-specific mortality. Methods We retrieved all-cause mortality data from January 1, 2009, to December 31, 2022, stratified by age group and sex. A linear mixed model, informed by all-cause mortality from 2009 to 2019, was used to predict non-pandemic all-cause mortality rates in 2020–2022 and estimate excess mortality. Further, we also analyzed trends in cause-specific and premature mortality. Results Different all-cause mortality patterns could be observed between the younger (

Abstract 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.

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.

Abstract 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.

Abstract 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

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background: Asia's elderly Baby Boomer demographic (born between 1946 and 1964) faced a huge problem during the COVID-19 pandemic due to increased all-cause mortality. We aimed to provide a unique Taiwan situation regarding the impact of Baby Boomers on excess mortalities from all causes relative to non-Baby Boomers throughout distinct times of SARS-CoV-2 mutations during the COVID-19 pandemic. Methods: We used the Poisson time series design with a Bayesian directed acyclic graphic approach to build the background mortality prior to the COVID-19 pandemic between 2015 and 2019. It was then used for predicting the expected all-cause deaths compared to the reported figures during the COVID-19 pandemic period based on Taiwan residents, an Omicron-naïve cohort. Results: Baby Boomers experienced a 2% negative excess mortality in 2020 (Wuhan/D614G) and a 4% excess mortality in 2021 (Alpha/Delta) with a rising background mortality trend whereas non-Baby Boomers showed the corresponding figures of 4% negative excess and 1% excess with a stable trend. Baby Boomer and non-Baby Boomer excess mortality soared to 9% (95% CI: 7-10%) and 10% (95% CI: 9-11%), respectively, during the epidemic Omicron period from January to June 2022. Surprisingly, Baby Boomers aged 58–76 experienced the same 9% excess mortality as non-Baby Boomers aged 77 and beyond. Non-COVID-19 deaths were more prevalent among Baby Boomers than non-Baby Boomers (33% vs. 29%). Conclusion: Baby Boomers were more likely to die from COVID-19 in early pandemic and had more non-COVID-19 deaths in late pandemic than older non-Baby Boomers demonstrated in Taiwan Omicron-naïve cohort. For this vulnerable population, adequate access to medical care and medical capacity require more consideration. [ABSTRACT FROM AUTHOR]

Genocide and mass violence research is predominantly focused on asymmetric, large-scale, deliberately targeted physical violence over relatively short timespans and involving stable perpetrator and victim groups. Recent attempts, such as Dirk Moses’s, to redefine the field in order to be more inclusive of politically targeted groups, persecuted over longer time-spans within and across states go in the right direction but still fall short I argue. Instead, I propose a capability-based approach, following Amartya Sen, that enables consideration of a far broader range of violence’s consequences such as starvation, systemic malnutrition, excess mortality from disease, and economic deprivation. After outlining the capability approach, I apply it to two case studies: (1) patterns of depopulation under (asymmetric) colonial violence that deprived indigenous communities of the capability to sustain their populations through violence, disease, and famines, a case which is already being scrutinized by genocide researchers; (2) sustained and much less asymmetric violence in the Central African Republic with high mortality, malnutrition, and economic deprivation. In both cases, the toll of physical violence is substantial, but violence’s indirect consequences are far more lethal. I argue, that if we are to take seriously victims’ suffering and loss of lives – a concern that ultimately normatively underwrites atrocity and conflict research – only the capability approach can encompass these cases. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The population with depression had a considerable excess mortality risk. This increased mortality may be attributed to the biological consequences of depression or the substantial prevalence of health risk behaviors (HRBs). This study aimed to quantify the combined effects of four major HRBs - smoking, excessive alcohol use, physical inactivity, and an unhealthy diet - on excess mortality among depressed individuals. This study included 35,738 adults from the National Health and Nutrition Examination Survey 2005–06 to 2017–18, with mortality follow-up data censored through 2019. The standardized prevalence of HRBs was calculated for populations with and without depression. Poisson regression models were used to calculate the mortality rate ratio (MRR). Based on model adjusting for socio-demographic factors, the attenuation of MRR was determined after further adjustment for HRBs. A total of 3147 participants were identified as having depression. All HRBs showed a significantly higher prevalence among the population with depression. After adjusting for socio-demographic factors, depression was associated with 1.7 and 1.8 times higher all-cause and cardiovascular disease mortality rate, respectively. Further adjustment for all current HRBs resulted in a 21.9 % reduction in all-cause mortality rate and a 15.4 % decrease in cardiovascular disease mortality rate. HRBs were reported at a single time point, and we are unable to demonstrate a causal effect. At least 1/5 of excess mortality for population with depression was attributable to HRBs. Efforts should be made to address HRBs among population with depression. • Depression is related to excess mortality due to depression itself and health risk behaviors. • Depression was related to 1.7 and 1.8 times higher all-cause and CVD mortality. • Adjusting for HRBs led to a 21.9 % and 15.4 % drop in all-cause and CVD mortality. [ABSTRACT FROM AUTHOR]

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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. [ABSTRACT FROM AUTHOR]

San Francisco implemented one of the most intensive, comprehensive, multipronged COVID-19 pandemic responses in the United States using 4 core strategies: (1) aggressive mitigation measures to protect populations at risk for severe disease, (2) prioritization of resources in neighborhoods highly affected by COVID-19, (3) timely and adaptive data-driven policy making, and (4) leveraging of partnerships and public trust. We collected data to describe programmatic and population-level outcomes. The excess all-cause mortality rate in 2020 in San Francisco was half that seen in 2019 in California as a whole (8% vs 16%). In almost all age and race and ethnicity groups, excess mortality from COVID-19 was lower in San Francisco than in California overall, with markedly diminished excess mortality among people aged >65 years. The COVID-19 response in San Francisco highlights crucial lessons, particularly the importance of community responsiveness, joint planning, and collective action, to inform future pandemic response and advance health equity.

ObjectivesPropose a methodology to identify COVID-19 associated deaths using healthcare billing records and evaluate its effectiveness by comparing the results with excess mortality data from 2020 to 2022 and confirmed COVID-19 deaths.MethodsA retrospective quantitative analysis was conducted by merging healthcare billing records with cause of death data. The term “COVID-19 associated death” was defined as any death occurring within a defined timeframe following a confirmed contact with COVID-19. This category includes individuals who died directly due to COVID-19, with COVID-19 as a contributing factor, or as an aftermath of a COVID-19 infection, as well as those who died from other causes but had previously contracted COVID-19. This broader definition provides a more comprehensive measure of excess mortality compared to the officially confirmed COVID-19 deaths attributed to the virus.ResultsWe identified 35,399 COVID-19 associated deaths during the 3-year pandemic in Slovakia compared to 21,395 confirmed COVID-19 deaths.ConclusionThe identification of COVID-19 associated deaths with our methodology offers a more accurate explanation for the notably high excess mortality observed in Slovakia (31,789 deaths) during the pandemic, relative to the EU27. Given the high level of excess mortality, the officially confirmed deaths are likely underestimated, and the presented methodology provides a more precise measure of mortality. Additionally, healthcare billing records prove valuable in identifying these deaths at the individual patient level using claims data of health insurance companies, which is crucial for implementing targeted preventive measures and improving preparedness for future pandemics.

In Alaska, the 1918–20 influenza pandemic was devastating, with mortality rates up to 90% of the population, while in other arctic regions in northern Sweden and Norway mortality was considerably lower. We investigated the timing and age-patterns in excess mortality in Greenland during the period 1918–21 and compare these to other epidemics and the 1889–92 pandemic. We accessed the Greenlandic National Archives and transcribed all deaths from 1880 to 1921 by age, geography, and cause of death. We estimated monthly excess mortality and studied the spatial-temporal patterns of the pandemics and compared them to other mortality crises in the 40-year period. The 1918–21 influenza pandemic arrived in Greenland in the summer of 1919, one year delayed due to ship traffic interruptions during the winter months. We found that 5.2% of the Greenland population died of the pandemic with substantial variability between counties (range, 0.1% to 11%). We did not see the typical pandemic age-pattern of high young-adult mortality, possibly due to high baseline mortality in this age-group or remoteness. However, despite substantial mortality, the mortality impact was not standing out relative to other mortality crises, or of similar devastation reported in Alaskan populations.

Abstract Background Asia’s elderly Baby Boomer demographic (born between 1946 and 1964) faced a huge problem during the COVID-19 pandemic due to increased all-cause mortality. We aimed to provide a unique Taiwan situation regarding the impact of Baby Boomers on excess mortalities from all causes relative to non-Baby Boomers throughout distinct times of SARS-CoV-2 mutations during the COVID-19 pandemic. Methods We used the Poisson time series design with a Bayesian directed acyclic graphic approach to build the background mortality prior to the COVID-19 pandemic between 2015 and 2019. It was then used for predicting the expected all-cause deaths compared to the reported figures during the COVID-19 pandemic period based on Taiwan residents, an Omicron-naïve cohort. Results Baby Boomers experienced a 2% negative excess mortality in 2020 (Wuhan/D614G) and a 4% excess mortality in 2021 (Alpha/Delta) with a rising background mortality trend whereas non-Baby Boomers showed the corresponding figures of 4% negative excess and 1% excess with a stable trend. Baby Boomer and non-Baby Boomer excess mortality soared to 9% (95% CI: 7-10%) and 10% (95% CI: 9-11%), respectively, during the epidemic Omicron period from January to June 2022. Surprisingly, Baby Boomers aged 58–76 experienced the same 9% excess mortality as non-Baby Boomers aged 77 and beyond. Non-COVID-19 deaths were more prevalent among Baby Boomers than non-Baby Boomers (33% vs. 29%). Conclusion Baby Boomers were more likely to die from COVID-19 in early pandemic and had more non-COVID-19 deaths in late pandemic than older non-Baby Boomers demonstrated in Taiwan Omicron-naïve cohort. For this vulnerable population, adequate access to medical care and medical capacity require more consideration.

Abstract 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.

Abstract The aim of this study is to analyse the relationship between democratic quality and excess mortality produced in the year 2020 before COVID-19 vaccinations were generalised. Using cross-sectional data from 80 countries on five continents, multiple linear regression models between excess mortality, the general democracy index and its disaggregation into five categories: electoral process and pluralism, government functioning, political participation, political culture and civil liberties were estimated. The analysis also considered, public health spending per capita, overweight inhabitants, the average temperature of the country, population over 65 years of age, The KOF Globalisation Index, and the Gross National Income per capita as control variables. It was possible to establish a strong inverse association between excess mortality per million inhabitants and the general democracy index and four of its five categories. There was a particularly strong relationship between excess mortality and the political culture dimension (−326.50, p

Background: Norway and Sweden picked two different ways to mitigate the dissemination of the SARS-CoV-2 virus. Norway introduced the strictest lockdown in Europe with strict border controls and intense virus tracking of all local outbreaks while Sweden did not. That resulted in 477 COVID-19 deaths (Norway) and 9737 (Sweden) in 2020, respectively. Methods: Weekly number of COVID-19 related deaths and total deaths for 2020–22 were collected as well as weekly number of deaths for 2015–19 which were used as controls when calculating excess mortality. During the first 12–18 months with high rate of virus transmission in the society, excess mortality rates were used as substitute for COVID-19 deaths. When excess mortality rates later turned negative because of mortality displacement, COVID-19 deaths adjusted for bias due to overreporting were used. Results: There were 17521 COVID-19 deaths in Sweden and 4272 in Norway in the study period. The rate ratio (RR) of COVID-19 related deaths in Sweden vs. Norway to the end of week 43, 2022, was 2.11 (95% CI 2.05–2.19). RR of COVID-19 related deaths vs. excess number of deaths were 2.5 (Sweden) and 1.3 (Norway), respectively. RR of COVID-19 deaths in Sweden vs. Norway after adjusting for mortality displacement and lockdown, was 1.35 (95% CI 1.31–1.39), corresponding to saving 2025 life in Norway. If including all deaths in 2022, RR= 1.28 (95% CI 1.24–1.31). Conclusions: Both COVID-19 related mortality and excess mortality rates are biased estimates. When adjusting for bias, mortality differences declined over time to about 30% higher mortality in Sweden after 30 months with pandemics.

Objective Methods Results Conclusion 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.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.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.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. [ABSTRACT FROM AUTHOR]

Background The COVID-19 pandemic has been extensively studied for its impact on mortality, particularly in older age groups. However, the pandemic effects on stillbirths and mortality rates in neonates, infants, children and youth remain poorly understood. This study comprehensively analyses the pandemic influence on young mortality and stillbirths across 112 countries and territories in 2020 and 104 in 2021. Methods Using data from civil registers and vital statistics systems (CRVS) and the Health Management Information System (HMIS), we estimate expected mortality levels in a non-pandemic setting and relative mortality changes (p-scores) through generalized linear models. The analysis focuses on the distribution of country-specific mortality changes and the proportion of countries experiencing deficits, no changes and excess mortality in each age group. Results Results show that stillbirths and under-25 mortality were as expected in most countries during 2020 and 2021. However, among countries with changes, more experienced deficits than excess mortality, except for stillbirths, neonates and those aged 10–24 in 2021, where, despite the predominance of no changes, excess mortality prevailed. Notably, a fifth of examined countries saw increases in stillbirths and a quarter in young adult mortality (20–24) in 2021. Our findings are highly consistent between females and males and similar across income levels. Conclusion Despite global disruptions to essential services, stillbirths and youth mortality were as expected in most observed countries, challenging initial hypotheses. However, the study suggests the possibility of delayed adverse effects that require more time to manifest at the population level. Understanding the lasting impacts of the COVID-19 pandemic requires ongoing, long-term monitoring of health and deaths among children and youth, particularly in low- and lower-middle-income countries. [ABSTRACT FROM AUTHOR]

Objective: 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. Methods: 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. Results: 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. Conclusions: 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. [ABSTRACT FROM AUTHOR]

This study examines excess mortality patterns in 32 European countries during the first three years of the pandemic, offering insights into the pandemic’s toll on each country. Using data from national statistical offices, we calculated monthly excess mortality for 2020–2022. Time series decomposition was employed for trend analysis, followed by clustering countries based on their mortality trends. Then we compared total excess mortality among different clusters. We found that neighboring countries with similar characteristics experienced comparable levels of excess mortality, regardless of the differences in their pandemic trajectories identified by cluster analysis. Other factors, such as healthcare infrastructure and pre-existing health risks, appear to have had a more significant impact on total excess mortality, with various pre-existing regional factors playing significant roles in shaping the pandemic’s final toll. While the timing of peak excess mortality may have been a factor, it was not the primary driver of the overall toll. This study highlights the critical need for comprehensive public health strategies that focus on reinforcing healthcare infrastructure and mitigating pre-existing health risks, essential for effective pandemic preparedness and response. These findings suggest the need for reevaluating current approaches and exploring alternative strategies for managing future health emergencies. [ABSTRACT FROM AUTHOR]

Copyright of Annali di Igiene, Medicina Preventiva e di Comunità is the property of Societa Editrice Universo s.r.l. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Polish Statistician / Wiadomości Statystyczne is the property of State Treasury - Statistics Poland and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The aim of this study is to analyse the relationship between democratic quality and excess mortality produced in the year 2020 before COVID-19 vaccinations were generalised. Using cross-sectional data from 80 countries on five continents, multiple linear regression models between excess mortality, the general democracy index and its disaggregation into five categories: electoral process and pluralism, government functioning, political participation, political culture and civil liberties were estimated. The analysis also considered, public health spending per capita, overweight inhabitants, the average temperature of the country, population over 65 years of age, The KOF Globalisation Index, and the Gross National Income per capita as control variables. It was possible to establish a strong inverse association between excess mortality per million inhabitants and the general democracy index and four of its five categories. There was a particularly strong relationship between excess mortality and the political culture dimension (−326.50, p < 0.001). The results suggest that the higher the democratic quality of the political institutions of a State and particularly of their political culture the more improved the response and management of the pandemic was in preventing deaths and protecting their citizens more effectively. Conversely, countries with lower democracy index values have higher excess mortality. Quality democratic political institutions provide more effective public health policies in the face of the COVID-19 pandemic. [ABSTRACT FROM AUTHOR]

Excess mortality is often used to estimate the effect of a certain crisis on the population. It is defined as the number of deaths during a crisis exceeding the expected number based on historical trends. Here, we calculated excess mortality due to the COVID-19 pandemic for Croatia in the 2020–2021 period. The excess was calculated on the national and county level for different age and sex categories. In addition to the absolute number, the excess mortality was also expressed as a ratio of excess deaths to the predicted baseline and excess mortality rate. We showed that using both measures is necessary to avoid incorrect conclusions. The estimated excess mortality on the national level was 14,963, corresponding to an excess percentage of 14.3%. With respect to sex, there was a higher excess mortality rate for men compared to women. An exponential relationship was observed between age and the excess mortality rate.These trends wee representative of most counties as well, with large variations in the magnitude of the effect. However, there were also exceptions to the general rule. The reasons for these deviations were discussed in terms of between-county differences in demographic structure, population density and special events that took place during the pandemic. [ABSTRACT FROM AUTHOR]

Objectives: Excess mortality (EM) is a comprehensive indicator for quantifying the direct and indirect effects of the COVID-19 pandemic. This study estimated EM in Taiwan during the COVID-19 pandemic. Methods: Monthly mortality data (2010–2019) and population statistics of counties and cities in Taiwan were collected for quasi-Poisson regression analysis. After the effects of month, aging, and total population were adjusted, weighted regression coefficients were obtained to construct a predictive model for the expected number of deaths in 2020–2022. EM is obtained using the following formula: reported number of deaths − expected number of deaths. Results: In 2020, no EM was observed at either national or regional levels. In 2021, EM was observed during the Level 3 alert period in Taipei City and New Taipei City. A COVID-19 variant (Omicron) broke out in May 2022, after which EM substantially increased. In 2022, EM of 20,702 was observed, of which 29.9% was indirect EM (not related to COVID-19). The five regions with the highest proportions of indirect EM were Hsinchu County, Chiayi County, Yunlin County, Miaoli County, and New Taipei City (42%–61%). Conclusions: EM can serve as an indicator of pandemic severity. Notably, regions with limited healthcare resources reported a higher proportion of indirect EM, highlighting the pandemic’s role in impairing healthcare accessibility in these regions. Thus, policy interventions are necessary to balance the distribution of medical resources and mitigate indirect EM. [ABSTRACT FROM AUTHOR]

Norway and Sweden picked two different ways to mitigate the dissemination of the SARS-CoV-2 virus. Norway introduced the strictest lockdown in Europe with strict border controls and intense virus tracking of all local outbreaks while Sweden did not. That resulted in 477 COVID-19 deaths (Norway) and 9737 (Sweden) in 2020, respectively. Weekly number of COVID-19 related deaths and total deaths for 2020–22 were collected as well as weekly number of deaths for 2015–19 which were used as controls when calculating excess mortality. During the first 12–18 months with high rate of virus transmission in the society, excess mortality rates were used as substitute for COVID-19 deaths. When excess mortality rates later turned negative because of mortality displacement, COVID-19 deaths adjusted for bias due to overreporting were used. There were 17521 COVID-19 deaths in Sweden and 4272 in Norway in the study period. The rate ratio (RR) of COVID-19 related deaths in Sweden vs. Norway to the end of week 43, 2022, was 2.11 (95% CI 2.05–2.19). RR of COVID-19 related deaths vs. excess number of deaths were 2.5 (Sweden) and 1.3 (Norway), respectively. RR of COVID-19 deaths in Sweden vs. Norway after adjusting for mortality displacement and lockdown, was 1.35 (95% CI 1.31–1.39), corresponding to saving 2025 life in Norway. If including all deaths in 2022, RR= 1.28 (95% CI 1.24–1.31). Both COVID-19 related mortality and excess mortality rates are biased estimates. When adjusting for bias, mortality differences declined over time to about 30% higher mortality in Sweden after 30 months with pandemics. [ABSTRACT FROM AUTHOR]

The study of mortality is an ever-active field of research, and new methods or combinations of methods are constantly being developed. In the actuarial domain, the study of phenomena disrupting mortality and leading to excess mortality, as in the case of COVID-19, is of great interest. Therefore, it is relevant to investigate the extent to which an epidemiological model can be integrated into an actuarial approach in the context of mortality. The aim of this project is to establish a method for the study of excess mortality due to an epidemic and to quantify these effects in the context of the insurance world to anticipate certain possible financial instabilities. We consider a case study caused by SARS-CoV-2 in Belgium during the year 2020. We propose an approach that develops an epidemiological model simulating excess mortality, and we incorporate this model into a classical approach to pricing life insurance products. [ABSTRACT FROM AUTHOR]

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.

Abstract 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.

ABSTRACT Objective To investigate excess mortality during the COVID-19 pandemic and its spatial distribution in Pernambuco, Brazil. Methods This was an ecological, descriptive and analytical study of deaths, by municipality, recorded on the Mortality Information System, in 2020 and 2021. Excess mortality was measured by comparing observed and expected deaths, the latter estimated by calculating standardized mortality ratio (SMR). SMR and respective confidence intervals (95%CI) were calculated. Spatial analysis was performed by calculating the Global and Local Moran Index. Results Excess mortality was 20.6% and 27.5%, respectively, in 2020 and 2021, with positive spatial correlation (p-value < 0.05). More populous municipalities (2020: SMR = 1.26; 95%CI 1.24;1.27 and 2021: SMR = 1.34; 95%CI 1.32;1.34), more developed municipalities (2020: SMR = 1.43; 95%CI 1.41;1.44 and 2021: SMR = 1.51;95%CI 1.50;1.53) and municipalities in the Sertão region (2020:SMR = 1.31;95%CI 1.30;1.33 and 2021: SMR = 1.44; 95%CI 1.42;1.46) showed greater excess deaths. Conclusion Excess mortality coincided with peak periods of COVID-19 transmission.

Objectives: The coronavirus disease 2019 (COVID-19) pandemic led to increased mortality rates. To assess this impact, this ecological study aimed to estimate the excess death counts in southern Iran. Methods: The study obtained weekly death counts by linking the National Death Registry and Medical Care Monitoring Center repositories. The P-score was initially estimated using a simple method that involved calculating the difference between the observed and expected death counts. The interrupted time series analysis was then used to calculate the mean relative risk (RR) of death during the first year of the pandemic. Results: Our study found that there were 5571 excess deaths from all causes (P-score=33.29%) during the first year of the COVID-19 pandemic, with 48.03% of these deaths directly related to COVID-19. The pandemic was found to increase the risk of death from all causes (RR, 1.26; 95% confidence interval [CI], 1.19 to 1.33), as well as in specific age groups such as those aged 35-49 (RR, 1.21; 95% CI, 1.12 to 1.32), 50-64 (RR, 1.38; 95% CI, 1.28 to 1.49), and ≥65 (RR, 1.29; 95% CI, 1.12 to 1.32) years old. Furthermore, there was an increased risk of death from cardiovascular diseases (RR, 1.17; 95% CI, 1.11 to 1.22). Conclusions: There was a 26% increase in the death count in southern Iran during the COVID-19 pandemic. More than half of these excess deaths were not directly related to COVID-19, but rather other causes, with cardiovascular diseases being a major contributor.

Introduction: The COVID-19 pandemic caused a significant mortality in the world and in Ecuador. This research aimed to analyze the excess mortality due to the COVID-19 pandemic in Ecuador. Method: An observational, longitudinal, quantitative and descriptive study, classified as an ecological study in the field of epidemiology. This study focuses on measuring excess mortality during the years 2020, 2021 and 2022, using the average number of deaths that occurred in the period from 2015 to 2019 as the baseline. Results: From January 2020 to October 2022, Ecuador accumulated a total excess of deaths of 98,915. In 2020, the excess mortality was higher at 46,374, with the highest value occurring in April at 15,484. In 2021, the excess deaths amounted to 35,859, with April having the highest excess of 7,330. In 2022, the excess mortality was 16,682, with January recording the highest excess at 4,204. Conclusion: Evidence of underreporting of deaths, as well as temporal and geographical variations in excess mortality, was observed. The province with the highest number of deaths and excess mortality was Guayas, followed by Pichincha. The results provide an analysis of the situation during the health emergency, emphasizing the importance of evaluating the healthcare system's capacity to respond during times of crisis and the imperative need to implement corrective measures for the future.

Abstract Objective 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. Methods 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. Results 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. Conclusions 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.

Excess mortality is often used to estimate the effect of a certain crisis on the population. It is defined as the number of deaths during a crisis exceeding the expected number based on historical trends. Here, we calculated excess mortality due to the COVID-19 pandemic for Croatia in the 2020–2021 period. The excess was calculated on the national and county level for different age and sex categories. In addition to the absolute number, the excess mortality was also expressed as a ratio of excess deaths to the predicted baseline and excess mortality rate. We showed that using both measures is necessary to avoid incorrect conclusions. The estimated excess mortality on the national level was 14,963, corresponding to an excess percentage of 14.3%. With respect to sex, there was a higher excess mortality rate for men compared to women. An exponential relationship was observed between age and the excess mortality rate.These trends wee representative of most counties as well, with large variations in the magnitude of the effect. However, there were also exceptions to the general rule. The reasons for these deviations were discussed in terms of between-county differences in demographic structure, population density and special events that took place during the pandemic.

Background/Aim: Until March 2023, it has been reported over 676 million cases of COVID-19 globally with almost 7 million deaths caused by this disease. Aim of this study was to determine COVID-19-related deaths and to study how COVID-19 pandemic impacted mortality of residents in the Canton of Sarajevo in 2020-2022 time period. Also, aim was to analyse to what extent the number of registered non-COVID-19-related deaths have changed in the Canton of Sarajevo compared to what would have been expected in the absence of the virus to better measure the impact of COVID-19. Methods: This study used mortality data obtained from Federal Institute for Statistics for period 2017-2022. Data was analysed and presented as raw numbers, age-, sex-, cause of death - crude death rates (CDR), excess mortality and P-score. Results: CDR in the Canton of Sarajevo in 2020 was 1246.3 per 100.000 persons, 1488.6 in 2021 and 1153.4 in 2022, while in period from 2017-2019 CDR ranged from 1051.3 to 1057.9. Total CDR in 2020 increased by 18.3 % compared to 2017-2019 average CDR, this relative difference being even greater in 2021 (41.3 %) and lower in 2022 (9.5 %). In 2020-2022 time period, 9 of the 10 leading causes of death remained the same as in 2019. COVID-19 was the 3rd leading cause of death in 2020 and 2022, while in 2021 spiked as the leading cause of death. In 2020 there was increase of 7 % in deaths from non-COVID-19 related deaths compared to mean number of deaths for period 2017-2019. As for 2021, this number goes higher (9.5 %) and in 2022 was much lower (1.0 %). Conclusion: In the Canton of Sarajevo, COVID-19 pandemic made a big impact on mortality in 2020-2022 years period. Data have changed in total mortality, leading causes of death and excess mortality. Deep-rooted organisational weaknesses that were exposed during pandemic that can bring harm to population from preventable chronic diseases needs to be addressed which have impact on morbidity and at the end, on mortality.

Objective Intertrochanteric fracture is one type of hip fracture, which is the most serious consequence of osteoporosis. Along with the growing elderly population, intertrochanteric fracture is expected to rise increasingly. The aim of this study was to assess excess mortality after intertrochanteric fractures and to identify the predictors of long‐term mortality by therapy among patients aged 50 years and older in Tianjin. Methods This is a retrospective cohort study on mortality for 3029 patients aged 50 years and older in Tianjin experiencing an intertrochanteric fracture between December 26, 2014 and December 31, 2018. Data were from Tianjin Hospital Hip Fracture (THHF) cohort. Follow‐up period was until March 31, 2022. Mortality, excess mortality, and comorbidities were analyzed and stratified by therapy and gender. Time dependent Cox models were performed to estimate the effects of the variables. Results Absolute mortality for all the patients was 5.90% at 3 months, 12.55% at 12 months, 19.92% at 24 months and 27.28% at 36 months. Absolute mortality for surgical group was 1.57% at 3 months, 4.77% at 12 months, 8.49% at 24 months and 12.07% at 36 months, significantly lower than conservative group: 10.50% at 3 months, 20.73% at 12 months, 31.96% at 24 months and 43.04% at 36 months. We found a substantially lower mortality (hazard ratio [HR] 0.34, 95% confidence internal, [CI]: 0.23–0.52, p = 0.000) among patients undergoing surgical therapy than those undergoing conservative therapy, even when controlled for gender, age, the length of hospital stay, and all the comorbidities. Female patients (HR 0.68, 95% CI: 0.58–0.79, p = 0.000) were less likely to die than male patients after an intertrochanteric fracture. Patients treated by the two methods were both found to have excess mortality rates compared to the general population, although in different levels. The excess mortality rates for patients in the conservative therapy group were 14.46% in males and 17.93% in females, while in the surgical therapy group, 2.78% in females and 4.37% in males. The comorbidities moderate or severe renal disease (HR 2.19, 95% CI: 1.61–2.98, p = 0.000), metastatic solid tumor (HR 6.35, 95% CI: 1.56–25.85, p = 0.010), hypoproteinemia (HR 1.22, 95% CI: 1.01–1.47, p = 0.034), and older age (HR 1.89, 95% CI: 1.73–2.08, p = 0.000) were also risk factors on mortality. A worse‐case analysis for the primary outcome were performed as sensitivity analysis and it was consistent with the original conclusion. Conclusion Intertrochanteric factures for people aged 50 years older were found to have excess mortality compared to the general population in Tianjin city, and preventing the fractures in the hip for elderly people was imperative. After controlling tfor comorbidities and age, female gender and surgical therapy were protective factors for the death after fractures, which could provide strong evidence for patients and surgeons to make decisions.