"Excess deaths" is the best metric for tracking the pandemic

Does mask usage correlate with excess mortality? Findings from 24 European countries

BACKGROUND

Several nonpharmaceutical interventions, such as masking, were mandated or recommended during the Coronavirus disease 2019 (COVID-19) pandemic. This study's primary objective is to investigate the relationship between population-level mask usage and excess mortality across Europe.

METHODS

We collected data on mask usage and other relevant variables from 24 European countries during 2020-2021, a period in which mask policies varied widely across nations, providing an ideal basis for a natural experiment. To assess the association between mask usage and relevant medical and socioeconomic data at the country level, we conducted both bivariate and multivariate regression analyses. Confounding factors were accounted for in the regression models, and numerous sensitivity tests were performed to ensure robustness.

RESULTS

Statistically significant correlations were found between mask usage rate and age-adjusted excess mortality in both bivariate (Spearman coefficient = 0.477, p = 0.018) and multivariate (Standardized coefficient = 0.52, p = 0.0012) regressions. Likewise, vaccination rates showed negative and significant bivariate (Spearman coefficient = -0.659, p < .001) and multivariate (Standardized coefficient = -0.48, p = 0.0016) correlations with age-adjusted excess mortality.

CONCLUSIONS

No correlation was observed between mask usage rates and COVID-19 morbidity. However, significant associations were identified between mask usage rates, COVID-19 mortality, and excess deaths. Various hypotheses have been proposed to explain these associations, with thorough consideration given to potential confounders, such as socioeconomic factors and the severity of COVID-19 waves.

Excess mortality and years of life lost from 2020 to 2023 in France: a cohort study of the overall impact of the COVID-19 pandemic on mortality

Introduction

Excess mortality has been frequently used worldwide for summarising the COVID-19 pandemic-related burden. Estimates for France for the years 2020-2022 vary substantially from one report to another, and the year 2023 is poorly documented. The present study assessed the level of excess mortality that occurred in France between 2020 and 2023 together with the corresponding years of life lost (YLL), in order to provide a reliable, detailed and comprehensive description of the overall impact of the pandemic.

Method

This open cohort study of the whole French population analysed the 8 451 372 death occurrences reported for the years 2010-2023. A Poisson regression model was trained with years 2010-2019 for determining the age-specific and sex-specific evolution trends of mortality before the pandemic period. These trends were then used for estimating the excess mortality during the pandemic period (years 2020-2023). The life expectancies of the persons in excess mortality were used for estimating the corresponding YLL.

Results

From 2020 to 2023, the number of excess deaths (mean (95% CI) (percentage of change versus expected mortality)) was, respectively, 49 541 (48 467; 50 616) (+8.0%), 42 667 (41 410; 43 909) (+6.9%), 53 129 (51 696; 54 551) (+8.5%), and 17 355 (15 760; 18 917) (+2.8%). Corresponding YLL were 512 753 (496 029; 529 633), 583 580 (564 137; 602 747), 663 588 (641 863; 685 723), and 312 133 (288 051; 335 929). Individuals younger than 60 years old accounted for 17% of the YLL in 2020, 26% in 2021, 32% in 2022 and 50% in 2023. Men were more affected than women by both excess mortality and YLL.

Conclusion

This study highlights the long-lasting impact of the pandemic on mortality in France, with four consecutive years of excess mortality and a growing impact on people under 60, particularly men, suggesting lasting and profound disruption to the healthcare system.

Impact of COVID-19 on total excess mortality and geographic disparities in Europe, 2020-2023: a spatio-temporal analysis

Background

COVID-19 dramatically reshaped mortality across Europe. This study aimed to assess its impact on total mortality in European countries taking into consideration the relationship with selected country-level socioeconomic indicators, non-pharmaceutical interventions, and vaccine uptake.

Methods

We obtained weekly mortality data from 2010 to 2023 from the Short-term Mortality Fluctuations data series, the annual population data from the United Nations archives, selected sociodemographic and economic indicators from the World Bank's database, the stringency index and the percentage of the population fully vaccinated from Our World in Data. A quasi-Poisson regression model trained on pre-pandemic years was used to estimate expected number of deaths in 2020-2023 in 29 European countries. Excess mortality was estimated using three different metrics: excess deaths (number), relative excess mortality (% different from expected deaths) and age-standardized excess death rate per 10,000 population. The relationship between socioeconomic indicators and excess mortality was evaluated using linear regression models, which included both linear and quadratic terms for the predictors to account for possible non-linear relationships.

Findings

We estimated 1,642,586 excess deaths (95% confidence interval, CI: 1,607,161-1,678,010) across all countries over the four years (+8.0% compared to the expected number of deaths). Excess mortality was mainly concentrated in 2020-2022 (0.52 million excess deaths in 2020, 0.57 million in 2021 and 0.44 million in 2022), with no substantial excess (0.11 million) estimated for 2023. Over the period 2020-23, the highest number of excess deaths was estimated for Italy (227,736 deaths, +8.7%), Poland (223,735 deaths, +13.7%), and Germany (218,111 deaths, +5.6%), while the highest excesses in relative terms were in Bulgaria (72,328 deaths, +17.2%), Lithuania (23,813 deaths, +16.1%), and Slovakia (31,984 deaths, +14.9%). The age-standardised death rates ranged from 1.8 per 10,000 population in Sweden to 24.7 in Bulgaria. The percentage of the population living below the poverty line and the Gini index were significantly associated with an increased excess death rate, with p-values for the linear and quadratic terms being 0.003 and 0.003 for the Gini index, and 0.024 and 0.017 for the population living below the poverty line. Conversely, gross domestic product per capita (p-values for the linear and quadratic terms: <0.001, 0.003), health expenditure (0.001, 0.273) and the percentage of people fully vaccinated by the end of 2021 (<0.001, 0.989) or 2022 (0.001, 0.890) were inversely associated with excess death rate. No significant association was observed with population density and stringency index.

Interpretation

The observed geographic disparities in total mortality excess across Europe can be related to differences in socioeconomic contexts, as well as to suboptimal vaccine uptakes in some countries.

Funding

This research was supported by European Union (EU) funding within the NextGeneration EU-MUR PNRR Extended Partnership initiative on Emerging Infectious Diseases (Project no. PE00000007, INF-ACT). The funding source had no role in study design; in the collection, analysis, and interpretation of data; in the writing of the report; and in the decision to submit the paper for publication.

Regional inequalities in excess mortality and its community determinants during the early COVID-19 pandemic in South Korea

BACKGROUND

Excess mortality during the COVID-19 pandemic provides a comprehensive measure of disease burden, and its local variation highlights regional health inequalities. We investigated local excess mortality in 2020 and its determinants at the community level.

METHODS

We collected data from 250 districts in South Korea, including monthly all-cause mortality for 2015-2020 and community characteristics from 2019. Excess mortality rate was defined as the difference between observed and expected mortality rates. A Seasonal Autoregressive Integrated Moving Average model was applied to predict the expected rates for each district. Penalized regression methods were used to derive relevant community predictors of excess mortality based on the elastic net.

RESULTS

In 2020, South Korea exhibited significant variation in excess mortality rates across 250 districts, ranging from no excess deaths in 46 districts to more than 100 excess deaths per 100 000 residents in 30 districts. Economic status or the number of medical centres in the community did not correlate with excess mortality rates. The risk was higher in ageing, remote communities with limited cultural and sports infrastructure, a higher density of welfare facilities, and a higher prevalence of hypertension. Physical distancing policies and active social engagement in voluntary activities protected from excess mortality.

CONCLUSION

Substantial regional disparities in excess mortality existed within South Korea during the early stages of COVID-19 pandemic. Weaker segments of the community were more vulnerable. Local governments should refine their preparedness for future novel infectious disease outbreaks, considering community circumstances.

Excess Mortality Calculations to Assess the Impact of the COVID-19 Pandemic: Concepts and Methodological Issues

We discuss some intriguing methodological aspects of excess mortality analyses, which have been widely used to describe the impact of the COVID-19 pandemic. We describe the main ways of presenting excess mortality: as a mortality rate (incidence rate) or as a percentage increase (relative risk or rate ratio). We discuss what should be regarded as the null value of excess mortality (i.e., when countries or regions can be judged as having fared equally well) and when age and sex standardization, adjustment for other determinants of the spread of a pandemic, or both is necessary. We discuss the level of detail by time and place and person that may be necessary. We note that an excess mortality comparison is essentially a difference-in-differences analysis. We conclude that, although one cannot rule out using excess mortality analyses for causal effect estimates, such analyses will remain most fruitful for generating hypotheses about both the efficiency of measures to curtail the pandemic and factors that cannot be influenced. Nevertheless, a judicious use of arguments and counterarguments can then lead to identifying best practices for various situations. (Am J Public Health. 2024;114(6):593-598. https://doi.org/10.2105/AJPH.2024.307572).

Magnitude and determinants of excess total, age-specific and sex-specific all-cause mortality in 24 countries worldwide during 2020 and 2021: results on the impact of the COVID-19 pandemic from the C-MOR project

INTRODUCTION

To examine the impact of the COVID-19 pandemic on mortality, we estimated excess all-cause mortality in 24 countries for 2020 and 2021, overall and stratified by sex and age.

METHODS

Total, age-specific and sex-specific weekly all-cause mortality was collected for 2015-2021 and excess mortality for 2020 and 2021 was calculated by comparing weekly 2020 and 2021 age-standardised mortality rates against expected mortality, estimated based on historical data (2015-2019), accounting for seasonality, and long-term and short-term trends. Age-specific weekly excess mortality was similarly calculated using crude mortality rates. The association of country and pandemic-related variables with excess mortality was investigated using simple and multilevel regression models.

RESULTS

Excess cumulative mortality for both 2020 and 2021 was found in Austria, Brazil, Belgium, Cyprus, England and Wales, Estonia, France, Georgia, Greece, Israel, Italy, Kazakhstan, Mauritius, Northern Ireland, Norway, Peru, Poland, Slovenia, Spain, Sweden, Ukraine, and the USA. Australia and Denmark experienced excess mortality only in 2021. Mauritius demonstrated a statistically significant decrease in all-cause mortality during both years. Weekly incidence of COVID-19 was significantly positively associated with excess mortality for both years, but the positive association was attenuated in 2021 as percentage of the population fully vaccinated increased. Stringency index of control measures was positively and negatively associated with excess mortality in 2020 and 2021, respectively.

CONCLUSION

This study provides evidence of substantial excess mortality in most countries investigated during the first 2 years of the pandemic and suggests that COVID-19 incidence, stringency of control measures and vaccination rates interacted in determining the magnitude of excess mortality.

A comparison of excess deaths by UK country and region during the first year of the COVID-19 pandemic

We compare the impact of the first two waves of the COVID-19 pandemic on risk of age-standardized mortality by sex, UK country, and English region. Each wave is defined as lasting 26 weeks and are consecutive beginning in 2020 week 11. The expected rate is estimated from 2015 to 2019 mean and the projected mortality trend from the same period are used to estimate excess mortality. By both measures, excess mortality was highest and lowest in regions of England, London and the South-West, respectively. Excess mortality was consistently higher for males than females.

Excess death estimates from multiverse analysis in 2009-2021

Excess death estimates have great value in public health, but they can be sensitive to analytical choices. Here we propose a multiverse analysis approach that considers all possible different time periods for defining the reference baseline and a range of 1 to 4 years for the projected time period for which excess deaths are calculated. We used data from the Human Mortality Database on 33 countries with detailed age-stratified death information on an annual basis during the period 2009-2021. The use of different time periods for reference baseline led to large variability in the absolute magnitude of the exact excess death estimates. However, the relative ranking of different countries compared to others for specific years remained largely unaltered. The relative ranking of different years for the specific country was also largely independent of baseline. Averaging across all possible analyses, distinct time patterns were discerned across different countries. Countries had declines between 2009 and 2019, but the steepness of the decline varied markedly. There were also large differences across countries on whether the COVID-19 pandemic years 2020-2021 resulted in an increase of excess deaths and by how much. Consideration of longer projected time windows resulted in substantial shrinking of the excess deaths in many, but not all countries. Multiverse analysis of excess deaths over long periods of interest can offer an approach that better accounts for the uncertainty in estimating expected mortality patterns, comparative mortality trends across different countries, and the nature of observed mortality peaks.

Excess deaths by cause and place of death in England and Wales during the first year of COVID-19

Using officially registered weekly mortality data, we estimate a counterfactual death count in the absence of the pandemic and we calculate the number of excess deaths in England and Wales during 2020 after the pandemic onset. We also break down those figures by region, age, gender, place of death, and cause of death. Our results suggest that there were 82,428 (95% Confidence interval [CI]: 78,402 to 86,415) excess deaths, and 88.9% (95% CI: 84.8%-93.5%) of them was due to COVID-19, suggesting that non-COVID-19 excess mortality may have been slightly higher that what has been previously estimated. Regarding deaths not due to COVID-19, persons older than 45 years old who died at their homes, mainly from heart diseases and cancer, were the most affected group. Across all causes of death, there was increased excess mortality from dementia and Alzheimer's disease, diabetes, Parkinson's disease and heart-related disease, while at the same period there was a reduction in deaths from pneumonia and influenza, stroke as well as infectious diseases and accidents. Supported by regional panel event estimates, our results highlight how measures to mitigate the pandemic spread and ease the pressure on healthcare service systems may adversely affect out-of-hospital mortality from other causes.

Excess death estimates from multiverse analysis in 2009-2021

Excess death estimates have great value in public health, but they can be sensitive to analytical choices. Here we propose a multiverse analysis approach that considers all possible different time periods for defining the reference baseline and a range of 1 to 4 years for the projected time period for which excess deaths are calculated. We used data from the Human Mortality Database on 33 countries with detailed age-stratified death information on an annual basis during the period 2009-2021. The use of different time periods for reference baseline led to large variability in the absolute magnitude of the exact excess death estimates. However, the relative ranking of different countries compared to others for specific years remained largely unaltered. The relative ranking of different years for the specific country was also largely independent of baseline. Averaging across all possible analyses, distinct time patterns were discerned across different countries. Countries had declines between 2009 and 2019, but the steepness of the decline varied markedly. There were also large differences across countries on whether the COVID-19 pandemic years 2020-2021 resulted in an increase of excess deaths and by how much. Consideration of longer projected time windows resulted in substantial shrinking of the excess deaths in many, but not all countries. Multiverse analysis of excess deaths over long periods of interest can offer a more unbiased approach to understand comparative mortality trends across different countries, the range of uncertainty around estimates, and the nature of observed mortality peaks.

COVID-19-related excess mortality - an overview of the current evidence

Analysis of excess deaths, defined as the difference in the total number of deaths in an emergency compared to the number of deaths expected under normal conditions, allows a more reliable assessment of the impact on health systems caused by the global threat of SARS-CoV-2 (Severe Acute Respiratory Syndrome Coronavirus-2). So far, data for the two years of the pandemic (2020-2021) indicates the occurrence of 14.9 million excess deaths according to WHO (World Health Organization) estimates. The purpose of the analysis conducted was to define the concept and identify the causes of excess mortality during the COVID-19 pandemic. Inconsistent and unreliable death registration systems; overburdened health systems in low- and middle-income countries; reduced access to medical services for patients with health problems other than COVID-19; the introduction of social distancing and lockdown rules, which translated into increased deaths from psychiatric illnesses and addictions; political considerations and media messages that interfered with vaccination acceptance and adherence; and the additional impact of other natural disasters (hurricanes, floods, drought) were identified as the most important reasons for excess deaths occurrence. The correct identification of country-specific factors and the correct response and countermeasures taken appear crucial in terms of limiting the negative impact of the current pandemic, but also of future threats of a similar nature, in order to reduce excess deaths.

Global Excess Mortality during COVID-19 Pandemic: A Systematic Review and Meta-Analysis

BACKGROUND

Currently, reported COVID-19 deaths are inadequate to assess the impact of the pandemic on global excess mortality. All-cause excess mortality is a WHO-recommended index for assessing the death burden of COVID-19. However, the global excess mortality assessed by this index remains unclear. We aimed to assess the global excess mortality during the COVID-19 pandemic.

METHODS

We searched PubMed, EMBASE, and Web of Science for studies published in English between 1 January 2020, and 21 May 2022. Cross-sectional and cohort studies that reported data about excess mortality during the pandemic were included. Two researchers independently searched the published studies, extracted data, and assessed quality. The Mantel-Haenszel random-effects method was adopted to estimate pooled risk difference (RD) and their 95% confidence intervals (CIs).

RESULTS

A total of 79 countries from twenty studies were included. During the COVID-19 pandemic, of 2,228,109,318 individuals, 17,974,051 all-cause deaths were reported, and 15,498,145 deaths were expected. The pooled global excess mortality was 104.84 (95% CI 85.56-124.13) per 100,000. South America had the highest pooled excess mortality [134.02 (95% CI: 68.24-199.80) per 100,000], while Oceania had the lowest [-32.15 (95% CI: -60.53--3.77) per 100,000]. Developing countries had higher excess mortality [135.80 (95% CI: 107.83-163.76) per 100,000] than developed countries [68.08 (95% CI: 42.61-93.55) per 100,000]. Lower middle-income countries [133.45 (95% CI: 75.10-191.81) per 100,000] and upper-middle-income countries [149.88 (110.35-189.38) per 100,000] had higher excess mortality than high-income countries [75.54 (95% CI: 53.44-97.64) per 100,000]. Males had higher excess mortality [130.10 (95% CI: 94.15-166.05) per 100,000] than females [102.16 (95% CI: 85.76-118.56) per 100,000]. The population aged ≥ 60 years had the highest excess mortality [781.74 (95% CI: 626.24-937.24) per 100,000].

CONCLUSIONS

The pooled global excess mortality was 104.84 deaths per 100,000, and the number of reported all-cause deaths was higher than expected deaths during the global COVID-19 pandemic. In South America, developing and middle-income countries, male populations, and individuals aged ≥ 60 years had a heavier excess mortality burden.

Comparison of pandemic excess mortality in 2020-2021 across different empirical calculations

Different modeling approaches can be used to calculate excess deaths for the COVID-19 pandemic period. We compared 6 calculations of excess deaths (4 previously published [3 without age-adjustment] and two new ones that we performed with and without age-adjustment) for 2020-2021. With each approach, we calculated excess deaths metrics and the ratio R of excess deaths over recorded COVID-19 deaths. The main analysis focused on 33 high-income countries with weekly deaths in the Human Mortality Database (HMD at mortality.org) and reliable death registration. Secondary analyses compared calculations for other countries, whenever available. Across the 33 high-income countries, excess deaths were 2.0-2.8 million without age-adjustment, and 1.6-2.1 million with age-adjustment with large differences across countries. In our analyses after age-adjustment, 8 of 33 countries had no overall excess deaths; there was a death deficit in children; and 0.478 million (29.7%) of the excess deaths were in people <65 years old. In countries like France, Germany, Italy, and Spain excess death estimates differed 2 to 4-fold between highest and lowest figures. The R values' range exceeded 0.3 in all 33 countries. In 16 of 33 countries, the range of R exceeded 1. In 25 of 33 countries some calculations suggest R > 1 (excess deaths exceeding COVID-19 deaths) while others suggest R < 1 (excess deaths smaller than COVID-19 deaths). Inferred data from 4 evaluations for 42 countries and from 3 evaluations for another 98 countries are very tenuous. Estimates of excess deaths are analysis-dependent and age-adjustment is important to consider. Excess deaths may be lower than previously calculated.

Socio-demographic inequalities and excess non-COVID-19 mortality during the COVID-19 pandemic: a data-driven analysis of 1 069 174 death certificates in Mexico

BACKGROUND

In 2020, Mexico experienced one of the highest rates of excess mortality globally. However, the extent of non-COVID deaths on excess mortality, its regional distribution and the association between socio-demographic inequalities have not been characterized.

METHODS

We conducted a retrospective municipal and individual-level study using 1 069 174 death certificates to analyse COVID-19 and non-COVID-19 deaths classified by ICD-10 codes. Excess mortality was estimated as the increase in cause-specific mortality in 2020 compared with the average of 2015-2019, disaggregated by primary cause of death, death setting (in-hospital and out-of-hospital) and geographical location. Correlates of individual and municipal non-COVID-19 mortality were assessed using mixed effects logistic regression and negative binomial regression models, respectively.

RESULTS

We identified a 51% higher mortality rate (276.11 deaths per 100 000 inhabitants) compared with the 2015-2019 average period, largely attributable to COVID-19. Non-COVID-19 causes comprised one-fifth of excess deaths, with acute myocardial infarction and type 2 diabetes as the two leading non-COVID-19 causes of excess mortality. COVID-19 deaths occurred primarily in-hospital, whereas excess non-COVID-19 deaths occurred in out-of-hospital settings. Municipal-level predictors of non-COVID-19 excess mortality included levels of social security coverage, higher rates of COVID-19 hospitalization and social marginalization. At the individual level, lower educational attainment, blue-collar employment and lack of medical care assistance prior to death were associated with non-COVID-19 deaths.

CONCLUSION

Non-COVID-19 causes of death, largely chronic cardiometabolic conditions, comprised up to one-fifth of excess deaths in Mexico during 2020. Non-COVID-19 excess deaths occurred disproportionately out-of-hospital and were associated with both individual- and municipal-level socio-demographic inequalities.

Epidemiology and Response to the COVID-19 Pandemic in Kerala, India, 2020-2021: A Cross-Sectional Study

Kerala, a southern state in India, experienced a slightly different COVID-19 pandemic than the rest of India. Using data from daily COVID-19 bulletins and two other Kerala health information systems, this study reported on epidemiological characteristics and response measures of the COVID-19 pandemic between January 2020 and December 2021. After the first six months, Kerala experienced three distinct phases, with COVID-19 cases peaking in October 2020, May 2021, and August 2021. This contrasts with India, which experienced two main peaks in September 2020 and May 2021. The demographic profile of cases aligned with the national profile except for a slight increase of COVID-19 in persons aged ≥60 years. Monthly COVID-19 deaths increased dramatically from May 2021 onwards in line with case numbers but also reflecting changes in definitions of COVID-19 deaths. Case fatality for the two years was significantly higher in males than females, increased with increasing age groups, and varied between districts (p < 0.001). Trends in bed occupancy in field hospitals, hospitals for severe disease, intensive care units, and mechanical ventilation mirrored the different phases of the pandemic. The monitoring system in Kerala allowed certain aspects of the pandemic to be mapped, but it would benefit from further strengthening.