Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21.
Ontology highlight
ABSTRACT:
SUBMITTER: COVID-19 Excess Mortality Collaborators
PROVIDER: S-EPMC8912932 | biostudies-literature | 2022 Apr
REPOSITORIES: biostudies-literature
Publications
Estimating excess mortality due to the COVID-19 pandemic: a systematic analysis of COVID-19-related mortality, 2020-21.
Lancet (London, England) 20220310 10334
<h4>Background</h4>Mortality statistics are fundamental to public health decision making. Mortality varies by time and location, and its measurement is affected by well known biases that have been exacerbated during the COVID-19 pandemic. This paper aims to estimate excess mortality from the COVID-19 pandemic in 191 countries and territories, and 252 subnational units for selected countries, from Jan 1, 2020, to Dec 31, 2021.<h4>Methods</h4>All-cause mortality reports were collected for 74 count ...[more]
Similar Datasets
Project description:BackgroundThe persistent coronavirus disease 2019 (COVID-19) pandemic has had direct and indirect effects on mortality, making it essential to analyze excess mortality to fully understand the impact of the pandemic. In this study, we constructed a mathematical model using number of deaths from Statistics Korea and analyzed excess mortality between 2020 and 2022 according to age, sex, and dominant severe acute respiratory syndrome coronavirus 2 variant period.MethodsNumber of all-cause deaths between 2010 and 2022 were obtained from the annual cause-of-death statistics provided by Statistics Korea. COVID-19 mortality data were acquired from the Korea Disease Control and Prevention Agency. A multivariate linear regression model with seasonal effect, stratified by sex and age, was used to estimate the number of deaths in the absence of COVID-19. The estimated excess mortality rate was calculated.ResultsExcess mortality was not significant between January 2020 and October 2021. However, it started to increase monthly from November 2021 and reached its highest point during the omicron-dominant period. Specifically, in March and April 2022, during the omicron BA.1/BA.2-dominant period, the estimated median values for excess mortality were the highest at 17,634 and 11,379, respectively. Both COVID-19-related deaths and excess mortality increased with age. A notable increase in excess mortality was observed in individuals aged ≥ 65 years. In the context of excess mortality per 100,000 population based on the estimated median values in March 2022, the highest numbers were found among males and females aged ≥ 85 years at 1,048 and 910, respectively.ConclusionThis study revealed that the prolonged COVID-19 pandemic coupled with its high transmissibility not only increased COVID-19-related deaths but also had a significant impact on overall mortality rates, especially in the elderly. Therefore, it is crucial to concentrate healthcare resources and services on the elderly and ensure continued access to healthcare services during pandemics. Establishing an excess mortality monitoring system in the early stages of a pandemic is necessary to understand the impact of infectious diseases on mortality and effectively evaluate pandemic response policies.
| S-EPMC11496562 | biostudies-literature
Project description:Excess mortalities are a more accurate indicator of true COVID-19 disease burden. This study aims to investigate levels of excess all-cause mortality and their geographic, age and sex distributions between January 2020-September 2021. National mortality data between January 2016 and September 2021 from the Department of Statistics Malaysia was utilised. Baseline mortality was estimated using the Farrington algorithm and data between 1 January 2016 and 31 December 2019. The occurrence of excess all-cause mortality by geographic-, age- and sex-stratum was examined from 1 January 2020 to 30 September 2021. A sub-analysis was also conducted for road-traffic accidents, ethnicity and nationality. Malaysia had a 5.5-23.7% reduction in all-cause mortality across 2020. A reversal is observed in 2021, with an excess of 13.0-24.0%. Excess mortality density is highest between July and September 2021. All states and sexes reported excess trends consistent with the national trends. There were reductions in all all-cause mortalities in individuals under the age of 15 (0.4-8.1%) and road traffic accident-related mortalities (36.6-80.5%). These reductions were higher during the first Movement Control Order in 2020. Overall, there appears to be a reduction in all-cause mortality for Malaysia in 2020. This trend is reversed in 2021, with excess mortalities being observed. Surveillance of excess mortalities can allow expedient detection of aberrant events allowing timely health system and public health responses.
| S-EPMC9807979 | biostudies-literature
Project description:Estimating excess mortality is challenging. The metric depends on the expected mortality level, which can differ based on given choices, such as the method and the time series length used to estimate the baseline. However, these choices are often arbitrary, and are not subject to any sensitivity analysis. We bring to light the importance of carefully choosing the inputs and methods used to estimate excess mortality. Drawing on data from 26 countries, we investigate how sensitive excess mortality is to the choice of the mortality index, the number of years included in the reference period, the method, and the time unit of the death series. We employ two mortality indices, three reference periods, two data time units, and four methods for estimating the baseline. We show that excess mortality estimates can vary substantially when these factors are changed, and that the largest variations stem from the choice of the mortality index and the method. We also find that the magnitude of the variation in excess mortality is country-specific, resulting in cross-country rankings changes. Finally, based on our findings, we provide guidelines for estimating excess mortality.
| S-EPMC9115405 | biostudies-literature
Project description:The impact of the COVID-19 pandemic on excess mortality from all causes in 2020 varied across and within European countries. Using data for 2015-2019, we applied Bayesian spatio-temporal models to quantify the expected weekly deaths at the regional level had the pandemic not occurred in England, Greece, Italy, Spain, and Switzerland. With around 30%, Madrid, Castile-La Mancha, Castile-Leon (Spain) and Lombardia (Italy) were the regions with the highest excess mortality. In England, Greece and Switzerland, the regions most affected were Outer London and the West Midlands (England), Eastern, Western and Central Macedonia (Greece), and Ticino (Switzerland), with 15-20% excess mortality in 2020. Our study highlights the importance of the large transportation hubs for establishing community transmission in the first stages of the pandemic. Here, we show that acting promptly to limit transmission around these hubs is essential to prevent spread to other regions and countries.
| S-EPMC8789777 | biostudies-literature
Project description:ObjectivesThis study analyzed inequities in excess mortality according to region and socioeconomic position to explain the distribution of excess mortality in Korea in 2020.MethodsWe acquired weekly all-cause mortality data from January 2015 to December 2020 from (1) the National Health Insurance Database and (2) Vital Statistics. Excess mortality for 2020 was calculated by comparing the weekly observed and expected deaths from the same period (2015-2019) using quasi-Poisson regression.ResultsAn inequitable distribution of excess mortality was identified. The estimated excess mortality in Korea was -29,112 (95% confidence interval, -29,832 to -28,391), corresponding to -55 per 100,000, and the ratio of observed deaths to expected deaths was 0.91. Negative excess mortality was observed except for females in the 0-14 age group. Male Medical Aid beneficiaries showed positive excess mortality, while non-disabled and disabled groups showed similar negative values. When the standardized mortality ratio was calculated for the top 10 causes of death, deaths from Alzheimer's disease and septicemia increased, whereas those from diabetes mellitus and cerebrovascular disease decreased. The decrease in mortality was primarily concentrated in older adults, while the mortality of young females increased due to increased intentional self-harm.ConclusionsThis study adds essential evidence regarding the overall performance of Korea. The observed inequalities according to various socioeconomic variables indicate that the results of strict measures to control coronavirus disease 2019 were not distributed equitably. Efforts should be made to properly evaluate the current and future problems related to the pandemic.
| S-EPMC10089707 | biostudies-literature
Project description:Excess mortality (EM) is a valid indicator of COVID-19's impact on public health. Several studies regarding the estimation of EM have been conducted in Italy, and some of them have shown conflicting values. We focused on three estimation models and compared their results with respect to the same target population, which allowed us to highlight their strengths and limitations. We selected three estimation models: model 1 (Maruotti et al.) is a Negative-Binomial GLMM with seasonal patterns; model 2 (Dorrucci et al.) is a Negative Binomial GLM epidemiological approach; and model 3 (Scortichini et al.) is a quasi-Poisson GLM time-series approach with temperature distributions. We extended the time windows of the original models until December 2021, computing various EM estimates to allow for comparisons. We compared the results with our benchmark, the ISS-ISTAT official estimates. Model 1 was the most consistent, model 2 was almost identical, and model 3 differed from the two. Model 1 was the most stable towards changes in the baseline years, while model 2 had a lower cross-validation RMSE. Presently, an unambiguous explanation of EM in Italy is not possible. We provide a range that we consider sound, given the high variability associated with the use of different models. However, all three models accurately represented the spatiotemporal trends of the pandemic waves in Italy.
| S-EPMC9779266 | biostudies-literature
Project description:BackgroundThe COVID-19 pandemic brought countless challenges to public health and highlighted the Brazilian health system vulnerabilities in facing the emergency. In this article, we analyze data on COVID-19-related deaths in 2020-21 to show the epidemic consequences in Brazil.MethodsThe Mortality Information System and the Live Birth Information System were the primary information sources. We used population estimates in 2020-21 to calculate COVID-19 specific mortality rates by age, sex, and educational level. Considering the total number of COVID-19 deaths in 2020-21, the COVID-19 proportional mortality (%) was estimated for each age group and sex. A graph of the daily number of deaths from January 2020 to December 2021 by sex was elaborated to show the temporal evolution of COVID-19 deaths in Brazil. In addition, four indicators related to COVID-19 mortality were estimated: infant mortality rate (IMR); maternal mortality ratio (MMR); number and rate of orphans due to mother's COVID-19 death; the average number of years lost.ResultsThe overall COVID-19 mortality rate was 14.8 (/10,000). The mortality rates increase with age and show a decreasing gradient with higher schooling. The rate among illiterate people was 38.8/10,000, three times higher than a college education. Male mortality was 31% higher than female mortality. COVID-19 deaths represented 19.1% of all deaths, with the highest proportions in the age group of 40-59 years. The average number of years lost due to COVID-19 was 19 years. The MMR due to COVID-19 was 35.7 per 100,000 live births (LB), representing 37.4% of the overall MMR. Regarding the number of orphans due to COVID-19, we estimated that 40,830 children under 18 lost their mothers during the epidemic, with an orphans' rate of 7.5/10,000 children aged 0-17 years. The IMR was 11.7 per 1000 LB, with 0.2 caused by COVID-19. The peak of COVID-19 deaths occurred in March 2021, reaching almost 4000 COVID-19 deaths per day, higher than the average number of deaths per day from all causes in 2019.ConclusionsThe delay in adopting public health measures necessary to control the epidemic has exacerbated the spread of the disease, resulting in several avoidable deaths.
| S-EPMC9762984 | biostudies-literature
Project description:In this paper, we measure the effect of the 2020 COVID-19 pandemic wave at the national and subnational levels in selected Latin American countries that were most affected: Brazil, Chile, Ecuador, Guatemala, Mexico, and Peru. We used publicly available monthly mortality data to measure the impacts of the pandemic using excess mortality for each country and its regions. We compare the mortality, at national and regional levels, in 2020 to the mortality levels of recent trends and provide estimates of the impact of mortality on life expectancy at birth. Our findings indicate that from April 2020 on, mortality exceeded its usual monthly levels in multiple areas of each country. In Mexico and Peru, excess mortality was spreading through many areas by the end of the second half of 2020. To a lesser extent, we observed a similar pattern in Brazil, Chile, and Ecuador. We also found that as the pandemic progressed, excess mortality became more visible in areas with poorer socioeconomic and sanitary conditions. This excess mortality has reduced life expectancy across these countries by 2-10 years. Despite the lack of reliable information on COVID-19 mortality, excess mortality is a useful indicator for measuring the effects of the coronavirus pandemic, especially in the context of Latin American countries, where there is still a lack of good information on causes of death in their vital registration systems.Supplementary informationThe online version contains supplementary material available at 10.1186/s41118-021-00139-1.
| S-EPMC8564791 | biostudies-literature
Project description:In this work, the COVID-19 pandemic burden in Ukraine is investigated retrospectively using the excess mortality measures during 2020-2021. In particular, the epidemic impact on the Ukrainian population is studied via the standardized both all-cause and cause-specific mortality scores before and during the epidemic. The excess mortality counts during the pandemic were predicted based on historic data using parametric and nonparametric modeling and then compared with the actual reported counts to quantify the excess. The corresponding standardized mortality P-score metrics were also compared with the neighboring countries. In summary, there were three "waves" of excess all-cause mortality in Ukraine in December 2020, April 2021 and November 2021 with excess of 32%, 43% and 83% above the expected mortality. Each new "wave" of the all-cause mortality was higher than the previous one and the mortality "peaks" corresponded in time to three "waves" of lab-confirmed COVID-19 mortality. The lab-confirmed COVID-19 mortality constituted 9% to 24% of the all-cause mortality during those three peak months. Overall, the mortality trends in Ukraine over time were similar to neighboring countries where vaccination coverage was similar to that in Ukraine. For cause-specific mortality, the excess observed was due to pneumonia as well as circulatory system disease categories that peaked at the same times as the all-cause and lab-confirmed COVID-19 mortality, which was expected. The pneumonias as well as circulatory system disease categories constituted the majority of all cases during those peak times. The seasonality in mortality due to the infectious and parasitic disease category became less pronounced during the pandemic. While the reported numbers were always relatively low, alcohol-related mortality also declined during the pandemic.
| S-EPMC10139669 | biostudies-literature
Project description:ObjectivesThe first wave of the SARS-CoV-2 pandemic in Germany lasted from week 10 to 23 in 2020. The aim is to provide estimates of excess mortality in Germany during this time.MethodsWe analyzed age-specific numbers of deaths per week from 2016 to week 26 in 2020. We used weekly mean numbers of deaths of 2016-2019 to estimate expected weekly numbers for 2020. We estimated standardized mortality ratios (SMR) and 95% confidence intervals.ResultsDuring the first wave observed numbers of deaths were higher than expected for age groups 60-69, 80-89, and 90+. The age group 70-79 years did not show excess mortality. The net excess number of deaths for weeks 10-23 was +8,071. The overall SMR was 1•03 (95%CI 1•03-1•04). The largest increase occurred among people aged 80-89 and 90+ (SMR=1•08 and SMR=1•09). A sensitivity analysis that accounts for demographic changes revealed an overall SMR of 0•98 (95%CI 0•98-0•99) and a deficit of 4,926 deaths for week 10-23, 2020.ConclusionsThe excess mortality existed for two months. The favorable course of the first wave may be explained by a younger age at infection at the beginning of the pandemic, lower contact rates, and a more efficient pandemic management.
| S-EPMC7501062 | biostudies-literature