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

eLife ◽  
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.

scholarly journals The World Mortality Dataset: Tracking excess mortality across countries during the COVID-19 pandemic

2021 ◽  
Author(s):  
Ariel Karlinsky ◽  
Dmitry Kobak
Keyword(s):  
Excess Mortality ◽  
Mortality Data ◽  
Objective Indicator ◽  
Death Toll ◽  
The World ◽  
All Cause Mortality ◽  
Order Of Magnitude ◽  
The Impact ◽  
Entire Dataset ◽  
Annual Mortality

AbstractComparing 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 recent average, is widely considered as a more objective indicator of the COVID-19 death toll. However, there has been no central, 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 77 countries, 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 the worst-affected countries the annual mortality increased by over 50%, while in several other countries it decreased by over 5%, presumably due to lockdown measures decreasing the non-COVID mortality. Moreover, we found that while some countries have been reporting the COVID-19 deaths very accurately, many countries have been underreporting their COVID-19 deaths by an order of magnitude or more. Averaging across the entire dataset suggests that the world’s COVID-19 death toll may be at least 1.6 times higher than the reported number of confirmed deaths.

scholarly journals Impact of the COVID-19 pandemic on life expectancy in Madrid (Spain)

2020 ◽  
Author(s):  
Sergi Trias-Llimós ◽  
Usama Bilal
Keyword(s):  
Life Expectancy ◽  
Surveillance System ◽  
Excess Mortality ◽  
Daily Mortality ◽  
Life Expectancy At Birth ◽  
The World ◽  
Using Data ◽  
The Impact ◽  
Mortality Surveillance ◽  
Annual Mortality

The COVID-19 pandemic is causing substantial increases in mortality across populations, potentially causing stagnation or decline in life expectancy. We explored this idea by examining the impact of excess mortality linked to the COVID-19 crisis on life expectancy in the region of Madrid (Spain). Using data from the Daily Mortality Surveillance System (MoMo), we calculated excess mortality (death counts) for the weeks 10th to 14th in 2020 using data on expected and observed mortality, assuming no further excess mortality during the rest of the year. The expected annual mortality variation was +6%, +21% and +25% among men aged under 65, between 65 and 74 and over 75, respectively, and +5%, +13%, and 18% for women, respectively. This excess mortality during weeks 10th to 14th resulted in a life expectancy at birth decline of 1.6 years among men and 1.1 years among women. These estimates confirm that Madrid and other severely hit regions in the world may face substantial life expectancy declines.

scholarly journals Good Democratic Governance Can Combat COVID-19

2021 ◽  
Author(s):  
Susumu Annaka
Keyword(s):  
New Zealand ◽  
Excess Mortality ◽  
Democratic Governance ◽  
Mortality Data ◽  
Political Regimes ◽  
Government Effectiveness ◽  
Reported Data ◽  
The Impact

Some scholars argue that democratic countries are in crisis during the COVID-19 pandemic and authoritarian countries tend to combat COVID-19. However, these studies are usually based on reported data susceptible to manipulation and often overlook successful cases such as New Zealand and Taiwan, which are considered to have higher levels of government effectiveness. Using excess mortality data from 78 countries, this study analyzed the impact of government effectiveness and its relationship with political regimes. The results revealed that democratic countries with higher government effectiveness can reduce COVID-19 excess mortality. This study suggests that democratic countries need not give up freedom and need to improve government effectiveness to combat COVID-19.

scholarly journals Good Democratic Governance Can Combat COVID-19-Excess Mortality Analysis

2021 ◽  
Author(s):  
Susumu Annaka
Keyword(s):  
New Zealand ◽  
Excess Mortality ◽  
Democratic Governance ◽  
Mortality Data ◽  
Political Regimes ◽  
Government Effectiveness ◽  
Reported Data ◽  
The Impact ◽  
Mortality Analysis

Some scholars argue that democratic countries are in crisis during the COVID-19 pandemic and authoritarian countries tend to combat COVID-19. However, these studies are usually based on reported data susceptible to manipulation and often overlook successful cases such as New Zealand and Taiwan, which are considered to have higher levels of government effectiveness. Using excess mortality data from 78 countries, this study analyzed the impact of government effectiveness and its relationship with political regimes. The results revealed that democratic countries with higher government effectiveness can reduce COVID-19 excess mortality. This study suggests that democratic countries need not give up freedom and need to improve government effectiveness to combat COVID-19.

scholarly journals Impact of the COVID-19 pandemic on life expectancy in Madrid (Spain)

2020 ◽  
Author(s):  
Sergi Trias-Llimós ◽  
Usama Bilal
Keyword(s):  
Life Expectancy ◽  
Surveillance System ◽  
Excess Mortality ◽  
Daily Mortality ◽  
Life Expectancy At Birth ◽  
The World ◽  
Using Data ◽  
The Impact ◽  
Mortality Surveillance ◽  
Annual Mortality

The COVID-19 pandemic is causing substantial increases in mortality across populations, potentially causing stagnation or decline in life expectancy. We explored this idea by examining the impact of excess mortality linked to the COVID-19 crisis on life expectancy in the region of Madrid (Spain). Using data from the Daily Mortality Surveillance System (MoMo), we calculated excess mortality (death counts) for the weeks 10th to 14th in 2020 using data on expected and observed mortality, assuming no further excess mortality during the rest of the year. The expected annual mortality variation was +6%, +21% and +25% among men aged under 65, between 65 and 74 and over 75, respectively, and +5%, +13%, and 18% for women, respectively. This excess mortality during weeks 10th to 14th resulted in a life expectancy at birth decline of 1.6 years among men and 1.1 years among women. These estimates confirm that Madrid and other severely hit regions in the world may face substantial life expectancy declines.

scholarly journals Influenza-attributable deaths, Canada 1990–1999

2007 ◽  
Vol 135 (7) ◽  
pp. 1109-1116 ◽  
Author(s):  
D. L. SCHANZER ◽  
T. W. S. TAM ◽  
J. M. LANGLEY ◽  
B. T. WINCHESTER
Keyword(s):  
Excess Mortality ◽  
Influenza Season ◽  
Vital Statistics ◽  
Attributable Mortality ◽  
Mortality Data ◽  
Poisson Regression Model ◽  
Severe Influenza ◽  
All Cause Mortality ◽  
Specific Mortality ◽  
The Impact

SUMMARYThe number of deaths attributable to influenza is believed to be considerably higher than the number certified by vital statistics registration as due to influenza. Weekly mortality data for Canada from the 1989/1990 to the 1998/1999 influenza seasons were analysed by cause of death, age group, and place of death to estimate the impact of influenza on mortality. A Poisson regression model was found to accurately predict all-cause, as well as cause-specific mortality, as a function of influenza-certified deaths, after controlling for seasonality, and trend. Influenza-attributable deaths were calculated as predicted less baseline-predicted deaths. In summary, throughout the 1990s there were on average just under 4000 deaths attributable to influenza annually (for an influenza-attributable mortality rate of 13/100 000 persons), varying from no detectable excess mortality for the 1990/1991 influenza season, to 6000–8000 influenza-attributable deaths for the more severe influenza seasons of 1997/1998 and 1998/1999. On average, 8% (95% CI 7–10) of influenza-attributable deaths were certified as influenza, although this percentage varied from 4% to 12% from year to year. Only 15% of the influenza-attributable deaths were certified as pneumonia, and for all respiratory causes, 40%. Deaths were distributed over most causes. The weekly pattern of influenza-certified deaths was a good predictor of excess all-cause mortality.

scholarly journals Risk factors for excess all-cause mortality during the first wave of the COVID-19 pandemic in England: A retrospective cohort study of primary care data

PLoS ONE ◽  
2021 ◽  
Vol 16 (12) ◽  
pp. e0260381
Author(s):  
Iain M. Carey ◽  
Derek G. Cook ◽  
Tess Harris ◽  
Stephen DeWilde ◽  
Umar A. R. Chaudhry ◽  
...  
Keyword(s):  
Risk Factors ◽  
Primary Care ◽  
Excess Mortality ◽  
Total Mortality ◽  
Individual Risk ◽  
Mortality Data ◽  
All Cause Mortality ◽  
Specific Mortality ◽  
Mortality Ratio ◽  
The Impact

Background The COVID-19 pandemic’s first wave in England during spring 2020 resulted in an approximate 50% increase in all-cause mortality. Previously, risk factors such as age and ethnicity, were identified by studying COVID-related deaths only, but these were under-recorded during this period. Objective To use a large electronic primary care database to estimate the impact of risk factors (RFs) on excess mortality in England during the first wave, compared with the impact on total mortality during 2015–19. Methods Medical history, ethnicity, area-based deprivation and vital status data were extracted for an average of 4.8 million patients aged 30–104 years, for each year between 18-March and 19-May over a 6-year period (2015–2020). We used Poisson regression to model total mortality adjusting for age and sex, with interactions between each RF and period (pandemic vs. 2015–19). Total mortality during the pandemic was partitioned into "usual" and "excess" components, assuming 2015–19 rates represented "usual" mortality. The association of each RF with the 2020 "excess" component was derived as the excess mortality ratio (EMR), and compared with the usual mortality ratio (UMR). Results RFs where excess mortality was greatest and notably higher than usual were age >80, non-white ethnicity (e.g., black vs. white EMR = 2.50, 95%CI 1.97–3.18; compared to UMR = 0.92, 95%CI 0.85–1.00), BMI>40, dementia, learning disability, severe mental illness, place of residence (London, care-home, most deprived). By contrast, EMRs were comparable to UMRs for sex. Although some co-morbidities such as cancer produced EMRs significantly below their UMRs, the EMRs were still >1. In contrast current smoking has an EMR below 1 (EMR = 0.80, 95%CI 0.65–0.98) compared to its UMR = 1.64. Conclusions Studying risk factors for excess mortality during the pandemic highlighted differences from studying cause-specific mortality. Our approach illustrates a novel methodology for evaluating a pandemic’s impact by individual risk factor without requiring cause-specific mortality data.

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.

Excess Mortality During the COVID-19 Pandemic in Philadelphia

2021 ◽  
pp. e1-e6
Author(s):  
Megan Todd ◽  
Meagan Pharis ◽  
Sam P. Gulino ◽  
Jessica M. Robbins ◽  
Cheryl Bettigole
Keyword(s):  
Public Health ◽  
Excess Mortality ◽  
Poisson Model ◽  
People Of Color ◽  
Mortality Data ◽  
Registration System ◽  
Vital Registration System ◽  
All Cause Mortality ◽  
Race Ethnicity ◽  
Excess Deaths

Objectives. To estimate excess all-cause mortality in Philadelphia, Pennsylvania, during the COVID-19 pandemic and understand the distribution of excess mortality in the population. Methods. With a Poisson model trained on recent historical data from the Pennsylvania vital registration system, we estimated expected weekly mortality in 2020. We compared these estimates with observed mortality to estimate excess mortality. We further examined the distribution of excess mortality by age, sex, and race/ethnicity. Results. There were an estimated 3550 excess deaths between March 22, 2020, and January 2, 2021, a 32% increase above expectations. Only 77% of excess deaths (n=2725) were attributed to COVID-19 on the death certificate. Excess mortality was disproportionately high among older adults and people of color. Sex differences varied by race/ethnicity. Conclusions. Excess deaths during the pandemic were not fully explained by COVID-19 mortality; official counts significantly undercount the true death toll. Far from being a great equalizer, the COVID-19 pandemic has exacerbated preexisting disparities in mortality by race/ethnicity. Public Health Implications. Mortality data must be disaggregated by age, sex, and race/ethnicity to accurately understand disparities among groups. (Am J Public Health. Published online ahead of print June 10, 2021: e1–e6. https://doi.org/10.2105/AJPH.2021.306285 )

Colonization, Decolonization, and Power: Ruptures and Critical Junctures Out of Dominance

2016 ◽  
Author(s):  
James H. Liu ◽  
Felicia Pratto
Keyword(s):  
Social Justice ◽  
National Identity ◽  
New Zealand ◽  
Social Structure ◽  
Critical Junctures ◽  
The Social ◽  
The World ◽  
European Colonization ◽  
Historical Trajectory ◽  
The Impact

Colonization and decolonization are theorized at the intersection of Critical Junctures Theory and Power Basis Theory. This framework allows human agency to be conceptualized at micro-, meso-, and macro-levels, where individuals act on behalf of collectives. Their actions decide whether critical junctures in history (moments of potential for substantive change) result in continuity (no change), anchoring (continuity amid change with new elements), or rupture. We apply this framework to European colonization of the world, which is the temporal scene for contemporary social justice. Several critical junctures in New Zealand history are analyzed as part of its historical trajectory and narrated through changes in its symbology (system of meaning) and technology of state, as well as the identity space it encompasses (indigenous Māori and British colonizers). The impact of this historical trajectory on the social structure of New Zealand, including its national identity and government, is considered and connected to the overarching theoretical framework.

Sign in / Sign up

Export Citation Format

Share Document