The contribution of population age-sex structure to the excess mortality estimates of 2020–2021 in Denmark, Finland, Iceland, Norway, and Sweden

Abstract

AbstractBackgroundThe Nordic countries are an ideal case study of the COVID-19 pandemic due to their comparability, high data quality, and variable responses. Excess mortality is a key metric but it is sensitive to data quality, model assumptions, and population structure, with diverse estimates published so far.MethodsWe investigated the age- and sex-specific mortality patterns during 2020−2021 for the five Nordic countries using annualized age- and sex specific death rates and populations. We compared the total age- and sex-adjusted excess deaths, ratios of actual vs. expected death rates, and age-standardized excess death estimates. We estimated excess deaths with several time periods and sensitivity tests, using 42 sex and age groups. Our models are less sensitive to outlier years than models based on 5 years of data.ResultsAge-specific death rates have declining trends that reflect real improving health demographics. Our total excess mortality is close to WHO’s estimates, except higher for Norway and lower for Sweden, partly due to data used. Total excess deaths were dominated by the age group 70−89 years, was not identified in children, and more pronounced in men than women. Sweden had more excess deaths in 2020 than 2021 whereas Finland, Norway, and Denmark had the opposite. Denmark has the highest death rates before and during the pandemic, whereas Sweden in 2020 had the largest mortality increase. The age-standardized mortality of Denmark, Iceland and Norway was lowest in 2020, and 2021 was one of the lowest mortality years for all Nordic countries. We show that neutral baseline methods underestimate excess deaths and we document the importance of outlier mortality years.ConclusionsWe provide excess mortality estimates mortality of the Nordic countries in relation to sex and age, with several metrics important in combination for a full understanding and comparison of the countries. We additionally identify important effects such as mortality displacement and sensitivities that affect our estimates and those of other excess mortality models.