scholarly journals Excess Mortality Associated With COVID-19 by Demographic Group: Evidence From Florida and Ohio

2021 ◽  
pp. 003335492110415
Author(s):  
Troy Quast ◽  
Ross Andel
Keyword(s):  
Excess Mortality ◽  
Prediction Interval ◽  
National Level ◽  
Age Groups ◽  
Black Population ◽  
Infection Rates ◽  
Black Adults ◽  
Demographic Groups ◽  
Younger Age ◽  
Excess Deaths

Objective COVID-19 mortality varies across demographic groups at the national level, but little is known about potential differences in COVID-19 mortality across states. The objective of this study was to estimate the number of all-cause excess deaths associated with COVID-19 in Florida and Ohio overall and by sex, age, and race. Methods We calculated the number of weekly and cumulative excess deaths among adults aged ≥20 from March 15 through December 5, 2020, in Florida and Ohio as the observed number of deaths less the expected number of deaths, adjusted for population, secular trends, and seasonality. We based our estimates on death certificate data from the previous 10 years. Results The results were based on ratios of observed-to-expected deaths. The ratios were 1.17 (95% prediction interval, 1.14-1.21) in Florida and 1.15 (95% prediction interval, 1.11-1.19) in Ohio. Although the largest number of excess deaths occurred in the oldest age groups, in both states the ratios of observed-to-expected deaths were highest among adults aged 20-49 (1.21; 95% prediction interval, 1.11-1.32). The ratio of observed-to-expected deaths for the Black population was especially elevated in Florida. Conclusions Although excess deaths were largely concentrated among older cohorts, the high ratios of observed-to-expected deaths among younger age groups indicate widespread effects of COVID-19. The high levels of observed-to-expected deaths among Black adults may reflect in part disparities in infection rates, preexisting conditions, and access to care. The finding of high excess deaths among Black adults deserves further attention.

scholarly journals Estimating the burden of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality in England and Wales: a population-level analysis

2021 ◽  
pp. jech-2020-215505
Author(s):  
Jose Manuel Aburto ◽  
Ridhi Kashyap ◽  
Jonas Schöley ◽  
Colin Angus ◽  
John Ermisch ◽  
...  
Keyword(s):  
Life Expectancy ◽  
Excess Mortality ◽  
Prediction Interval ◽  
Age Groups ◽  
Population Level ◽  
England And Wales ◽  
Life Expectancy At Birth ◽  
Using Data ◽  
The Impact ◽  
Excess Deaths

BackgroundDeaths directly linked to COVID-19 infection may be misclassified, and the pandemic may have indirectly affected other causes of death. To overcome these measurement challenges, we estimate the impact of the COVID-19 pandemic on mortality, life expectancy and lifespan inequality from week 10 of 2020, when the first COVID-19 death was registered, to week 47 ending 20 November 2020 in England and Wales through an analysis of excess mortality.MethodsWe estimated age and sex-specific excess mortality risk and deaths above a baseline adjusted for seasonality with a systematic comparison of four different models using data from the Office for National Statistics. We additionally provide estimates of life expectancy at birth and lifespan inequality defined as the SD in age at death.ResultsThere have been 57 419 (95% prediction interval: 54 197, 60 752) excess deaths in the first 47 weeks of 2020, 55% of which occurred in men. Excess deaths increased sharply with age and men experienced elevated risks of death in all age groups. Life expectancy at birth dropped 0.9 and 1.2 years for women and men relative to the 2019 levels, respectively. Lifespan inequality also fell over the same period by 5 months for both sexes.ConclusionQuantifying excess deaths and their impact on life expectancy at birth provide a more comprehensive picture of the burden of COVID-19 on mortality. Whether mortality will return to—or even fall below—the baseline level remains to be seen as the pandemic continues to unfold and diverse interventions are put in place.

scholarly journals Pooling European all-cause mortality: methodology and findings for the seasons 2008/2009 to 2010/2011

2012 ◽  
Vol 141 (9) ◽  
pp. 1996-2010 ◽  
Author(s):  
J. NIELSEN ◽  
A. MAZICK ◽  
N. ANDREWS ◽  
M. DETSIS ◽  
T. M. FENECH ◽  
...  
Keyword(s):  
Influenza A ◽  
Excess Mortality ◽  
National Level ◽  
Age Groups ◽  
Pooled Analysis ◽  
European Countries ◽  
Younger Age ◽  
Influenza A H1n1 ◽  
All Cause Mortality ◽  
Fertile Women

SUMMARYSeveral European countries have timely all-cause mortality monitoring. However, small changes in mortality may not give rise to signals at the national level. Pooling data across countries may overcome this, particularly if changes in mortality occur simultaneously. Additionally, pooling may increase the power of monitoring populations with small numbers of expected deaths, e.g. younger age groups or fertile women. Finally, pooled analyses may reveal patterns of diseases across Europe. We describe a pooled analysis of all-cause mortality across 16 European countries. Two approaches were explored. In the ‘summarized’ approach, data across countries were summarized and analysed as one overall country. In the ‘stratified’ approach, heterogeneities between countries were taken into account. Pooling using the ‘stratified’ approach was the most appropriate as it reflects variations in mortality. Excess mortality was observed in all winter seasons albeit slightly higher in 2008/09 than 2009/10 and 2010/11. In the 2008/09 season, excess mortality was mainly in elderly adults. In 2009/10, when pandemic influenza A(H1N1) dominated, excess mortality was mainly in children. The 2010/11 season reflected a similar pattern, although increased mortality in children came later. These patterns were less clear in analyses based on data from individual countries. We have demonstrated that with stratified pooling we can combine local mortality monitoring systems and enhance monitoring of mortality across Europe.

scholarly journals Excess Deaths associated with the COVID-19 Pandemic in Ukraine in 2020

2021 ◽  
Author(s):  
Neil K. Mehta ◽  
Ihor Honchar ◽  
Olena Doroshenko ◽  
Igor Brovchenko ◽  
Khrystyna Pak ◽  
...  
Keyword(s):  
Excess Mortality ◽  
Age Groups ◽  
European Countries ◽  
List Type ◽  
Younger Age ◽  
Influenza Activity ◽  
Expected Mortality ◽  
The Impact ◽  
Excess Deaths

AbstractCOVID-19 related mortality has been understudied in Ukraine. As part of a World Bank project, we estimated excess mortality in Ukraine during 2020. Data on all deaths registered in government-controlled Ukraine from 2016-2020 (N=2,946,505) were utilized. We predicted deaths in 2020 by five-year age groups, sex, and month and calculated the number of deaths that deviated from expected levels (excess deaths). We compared excess deaths with the number of recorded COVID-19 deaths on death certificates and with published estimates for 30 European countries. We estimated 38,095 excess deaths in 2020 (6% of all deaths). Death rates were above expected levels in February and from June-December and lower in January and March-May. From June-December, we estimated 52,124 excess deaths with a peak in November (16,891 deaths). COVID-19 recorded deaths were approximately one-third of excess deaths in June-December (18,959 vs. 52,124). Higher than expected mortality was detected for all age groups 40-44 years and above and for those ages 0-4, 15-19, and 20-24. Ukraine’s excess mortality was about average compared to 30 other European countries. Excess deaths may be attributed directly to SARS-COV2 infection or indirectly to death causes associated with social and economic upheavals resulting in from the pandemic. Lower than expected mortality during the early part of 2020 is consistent with low influenza activity and reductions in deaths from restricted movement. Further studies are required to examine the causes of death that have contributed to positive excess mortality, particularly among younger aged groups.Key MessagesUkraine has experienced sizeable changes in its recent demography and the impact of the COVID-19 pandemic on the country’s aggregate mortality patterns is understudiedBased on recent death trends, we found that Ukraine experienced lower than expected mortality during the early part of 2020 and consistently higher than expected mortality from June-December with peak levels occurring in NovemberPositive excess mortality was observed for all age groups beginning at ages 40-44 as well as some younger age groups.

scholarly journals Estimation of Excess Mortality and Years of Life Lost to COVID-19 in Norway and Sweden between March and November 2020

2021 ◽  
Vol 18 (8) ◽  
pp. 3913
Author(s):  
Martin Rypdal ◽  
Kristoffer Rypdal ◽  
Ola Løvsletten ◽  
Sigrunn Holbek Sørbye ◽  
Elinor Ytterstad ◽  
...  
Keyword(s):  
Excess Mortality ◽  
Age Groups ◽  
Years Of Life Lost ◽  
Regressive Model ◽  
Epidemic Period ◽  
All Cause Mortality ◽  
Auto Regressive ◽  
Expected Mortality ◽  
Auto Regressive Model ◽  
Excess Deaths

We estimate the weekly excess all-cause mortality in Norway and Sweden, the years of life lost (YLL) attributed to COVID-19 in Sweden, and the significance of mortality displacement. We computed the expected mortality by taking into account the declining trend and the seasonality in mortality in the two countries over the past 20 years. From the excess mortality in Sweden in 2019/20, we estimated the YLL attributed to COVID-19 using the life expectancy in different age groups. We adjusted this estimate for possible displacement using an auto-regressive model for the year-to-year variations in excess mortality. We found that excess all-cause mortality over the epidemic year, July 2019 to July 2020, was 517 (95%CI = (12, 1074)) in Norway and 4329 [3331, 5325] in Sweden. There were 255 COVID-19 related deaths reported in Norway, and 5741 in Sweden, that year. During the epidemic period of 11 March–11 November, there were 6247 reported COVID-19 deaths and 5517 (4701, 6330) excess deaths in Sweden. We estimated that the number of YLL attributed to COVID-19 in Sweden was 45,850 [13,915, 80,276] without adjusting for mortality displacement and 43,073 (12,160, 85,451) after adjusting for the displacement accounted for by the auto-regressive model. In conclusion, we find good agreement between officially recorded COVID-19 related deaths and all-cause excess deaths in both countries during the first epidemic wave and no significant mortality displacement that can explain those deaths.

scholarly journals Cataract among elderly in Sri Lanka

2019 ◽  
Author(s):  
A.A. Nilanga Nishad ◽  
S.A. Hewage ◽  
K. Arulmoly ◽  
M.S. Amaratunge ◽  
J de Silva ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Screening Programme ◽  
National Level ◽  
Age Groups ◽  
Cross Sectional Study ◽  
Community Based ◽  
Cross Sectional ◽  
Future Studies ◽  
Factors Associated ◽  
Younger Age

AbstractOut of 39 billion people who are blind around the world, 20 billion (51.3%) is due to cataract, which is preventable. This study intended to assess the prevalence and factors associated with cataract among elderly in a divisional secretariat area in Sri Lanka. This community based cross sectional study assessed randomly selected470 adults over 60 years of age. Diagnosis of cataract was made by a slit lamp examination by medical officers, and classified according to Oxford Lens Opacity Classification system (LOCS III). Majority was between 60-69 age groups and 71% was females. The prevalence of cataract was estimated to be 80.6% including operated eye and 73.6% excluding the operated eye, with a female preponderance in lower age categories. Commonest type of cataract was the nuclear type (n=422; 44.9%), with a majority in grade 2 (218; 23.2%). The prevalence of cataract surgery in the diseased population was as low as 7%. Cataract leading to blindness is very prevalent among adults over 60 years of age in the studied area. Females tend to develop the disease at an early age than males. These findings warrant screening programme for elderly at community level, targeting females at a younger age than males. Future studies are recommended to assess the coverage and barriers for cataract surgeries at national level, which would be immensely useful in planning and improving health services.

scholarly journals Predictive Value of Technical Throwing Skills on Nomination Status in Youth and Long-Term Career Attainment in Handball

2022 ◽  
Vol 8 (1) ◽  
Author(s):  
Till Koopmann ◽  
Franziska Lath ◽  
Dirk Büsch ◽  
Jörg Schorer
Keyword(s):  
Logistic Regression ◽  
National Level ◽  
Age Groups ◽  
Age Group ◽  
Regression Analyses ◽  
Chi Square ◽  
Career Attainment ◽  
Future Performance ◽  
Younger Age

Abstract Background Research on talent in sports aims to identify predictors of future performance. This study retrospectively investigated 1) relationships between young handball field players’ technical throwing skills and (a) their potential nomination to youth national teams and (b) their long-term career attainment 10 years later, and 2) associations between nomination status and career attainment. Results Results from retrospectively predicting nomination status and career attainment using logistic regression analyses show that technical throwing skills were partly able to explain players’ nomination status (Nagelkerke R2: females 9.2%, males 13.1%) and career attainment (Nagelkerke R2: 9.8% for female players). Here, variables throwing velocity and time on exercise showed statistically significant effects. In addition, nomination status and career attainment were shown to be associated using chi-square tests (w of .37 and .23 for female and male players, respectively) and nomination status as a predictor increased the prediction of career attainment remarkably (Nagelkerke R2: females 20.3%, males 12.7%). Conclusions Given these results, basic technical throwing skills may serve rather as a prerequisite in this age group on national level, emphasizing its importance already on lower levels and in younger age groups. Furthermore, advantages from entering the national TID system early especially for females are discussed.

scholarly journals THE US MIDLIFE MORTALITY CRISIS CONTINUES: INCREASED DEATH RATES FROM CAUSES OTHER THAN COVID-19 DURING 2020

2021 ◽  
Author(s):  
Dana A Glei
Keyword(s):  
Indirect Effect ◽  
Causes Of Death ◽  
Excess Mortality ◽  
Negative Binomial ◽  
National Level ◽  
Age Groups ◽  
Negative Binomial Regression ◽  
Negative Binomial Regression Model ◽  
Age Group ◽  
External Causes

COVID-19 has prematurely ended many lives, particularly among the oldest Americans, but the pandemic has also had an indirect effect on health and non-COVID mortality among the working-age population, who have suffered the brunt of the economic consequences. This analysis quantifies the changes in mortality for selected causes of death during the COVID 19 pandemic up to December 31, 2020, and investigates whether the levels of excess mortality varied by age group. The data comprise national-level monthly death counts by age group and selected causes of death from January 1999 to December 2020 combined with annual mid-year population estimates over the same period. A negative binomial regression model was used to estimate monthly cause-specific excess mortality during 2020 controlling for the pre-pandemic mortality patterns by age, calendar year, and season. To determine whether excess mortality varied by age, we tested interactions between broad age groups and dichotomous indicators for the pre-pandemic (January-February) and the pandemic (March-December) portions of 2020. In relative terms, excess all cause mortality (including COVID-19) peaked in December at ages 25-44 (RR=1.58 relative to 2019, 95% CI=1.50-1.68). Excluding COVID-19, all of the excess mortality occurred between ages 15 and 64, peaking in July among those aged 25-44 (RR=1.45, 95% CI 1.37-1.53). We find notable excess mortality during March-December 2020 for many causes (i.e., influenza/pneumonia, other respiratory diseases, diabetes, heart disease, cerebrovascular disease, kidney disease, and external causes), but almost exclusively among young and midlife (aged 25-74) Americans. For those aged 75 and older, there was little excess mortality from causes other than COVID-19 except from Alzheimer's disease. Excess non-COVID mortality may have resulted, at least partly, from incorrectly classified COVID-19 deaths, but neither misclassification nor an atypical flu season that disproportionately affected younger people is likely to explain the increase in mortality from external causes, which was evident even during January-February 2020. Exploratory analyses suggest that drug-related mortality may be driving the early rise in external mortality. The growth in drug overdoses well before there was any hint of a pandemic suggests it is probably not solely an indirect effect of COVID-19, although the pandemic may have exacerbated the problem.

scholarly journals Excess mortality in Guadeloupe and Martinique, islands of the French West Indies, during the chikungunya epidemic of 2014

2018 ◽  
Vol 146 (16) ◽  
pp. 2059-2065 ◽  
Author(s):  
A. R. R. Freitas ◽  
P. M. Alarcón-Elbal ◽  
M. R. Donalisio
Keyword(s):  
Strong Correlation ◽  
Excess Mortality ◽  
Pearson Correlation ◽  
Age Groups ◽  
Epidemiological Data ◽  
Mortality Data ◽  
Surveillance Systems ◽  
Mortality And Morbidity ◽  
The Impact ◽  
Excess Deaths

AbstractIn some chikungunya epidemics, deaths are not completely captured by traditional surveillance systems, which record case and death reports. We evaluated excess deaths associated with the 2014 chikungunya virus (CHIKV) epidemic in Guadeloupe and Martinique, Antilles. Population (784 097 inhabitants) and mortality data, estimated by sex and age, were accessed from the Institut National de la Statistique et des Études Économiques in France. Epidemiological data, cases, hospitalisations and deaths on CHIKV were obtained from the official epidemiological reports of the Cellule de Institut de Veille Sanitaire in France. Excess deaths were calculated as the difference between the expected and observed deaths for all age groups for each month in 2014 and 2015, considering the upper limit of 99% confidence interval. The Pearson correlation coefficient showed a strong correlation between monthly excess deaths and reported cases of chikungunya (R= 0.81,p< 0.005) and with a 1-month lag (R= 0.87,p< 0.001); and a strong correlation was also observed between monthly rates of hospitalisation for CHIKV and excess deaths with a delay of 1 month (R= 0.87,p< 0.0005). The peak of the epidemic occurred in the month with the highest mortality, returning to normal soon after the end of the CHIKV epidemic. There were excess deaths in almost all age groups, and excess mortality rate was higher among the elderly but was similar between male and female individuals. The overall mortality estimated in the current study (639 deaths) was about four times greater than that obtained through death declarations (160 deaths). Although the aetiological diagnosis of all deaths associated with CHIKV infection is not always possible, already well-known statistical tools can contribute to the evaluation of the impact of CHIKV on mortality and morbidity in the different age groups.

scholarly journals Assessing excess mortality in Vienna and Austria after the first year of the COVID-19 pandemic

2022 ◽  
Author(s):  
Ramon Bauer ◽  
Markus Speringer ◽  
Peter Frühwirt ◽  
Roman Seidl ◽  
Franz Trautinger
Keyword(s):  
Excess Mortality ◽  
Heat Waves ◽  
National Level ◽  
Age Groups ◽  
Prediction Intervals ◽  
First Year ◽  
Expected Number ◽  
Mortality Trends ◽  
The Public ◽  
Definition Of

In Austria, the first confirmed COVID-19 death occurred in early March 2020. Since then, the question as to whether and, if so, to what extent the COVID-19 pandemic has increased overall mortality has been raised in the public and academic discourse. In an effort to answer this question, Statistics Vienna (City of Vienna, Department for Economic Affairs, Labour and Statistics) has evaluated the weekly mortality trends in Vienna, and compared them to the trends in other Austrian provinces. For our analysis, we draw on data from Statistics Austria and the Austrian Agency for Health and Food Safety (AGES), which are published along with data on the actual and the expected weekly numbers of deaths via the Vienna Mortality Monitoring website. Based on the definition of excess mortality as the actual number of reported deaths from all causes minus the expected number of deaths, we calculate the weekly prediction intervals of the expected number of deaths for two age groups (0 to 64 years and 65 years and older). The temporal scope of the analysis covers not only the current COVID-19 pandemic, but also previous flu seasons and summer heat waves. The results show the actual weekly numbers of deaths and the corresponding prediction intervals for Vienna and the other Austrian provinces since 2007. Our analysis underlines the importance of comparing time series of COVID-19-related excess deaths at the sub-national level in order to highlight within-country heterogeneities.

scholarly journals Errata ao artigo “Estimativa do Excesso de Mortalidade Durante a Pandemia COVID-19: Dados Preliminares Portugueses”, publicado em Acta Med Port 2020 Jun;33(6):376-383

2020 ◽  
Vol 33 (6) ◽  
pp. 450
Author(s):  
Paulo Jorge Nogueira ◽  
Miguel De Araújo Nobre ◽  
Paulo Jorge Nicola ◽  
Cristina Furtado ◽  
António Vaz Carneiro
Keyword(s):  
Protective Effect ◽  
Excess Mortality ◽  
Age Groups ◽  
Older Age ◽  
Younger Age ◽  
Summer Holiday ◽  
Overall Mortality

Article published with errors: https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/13928On page 376, in Abstract, paragraph Results, where it reads: ”Despite the inherent uncertainty, it is safe to assume an observed excess mortality of 2400 to 4000 deaths. Excess mortality was associated with older age groups (over age 65).”It should read: “An excess mortality of 2400 to 4000 deaths was observed. Excess mortality was associated with older age groups (over age 65).”On page 376, in Abstract, paragraph Conclusion, where it reads: ”The excess mortality occurred between March 1 and April 22 was 3 to 5 fold higher than what can be explained by the official COVID-19 deaths.”It should read: “Despite the inherent uncertainty, the excess mortality occurred between March 1 and April 22 could be 3.5- to 5-fold higher than what can be explained by the official COVID-19 deaths.”On page 376, in Resumo, paragraph Conclusão, where it reads: “Da análise dos resultados é possível concluir que o excesso de mortalidade ocorrido entre 1 de março e 22 de abril foi 3 a 5 vezes superior ao explicado pelas mortes por COVID-19 reportadas oficialmente.”It should read: “Apesar da incerteza inerente, da análise dos resultados é possível concluir que o excesso de mortalidade ocorrido entre 1 de março e 22 de abril poderá ter sido 3,5 a 5 vezes superior ao explicado pelas mortes por COVID-19 reportadas oficialmente.”On page 377, last line of the first paragraph, where it reads: “If the lockdown had some protective effect on overall mortality, like summer holiday months seem to have, these effects may be observed some, if not all, age groups.”It should read: “If the lockdown had some protective effect on overall mortality, like summer holiday months seem to have, these effects may be observed in all age groups.”On page 377, section Results, third paragraph, last sentence where it reads: “Mortality in the younger age groups was, on average, below the proposed baselines, as hypothesized.”It should read: “Mortality in the younger age groups was, on average, lower than the proposed baselines as theorized.”On page 382, section Conclusion, last sentence, where it reads: “Overall, these results point towards an excess mortality that is associated with and that is 3 to 5-fold higher than the official COVID-19 mortality.” It should read: “Overall, these results point towards an excess mortality that is associated with and that could be 3.5- to 5-fold higher than the official COVID-19 mortality.” Artigo publicado com erros: https://www.actamedicaportuguesa.com/revista/index.php/amp/article/view/13928Na página 376, no Abstract, parágrafo Results, onde se lê: “Despite the inherent uncertainty, it is safe to assume an observed excess mortality of 2400 to 4000 deaths. Excess mortality was associated with older age groups (over age 65).”Deverá ler-se: “An excess mortality of 2400 to 4000 deaths was observed. Excess mortality was associated with older age groups (over age 65).”Na página 376, no Abstract, parágrafo Conclusion, onde se lê: “The excess mortality occurred between March 1 and April 22 was 3 to 5 fold higher than what can be explained by the official COVID-19 deaths."Deverá ler-se: “Despite the inherent uncertainty, the excess mortality occurred between March 1 and April 22 could be 3.5- to 5-fold higher than what can be explained by the official COVID-19 deaths.”Na página 376, no Resumo, parágrafo Conclusão, onde se lê: “Da análise dos resultados é possível concluir que o excesso de mortalidade ocorrido entre 1 de março e 22 de abril foi 3 a 5 vezes superior ao explicado pelas mortes por COVID-19 reportadas oficialmente.”Deverá ler-se: “Apesar da incerteza inerente, da análise dos resultados é possível concluir que o excesso de mortalidade ocorrido entre 1 de março e 22 de abril poderá ter sido 3,5 a 5 vezes superior ao explicado pelas mortes por COVID-19 reportadas oficialmente.”Na página 377, na última linha do primeiro parágrafo, onde se lê: “If the lockdown had some protective effect on overall mortality, like summer holiday months seem to have, these effects may be observed some, if not all, age groups.”Deverá ler-se: “If the lockdown had some protective effect onoverall mortality, like summer holiday months seem to have, these effects may be observed in all age groups.”Na página 377, secção Resultados, terceiro parágrafo última frase, onde se lê: “Mortality in the younger age groups was, on average, below the proposed baselines, as hypothesized.”Deverá ler-se: “Mortality in the younger age groups was, on average, lower than the proposed baselines as theorized.”Na página 382, secção Conclusion, última frase, onde se lê: “Overall, these results point towards an excess mortality that is associated with and that is 3 to 5-fold higher than the official COVID-19 mortality.”Deverá ler-se: “Overall, these results point towards an excess mortality that is associated with and that could be 3.5- to 5-fold higher than the official COVID-19 mortality.”

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