Excess deaths associated with covid-19 pandemic in 2020: age and sex disaggregated time series analysis in 29 high income countries

Abstract

Objective To estimate the direct and indirect effects of the covid-19 pandemic on mortality in 2020 in 29 high income countries with reliable and complete age and sex disaggregated mortality data. Design Time series study of high income countries. Setting Austria, Belgium, Czech Republic, Denmark, England and Wales, Estonia, Finland, France, Germany, Greece, Hungary, Israel, Italy, Latvia, Lithuania, the Netherlands, New Zealand, Northern Ireland, Norway, Poland, Portugal, Scotland, Slovakia, Slovenia, South Korea, Spain, Sweden, Switzerland, and United States. Participants Mortality data from the Short-term Mortality Fluctuations data series of the Human Mortality Database for 2016-20, harmonised and disaggregated by age and sex. Interventions Covid-19 pandemic and associated policy measures. Main outcome measures Weekly excess deaths (observed deaths versus expected deaths predicted by model) in 2020, by sex and age (0-14, 15-64, 65-74, 75-84, and ≥85 years), estimated using an over-dispersed Poisson regression model that accounts for temporal trends and seasonal variability in mortality. Results An estimated 979 000 (95% confidence interval 954 000 to 1 001 000) excess deaths occurred in 2020 in the 29 high income countries analysed. All countries had excess deaths in 2020, except New Zealand, Norway, and Denmark. The five countries with the highest absolute number of excess deaths were the US (458 000, 454 000 to 461 000), Italy (89 100, 87 500 to 90 700), England and Wales (85 400, 83 900 to 86 800), Spain (84 100, 82 800 to 85 300), and Poland (60 100, 58 800 to 61 300). New Zealand had lower overall mortality than expected (−2500, −2900 to −2100). In many countries, the estimated number of excess deaths substantially exceeded the number of reported deaths from covid-19. The highest excess death rates (per 100 000) in men were in Lithuania (285, 259 to 311), Poland (191, 184 to 197), Spain (179, 174 to 184), Hungary (174, 161 to 188), and Italy (168, 163 to 173); the highest rates in women were in Lithuania (210, 185 to 234), Spain (180, 175 to 185), Hungary (169, 156 to 182), Slovenia (158, 132 to 184), and Belgium (151, 141 to 162). Little evidence was found of subsequent compensatory reductions following excess mortality. Conclusion Approximately one million excess deaths occurred in 2020 in these 29 high income countries. Age standardised excess death rates were higher in men than women in almost all countries. Excess deaths substantially exceeded reported deaths from covid-19 in many countries, indicating that determining the full impact of the pandemic on mortality requires assessment of excess deaths. Many countries had lower deaths than expected in children <15 years. Sex inequality in mortality widened further in most countries in 2020.

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

“…For example, in South Africa, lockdowns have noticeably decreased toddler mortality (0–4 years) ( Bradshaw et al, 2021 ). This effect was not observed in the developed countries where toddler mortality is low ( Islam et al, 2021 ), but could be present in other developing countries as well.…”

“…Some of the countries in our dataset have excess death estimates available in the constantly evolving literature on excess deaths during the COVID-19 pandemic from academia, official institutions and professional associations. The largest efforts include the analysis of STMF data ( Kontis et al, 2020 ; Islam et al, 2021 ) and excess mortality trackers by The Economist and Financial Times . While the analysis is similar everywhere and the estimates broadly agree, there are many possible modeling choices (the start date and the end date of the total excess computation; including or excluding historic influenza waves when computing the baseline; modeling trend over years or not, etc.)…”

“…Excess mortality has already been used to estimate the COVID-19 impact in different countries, both in academic literature (e.g. Kontis et al, 2020 ; Alicandro et al, 2020 ; Ghafari et al, 2021 ; Woolf et al, 2020a ; Woolf et al, 2020b ; Weinberger et al, 2020 ; Blangiardo et al, 2020 ; Kobak, 2021a ; Modi et al, 2021 ; Bradshaw et al, 2021 ; Islam et al, 2021 , among many others) and by major media outlets. It has also been used to compare COVID-19 impact to the impact of major influenza pandemics ( Faust et al, 2020 ; Petersen et al, 2020 ).…”

“…At the time of writing, this dataset covers 36 European countries and also contains sub-national (NUTS1–3 regions) data as well as data disaggregated by age groups and by sex for some countries. In May 2020, the Human Mortality Database ( http://mortality.org ), a joint effort by the University of California, Berkeley, and Max Planck Institute for Demographic Research ( Barbieri et al, 2015 ), started compiling the Short Term Mortality Fluctuations (STMF) dataset ( STMF, 2021 ; Islam et al, 2021 ; Németh et al, 2021 ). This dataset consists of weekly data, disaggregated by five age groups and by sex, and currently contains 35 countries with 2020 data.…”

Governments should be made to work harder to keep public trust

“…Estimates of excess deaths, rather than reported covid-19 deaths, give a better measure of the pandemic’s burden around the world (doi:10.1136/bmj.n1137). 9 But deaths provide only a partial picture of the true impact, especially on younger people and those affected by long covid, say Jonathan Clarke and colleagues (doi:10.1136/bmj.n1239). 10 Non-covid vaccination programmes have been badly hit (doi:10.1136/bmj.n1436),11 and global, gender, racial, and intergenerational inequalities are sure to increase unless urgently tackled.…”