High excess mortality in areas with young and socially vulnerable populations during the COVID-19 outbreak in Stockholm Region, Sweden

IntroductionWe aimed to describe the distribution of excess mortality (EM) during the first weeks of the COVID-19 outbreak in the Stockholm Region, Sweden, according to age, sex and sociodemographic context.MethodsWeekly all-cause mortality data were obtained from Statistics Sweden for the period 1 January 2015 to 17 May 2020. EM during the first 20 weeks of 2020 was estimated by comparing observed mortality rates with expected mortality rates during the five previous years (N=2 379 792). EM variation by socioeconomic status (tertiles of income, education, Swedish-born, gainful employment) and age distribution (share of 70+-year-old persons) was explored based on Demographic Statistics Area (DeSO) data.ResultsEM was first detected during the week of 23–29 March 2020. During the peak week of the epidemic (6–12 April 2020), an EM of 150% was observed (152% in 80+-year-old women; 183% in 80+-year-old men). During the same week, the highest EM was observed for DeSOs with lowest income (171%), lowest education (162%), lowest share of Swedish-born (178%) and lowest share of gainfully employed residents (174%). EM was further increased in areas with higher versus lower proportion of younger people (magnitude of increase: 1.2–1.7 times depending on socioeconomic measure).ConclusionLiving in areas characterised by lower socioeconomic status and younger populations was linked to excess mortality during the COVID-19 pandemic in the Stockholm Region. These conditions might have facilitated viral spread. Our findings highlight the well-documented vulnerability linked to increasing age and sociodemographic context for COVID-19–related death.

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High excess mortality during the COVID-19 outbreak in Stockholm Region areas with young and socially vulnerable populations

10.1101/2020.07.07.20147983 ◽

2020 ◽

Author(s):

Amaia Calderón-Larrañaga ◽

Davide L Vetrano ◽

Debora Rizzuto ◽

Tom Bellander ◽

Laura Fratiglioni ◽

...

Keyword(s):

Socioeconomic Status ◽

Excess Mortality ◽

Age Distribution ◽

Fold Increase ◽

Mortality Rates ◽

Individual Risk ◽

Mortality Data ◽

Gainful Employment ◽

Viral Spread ◽

The Individual

AbstractBackgroundWe aimed to describe the distribution of excess mortality (EM) during the first weeks of the COVID-19 outbreak in the Stockholm Region, Sweden, according to individual age and sex, and the sociodemographic contextMethodsWeekly all-cause mortality data were obtained from Statistics Sweden for the period 01/01/2015 to 17/05/2020. EM during the first 20 weeks of 2020 was estimated by comparing observed mortality rates with expected mortality rates during the five previous years (N=2,379,792). EM variation by socioeconomic status (tertiles of income, education, Swedish-born, gainful employment) and age distribution (share of 70+ year-old persons) was explored based on Demographic Statistics Area (DeSO) data.FindingsAn EM was first detected during the week of March 23-29 2020. During the peaking week of the epidemic (6-12 April 2020), an EM of 160% was observed: 211% in 80+ year-old women; 179% in 80+ year-old men. During the same week, the highest EM was observed for DeSOs with lowest income (171%), lowest education (162%), lowest share of Swedish-born (178%), and lowest share of gainfully employed (174%). There was a 1.2 to 1.7-fold increase in EM between those areas with a higher vs. lower proportion of young people.InterpretationLiving in areas with lower socioeconomic status and younger populations is linked to COVID-19 EM. These conditions might have facilitated the viral spread. Our findings add to the well-known biological vulnerability linked to increasing age, the relevance of the sociodemographic context when estimating the individual risk to COVID-19.FundingNone.

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Incidence, Characteristics, and Outcome of COVID-19 in Adults on Kidney Replacement Therapy: A Regionwide Registry Study

Journal of the American Society of Nephrology ◽

10.1681/asn.2020060875 ◽

2020 ◽

pp. ASN.2020060875

Author(s):

Johan De Meester ◽

Dirk De Bacquer ◽

Maarten Naesens ◽

Bjorn Meijers ◽

Marie M. Couttenye ◽

...

Keyword(s):

General Population ◽

Excess Mortality ◽

Mortality Rates ◽

Incidence Rates ◽

Registry Study ◽

Additional Risk ◽

Mortality Burden ◽

Kidney Replacement Therapy ◽

Expected Mortality ◽

Chronic Comorbidities

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection disproportionally affects frail, elderly patients and those with multiple chronic comorbidities. Whether patients on RRT have an additional risk because of their specific exposure and complex immune dysregulation is controversial.MethodsTo describe the incidence, characteristics, and outcomes of SARS-CoV-2 infection, we conducted a prospective, multicenter, region-wide registry study in adult patients on RRT versus the general population from March 2 to May 25, 2020. This study comprised all patients undergoing RRT in the Flanders region of Belgium, a country that has been severely affected by coronavirus disease 2019 (COVID-19).Results At the end of the epidemic wave, crude and age-standardized cumulative incidence rates of SARS-CoV-2 infection were 5.3% versus 2.5%, respectively, among 4297 patients on hemodialysis, and 1.4% versus 1.6%, respectively, among 3293 patients with kidney transplants (compared with 0.6% in the general population). Crude and age-standardized cumulative mortality rates were 29.6% versus 19.9%, respectively, among patients on hemodialysis, and 14.0% versus 23.0%, respectively, among patients with transplants (compared with 15.3% in the general population). We found no excess mortality in the hemodialysis population when compared with mean mortality rates during the same 12-week period in 2015–2019 because COVID-19 mortality was balanced by lower than expected mortality among uninfected patients. Only 0.18% of the kidney transplant population died of SARS-CoV-2 infection.ConclusionsMortality associated with SARS-CoV-2 infection is high in patients on RRT. Nevertheless, the epidemic’s overall effect on the RRT population remained remarkably limited in Flanders. Calculation of excess mortality and age standardization provide a more reliable picture of the mortality burden of COVID-19 among patients on RRT.

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Pancreatic cancer: Do disparities in mortality rates exist with respect to socioeconomic status?

Journal of Clinical Oncology ◽

10.1200/jco.2020.38.15_suppl.e19007 ◽

2020 ◽

Vol 38 (15_suppl) ◽

pp. e19007-e19007

Author(s):

Richard Stephen Sheppard ◽

Adewumi Adekunle ◽

Stefani Beale ◽

Janet Joseph ◽

Gerald Fletcher ◽

...

Keyword(s):

Pancreatic Cancer ◽

Socioeconomic Status ◽

Mortality Rates ◽

Ordinary Least Squares ◽

Mortality Data ◽

P Value ◽

Malignant Neoplasms ◽

Median Income ◽

Survival Times ◽

Zip Code

e19007 Background: Pancreatic cancer continues to have one of the highest mortality rates among major cancer diagnoses with rates greater than 90 percent for all stages and with five year survival rates below 10 percent. With access to treatment modalities such as chemo-radiation, staged surgical interventions and targeted therapies, survival times have increased but due to the costs of these procedures, they may not be accessible to all members of society. Recent studies have shown that lower socioeconomic status is associated with higher mortality rates and lower survival times. With this study we aim to investigate if disparities exist among socioeconomic classes, based on zip code location, in a major multi-ethnic metropolitan city using census data. Methods: Malignant neoplasm mortality data at the ZIP code level was gathered from the New York City Department of Health Vital Statistics Mortality Data from years 2009-2011. NYC population data was gathered from the U.S. Census Bureau 2010 decennial census. We used ordinary least squares regression to assess the independent association between neighborhood median income and neighborhood mortality from malignant neoplasms arising from the pancreas. Results: In 2009-2011, 2,527 deaths from malignant neoplasms arising from the pancreas were recorded across NYC. There is no statistically significant correlation between neighborhood median income and age-adjusted mortality from malignant neoplasms arising from the pancreas for males and for females. For males, there was an R-squared of 0.001721 ( P-value > 0.05). For females, there was an adjusted adjusted R-squared of 9.818e-05 ( P-value > 0.05). Conclusions: Neighborhood median income is not associated with an increase in mortality rate with respect to neoplasms arising from the pancreas.

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Tracking excess mortality across countries during the COVID-19 pandemic with the World Mortality Dataset

eLife ◽

10.7554/elife.69336 ◽

2021 ◽

Vol 10 ◽

Author(s):

Ariel Karlinsky ◽

Dmitry Kobak

Keyword(s):

New Zealand ◽

Excess Mortality ◽

Mortality Data ◽

Objective Indicator ◽

Death Toll ◽

The World ◽

All Cause Mortality ◽

Expected Mortality ◽

The Impact ◽

Annual Mortality

Comparing the impact of the COVID-19 pandemic between countries or across time is difficult because the reported numbers of cases and deaths can be strongly affected by testing capacity and reporting policy. Excess mortality, defined as the increase in all-cause mortality relative to the expected mortality, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no global, frequently-updated repository of the all-cause mortality data across countries. To fill this gap, we have collected weekly, monthly, or quarterly all-cause mortality data from 94 countries and territories, openly available as the regularly-updated World Mortality Dataset. We used this dataset to compute the excess mortality in each country during the COVID-19 pandemic. We found that in several worst-affected countries (Peru, Ecuador, Bolivia, Mexico) the excess mortality was above 50% of the expected annual mortality. At the same time, in several other countries (Australia, New Zealand) mortality during the pandemic was below the usual level, presumably due to social distancing measures decreasing the non-COVID infectious mortality. Furthermore, we found that while many countries have been reporting the COVID-19 deaths very accurately, some countries have been substantially underreporting their COVID-19 deaths (e.g. Nicaragua, Russia, Uzbekistan), sometimes by two orders of magnitude (Tajikistan). Our results highlight the importance of open and rapid all-cause mortality reporting for pandemic monitoring.

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Excess mortality in Italy: Should we care about low influenza vaccine uptake?

Scandinavian Journal of Public Health ◽

10.1177/1403494817720102 ◽

2017 ◽

Vol 46 (2) ◽

pp. 170-174 ◽

Cited By ~ 3

Author(s):

Francia Fausto ◽

Pandolfi Paolo ◽

Odone Anna ◽

Signorelli Carlo

Keyword(s):

Excess Mortality ◽

Local Level ◽

Frailty Index ◽

Age Distribution ◽

The Elderly ◽

Vaccine Uptake ◽

Elderly Subjects ◽

Mortality Data ◽

Risk Of Death ◽

Increased Risk

Aims: The aims of this study were to explore 2015 mortality data further and to assess excess deaths’ determinants. Methods: We analysed data from a large metropolitan area in the north of Italy, the city of Bologna. We took advantage of a comprehensive local-level database and merged three different data sources to analitically explore reported 2014–2015 excess mortality and its determinants. Effect estimates were derived from multivariable Poisson regression analysis, according to vaccination status and frailty index. Results: We report 9.8% excess mortality in 2015 compared to 2014, with seasonal and age distribution patterns in line with national figures. All-cause mortality in the elderly population is 36% higher (risk ratio [RR]=1.36, 95% confidence interval [CI] 1.27–1.45) in subjects not vaccinated against seasonal flu compared to vaccinated subjects, with risk of death for influenza or pneumonia being 43% higher (RR=1.43, 95% CI 1.02–2.00) in unvaccinated subjects. Conclusions: Reported excess mortality’s determinants in Italy should be further explored. Elderly subjects not vaccinated against the flu appear to have increased risk of all-cause and cause-specific mortality compared to vaccinated subjects after accounting for possible confounders. Our findings raise awareness of the need to promote immunisation against the flu among elder populations and offer insights to plan and implement effective public-health interventions.

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Excess mortality in England and Wales during the first wave of the COVID-19 pandemic

Journal of Epidemiology & Community Health ◽

10.1136/jech-2020-214764 ◽

2020 ◽

pp. jech-2020-214764 ◽

Cited By ~ 3

Author(s):

Evangelos Kontopantelis ◽

Mamas A Mamas ◽

John Deanfield ◽

Miqdad Asaria ◽

Tim Doran

Keyword(s):

Excess Mortality ◽

Negative Binomial ◽

Mortality Rates ◽

Mortality Data ◽

Public Health Response ◽

England And Wales ◽

South West ◽

Health Response ◽

West Midlands ◽

National Public Health

BackgroundDeaths during the COVID-19 pandemic result directly from infection and exacerbation of other diseases and indirectly from deferment of care for other conditions, and are socially and geographically patterned. We quantified excess mortality in regions of England and Wales during the pandemic, for all causes and for non-COVID-19-associated deaths.MethodsWeekly mortality data for 1 January 2010 to 1 May 2020 for England and Wales were obtained from the Office of National Statistics. Mean-dispersion negative binomial regressions were used to model death counts based on pre-pandemic trends and exponentiated linear predictions were subtracted from: (i) all-cause deaths and (ii) all-cause deaths minus COVID-19 related deaths for the pandemic period (week starting 7 March, to week ending 8 May).FindingsBetween 7 March and 8 May 2020, there were 47 243 (95% CI: 46 671 to 47 815) excess deaths in England and Wales, of which 9948 (95% CI: 9376 to 10 520) were not associated with COVID-19. Overall excess mortality rates varied from 49 per 100 000 (95% CI: 49 to 50) in the South West to 102 per 100 000 (95% CI: 102 to 103) in London. Non-COVID-19 associated excess mortality rates ranged from −1 per 100 000 (95% CI: −1 to 0) in Wales (ie, mortality rates were no higher than expected) to 26 per 100 000 (95% CI: 25 to 26) in the West Midlands.InterpretationThe COVID-19 pandemic has had markedly different impacts on the regions of England and Wales, both for deaths directly attributable to COVID-19 infection and for deaths resulting from the national public health response.

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Evaluation of Strategies to Fight COVID-19: The French Paradigm

Journal of Clinical Medicine ◽

10.3390/jcm10132942 ◽

2021 ◽

Vol 10 (13) ◽

pp. 2942

Author(s):

Audrey Giraud-Gatineau ◽

Philippe Gautret ◽

Philippe Colson ◽

Hervé Chaudet ◽

Didier Raoult

Keyword(s):

Surveillance System ◽

Excess Mortality ◽

Age Distribution ◽

European Countries ◽

Biological Assessment ◽

Epidemiological Surveillance ◽

Mortality Data ◽

Age Group ◽

All Cause Mortality ◽

Epidemiological Surveillance System

(1) Background: We collected COVID-19 mortality data and the age distribution of the deceased in France and other European countries, as well as specifically in the cities of Paris and Marseille, and compared them. (2) Methods: Data on mortality related to COVID-19 and the associated age distribution were collected from government institutions in various European countries. In France, data were obtained from INSEE and Santé Publique France. All-cause mortality was also examined in order to study potential excess mortality using EuroMOMO. The Marseille data came from the epidemiological surveillance system. (3) Results: France is one of the European countries most impacted by COVID-19. Its proportion of deaths in people under 60 years of age is higher (6.5%) than that of Italy (4.6%) or Spain (4.7%). Excess mortality (5% more deaths) was also observed. Ile-de-France and the Grand-Est are the two French regions with the highest mortality. The proportion of deaths in the under-60 age group was considerable in Ile-de-France (9.9% vs. 4.5% in the Southern region). There are significantly higher numbers of patients hospitalized, in intensive care and deceased in Paris than in Marseille. (4) Conclusions: No patient management, i.e., from screening to diagnosis, including biological assessment and clinical examination, likely explains the high mortality associated with COVID-19.

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Mortality in Norway and Sweden before and after the Covid-19 outbreak: a cohort study

10.1101/2020.11.11.20229708 ◽

2020 ◽

Author(s):

Frederik E Juul ◽

Henriette C Jodal ◽

Ishita Barua ◽

Erle Refsum ◽

Ørjan Olsvik ◽

...

Keyword(s):

Excess Mortality ◽

Mortality Rates ◽

List Type ◽

School Closures ◽

Epidemic Period ◽

All Cause Mortality ◽

Specific Mortality ◽

Before And After ◽

Rate Ratios ◽

Expected Mortality

AbstractObjectivesNorway and Sweden are similar countries regarding ethnicity, socioeconomics and health care. To combat Covid-19, Norway implemented extensive measures such as school closures and lock-downs, while Sweden has been criticised for relaxed measures against Covid-19. We compared the effect of the different national strategies on all-cause and Covid-19 associated mortality.DesignRetrospective cohort.SettingThe countries Norway and Sweden.ParticipantsAll inhabitants.Main outcome measuresWe calculated weekly mortality rates (MR) with 95% confidence intervals (CI) per 100,000 individuals as well as mortality rate ratios (MRR) comparing the epidemic year (29th July, 2019 to 26th July, 2020) to the four preceding years (July 2015 to July 2019). We also compared Covid-19 associated deaths and mortality rates for the weeks of the epidemic in Norway and Sweden (16th March to 26th July, 2020).ResultsIn Norway, mortality rates were stable during the first three 12-month periods of 2015/16; 2016/17 and 2017/18 (MR 14.8 to 15.1 per 100,000), and slightly lower in the two most recent periods including during epidemic period (2018/19 and 2019/20; 14.5 per 100,000). In Sweden, all-cause mortality was stable during the first three 12-month periods of 2015/16; 2016/17 and 2017/18 (MR 17.2 to 17.5 per 100,000), but lower in the year 2018/19 immediately preceding the epidemic (16.2 per 100,000). Covid-19 associated mortality rates were 0.2 per 100,000 (95%CI 0.1 to 0.4) in Norway and 2.9 (95%CI 1.9 to 3.9) in Sweden. The increase in mortality was confined to individuals in 70 years or older.ConclusionsAll-cause mortality remained unaltered in Norway. In Sweden, the observed increase in all-cause mortality during Covid-19 was partly due to a lower than expected mortality preceding the epidemic and the observed excess mortality, was followed by a lower than expected mortality after the first Covid-19 wave. This may suggest mortality displacement.Strengths and limitations of this studyCompares two similar contries in all aspects but the handling of the Covid-19 epidemicEvaluates the mortality for several years before and during the epidemicProvides a possible explanation of the observed mortality changesDiscusses the socioeconomic effects of the different strategies in the two countriesDoes not evaluate cause-specific mortality

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Racial Disparities in COVID-19 and Excess Mortality in Minnesota

10.31235/osf.io/rs4ph ◽

2020 ◽

Author(s):

Elizabeth Wrigley-Field ◽

Sarah Garcia ◽

Jonathon P. Leider ◽

Christopher Robertson ◽

Rebecca Wurtz

Keyword(s):

United States ◽

Natural History ◽

Racial Disparities ◽

Excess Mortality ◽

Age Distribution ◽

The United States ◽

Mortality Rates ◽

Racial Groups ◽

Communities Of Color ◽

History Of

The COVID-19 pandemic has produced vastly disproportionate deaths for communities of color in the United States. Minnesota seemingly stands out as an exception to this national pattern, with white Minnesotans accounting for 80% of the population and 82% of COVID-19 deaths. We examine confirmed COVID mortality alongside deaths indirectly attributable to the pandemic -- ‘excess mortality’ -- in Minnesota. This analysis reveals profound racial disparities: age-adjusted excess mortality rates for whites are exceeded by a factor of 2.8-5.3 for all other racial groups, with the highest rates among Black, Latino, and Native Minnesotans. The seemingly small disparities in COVID deaths in Minnesota reflect the interaction of three factors: the natural history of the disease whose early toll was heavily concentrated in nursing homes; an exceptionally divergent age distribution in the state; and a greatly different proportion of excess mortality captured in confirmed-COVID rates for white Minnesotans compared with most other groups.

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Abstract 2630: Lower Socioeconomic Status is Associated with Higher Rates of First Hospitalization for Stroke and Subsequent Case Fatality: A Population Study of 5.1 Million People in Scotland 1985–2005

Circulation ◽

10.1161/circ.118.suppl_18.s_756-a ◽

2008 ◽

Vol 118 (suppl_18) ◽

Author(s):

Pardeep S Jhund ◽

James Lewsey ◽

Michelle Gillies ◽

James Chalmers ◽

Adam Redpath ◽

...

Keyword(s):

Socioeconomic Status ◽

Cox Regression ◽

Case Fatality ◽

Mortality Data ◽

Lower Socioeconomic Status ◽

Stroke Subtype ◽

Model Case ◽

Stroke Incidence ◽

Hospitalization Rates ◽

Lower Socioeconomic

Introduction Small, age or geographically restricted studies suggest that stroke incidence and case fatality increase with lower socioeconomic status (SES). We examined the relationship between SES and stroke incidence and case fatality in a whole country. Methods Linked morbidity and mortality data were used to identify all first hospitalizations in Scotland where stroke was coded in the principal diagnostic position at discharge from 1986 –2005. SES was measured using the quintiles of Carstairs index of deprivation (quintile 1= most affluent, 5=most deprived). Age and sex specific incidence rates by SES were calculated. Cox regression was used to model case-fatality by SES at 30 days, 1 and 5 years adjusted for comorbidities. Results From 1986 –2005 73,676 men and 88,808 women were admitted with a first stroke. In men (women) 11575 (14713) occurred in individuals in deprivation quintile 1 and 15800 (19022) in quintile 5. Rates of stroke were higher in the most deprived vs the most affluent individuals. In 1986, in men aged <55, 55– 64, 65–74, 75– 84 and >85 years, the rate ratios (deprived vs affluent) were 2.05(1.46 –2.87), 1.82(1.38 –2.38), 1.56(1.27–1.92), 1.06(0.87–1.31) and 1.16(0.78 –1.74) respectively. In women the respective ratios were 2.57(1.71–3.87), 2.06(1.50 –2.83), 1.62(1.32–1.99), 1.27(1.09 –1.49) and 1.36(1.07–1.74). These gradients persisted from 1986 to2005 in both men and women and in all ages. Adjusted case fatality did not vary by SES at 30 days,, HR (deprived vs affluent) = 1.01(95%CI 0.96 –1.06) in men, 1.03(0.99 –1.08) in women. However, at 30 days-1 year the HR was 1.17(1.09 –1.24) in men and 1.11 (1.05–1.17) in women. At 1–5 years the HRs were 1.20(1.13–1.26) in men and 1.14(1.09 –1.20) in women. The effect of SES on case fatality and hospitalization rates did not vary by year or stroke subtype (p for interactions >0.05). Conclusion Not only are stroke hospitalization rates highest in the most deprived individuals, but adjusted longer term case fatality after discharge is also higher. There is no evidence that this disparity is decreasing over time.

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