Estimates of excess mortality for the five Nordic countries during the COVID-19 pandemic 2020-2021

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).

Excess mortality in Denmark, Finland, Norway and Sweden during the COVID-19 pandemic 2020-2022

BACKGROUND

The Nordic countries represent a unique case study for the COVID-19 pandemic due to socioeconomic and cultural similarities, high-quality comparable administrative register data and notable differences in mitigation policies during the pandemic. We aimed to compare weekly excess mortality in the Nordic countries across the three full pandemic years 2020-2022.

METHODS

Using data on weekly all-cause mortality from official administrative registers in Denmark, Finland, Norway and Sweden, we employed time series regression models to assess mortality developments within each pandemic year, with the period 2010-2019 used as reference period. We then compared excess mortality across the countries in 2020-2022, taking differences in population size and age- and sex-distribution into account. Results were age- and sex-standardized to the Danish population of 2020. Robustness was examined with a variety of sensitivity analyses.

RESULTS

While Sweden experienced excess mortality in 2020 [75 excess deaths per 100 000 population (95% prediction interval 29-122)], Denmark, Finland and Norway experienced excess mortality in 2022 [52 (14-90), 130 (83-177) and 88 (48-128), respectively]. Weekly death data reveal how mortality started to increase in mid-2021 in Denmark, Finland and Norway, and continued above the expected level through 2022.

CONCLUSION

Although the Nordic countries experienced relatively low pandemic excess mortality, the impact and timing of excess mortality differed substantially. These estimates-arguably the most accurate available for any region in capturing pandemic-related excess deaths-may inform future research and policy regarding the complex mortality dynamics in times of a health crisis such as the COVID-19 pandemic.

Age at death during the Covid-19 lockdown in French metropolitan regions: a non parametric quantile regression approach

BACKGROUND

Lockdowns have been implemented to limit the number of hospitalisations and deaths during the first wave of 2019 coronavirus disease. These measures may have affected differently death characteristics, such age and sex. France was one of the hardest hit countries in Europe with a decreasing east-west gradient in excess mortality. This study aimed at describing the evolution of age at death quantiles during the lockdown in spring 2020 (17 March-11 May 2020) in the French metropolitan regions focusing on 3 representatives of the epidemic variations in the country: Bretagne, Ile-de-France (IDF) and Bourgogne-Franche-Comté (BFC).

METHODS

Data were extracted from the French public mortality database from 1 January 2011 to 31 August 2020. The age distribution of mortality observed during the lockdown period (based on each decile, plus quantiles 1, 5, 95 and 99) was compared with the expected one using Bayesian non-parametric quantile regression.

RESULTS

During the lockdown, 5457, 5917 and 22 346 deaths were reported in Bretagne, BFC and IDF, respectively. An excess mortality from + 3% in Bretagne to + 102% in IDF was observed during lockdown compared to the 3 previous years. Lockdown led to an important increase in the first quantiles of age at death, irrespective of the region, while the increase was more gradual for older age groups. It corresponded to fewer young people, mainly males, dying during the lockdown, with an increase in the age at death in the first quantile of about 7 years across regions. In females, a less significant shift in the first quantiles and a greater heterogeneity between regions were shown. A greater shift was observed in eastern region and IDF, which may also represent excess mortality among the elderly.

CONCLUSIONS

This study focused on the innovative outcome of the age distribution at death. It shows the first quantiles of age at death increased differentially according to sex during the lockdown period, overall shift seems to depend on prior epidemic intensity before lockdown and complements studies on excess mortality during lockdowns.

Mortality in Norway and Sweden during the COVID-19 pandemic 2020-22: A comparative study

BACKGROUND

Norway and Sweden picked two different ways to mitigate the dissemination of the SARS-CoV-2 virus. Norway introduced the strictest lockdown in Europe with strict border controls and intense virus tracking of all local outbreaks while Sweden did not. That resulted in 477 COVID-19 deaths (Norway) and 9737 (Sweden) in 2020, respectively.

METHODS

Weekly number of COVID-19 related deaths and total deaths for 2020-22 were collected as well as weekly number of deaths for 2015-19 which were used as controls when calculating excess mortality. During the first 12-18 months with high rate of virus transmission in the society, excess mortality rates were used as substitute for COVID-19 deaths. When excess mortality rates later turned negative because of mortality displacement, COVID-19 deaths adjusted for bias due to overreporting were used.

RESULTS

There were 17521 COVID-19 deaths in Sweden and 4272 in Norway in the study period. The rate ratio (RR) of COVID-19 related deaths in Sweden vs. Norway to the end of week 43, 2022, was 2.11 (95% CI 2.05-2.19). RR of COVID-19 related deaths vs. excess number of deaths were 2.5 (Sweden) and 1.3 (Norway), respectively. RR of COVID-19 deaths in Sweden vs. Norway after adjusting for mortality displacement and lockdown, was 1.35 (95% CI 1.31-1.39), corresponding to saving 2025 life in Norway. If including all deaths in 2022, RR= 1.28 (95% CI 1.24-1.31).

CONCLUSIONS

Both COVID-19 related mortality and excess mortality rates are biased estimates. When adjusting for bias, mortality differences declined over time to about 30% higher mortality in Sweden after 30 months with pandemics.

Sweden's excess mortality in 2020-2022 and reporting in the media

AIM

The aim was to scrutinize the report in March 2023 that Sweden's excess mortality was lowest in 2020-2022 compared with other European Union and Nordic countries, a report that received great national and international attention.

STUDY DESIGN

Comparison of excess mortality in Sweden and Norway.

METHODS

Excess mortality for 2020-2022 was calculated for Sweden and Norway, the country with per-capita excess mortality closest to Sweden's, compared with the average mortality for 2017-2019 in the respective country, following the definitions by Statistics Sweden reported in a daily newspaper.

RESULTS

Excess mortality is a measure with low misclassification compared with other pandemic outcome measures. Following the definitions, total excess mortality for the years 2020-2022 was 11,897 individuals in Sweden and 6089 in Norway. However, the distributions of excess mortality across the 3 years strongly differed. In Sweden, 60% of excess mortality was observed in 2020, 8% in 2021 and 32% in 2022. In sharp contrast, 0% of excess mortality was observed in Norway in 2020, 20% in 2021 and 80% in 2022. If the relative distribution of excess mortality in Sweden had been the same as in Norway in 2020-2022, approximately 7000 individuals who died in 2020 would instead have died as excess mortality in 2022, saving approximately 14,000 person-years in Sweden.

CONCLUSIONS

The report disregards residual confounding due to the broad definition of the period 2020-2022. Mass media should avoid one-sided reporting.

Regional excess mortality in France during COVID-19 pandemic: the first three epidemic periods (March 2020-June 2021)

BACKGROUND

This study aimed to describe the mortality excess during the three first epidemic periods of COVID-19 in all regions of France.

METHODS

Two complementary approaches were implemented. First, we described the number of death of patients infected with or diagnosed with COVID-19 in health care (HC) and medico-social (MS) institutions. Then, we estimated general all-cause mortality excess (all ages) by comparing the mortality observed with the expected mortality. We used a daily number of death model according to a negative binomial distribution, as a function of the long-term trend in mortality (penalized spline function of time) and its seasonal variation (cyclic spline function). The model provided expected mortality during epidemic periods with a 95% credibility interval. Each region defined three epidemic periods, including the overseas territories.

RESULTS

The two approaches were consistent in the most affected regions but there are major regional disparities that vary according to the epidemic period. There is an east-west gradient in the relative excess of deaths from all-causes during each epidemic period. The deaths observed in HC and MS institutions alone do not explain the excess (or deficit) of mortality in each region and epidemic period.

CONCLUSION

An analysis by age group according to the two approaches and a comparison of death specific causes could provide a better understanding of these differences. Electronic death registration system (mortality by medical causes) would allow a rapid mortality related estimation to an emerging pathology like Coronavirus Disease-2019 (COVID-19) but is still insufficient for real-time medical causes of death monitoring.

Excess mortality in adults from Sao Paulo during the COVID-19 pandemic in 2020: analyses of all-cause and noncommunicable diseases mortality

In this study, we estimated the excess mortality from all-causes of death and noncommunicable diseases (NCDs) in adults living in the state of São Paulo during the COVID-19 pandemic in 2020. Number of deaths were retrieved from the Mortality Information System before (2017-2019) and during (2020) the COVID-19 pandemic, considering the following underlying causes of death: Neoplasms; Diabetes Mellitus; Circulatory System Diseases, and Respiratory System Diseases. Standardized Mortality Ratio (SMR) were calculated by dividing the mortality rates in 2020 by average mortality rates in 2017-2019, according to sex, age group, geographic location (state, capital, and Regional Health Departments). In 2020, occurred 341,704 deaths in the state of São Paulo vs 290,679 deaths in 2017-2019, representing an 18% increase in all-cause mortality (SMR 1.18) or 51,025 excess deaths during the first year of COVID-19 pandemic. The excess mortality was higher in men (186,741 deaths in 2020 vs 156,371 deaths in 2017-2019; SMR 1.18; 30,370 excess deaths) compared to women (154,963 deaths in 2020 vs 134,308 deaths in 2017-2019; SMR 1.15; 20,655 excess deaths). Regarding NCDs mortality, we observed a reduction in cancer mortality (SMR 0.98; -1,354 deaths), diseases of the circulatory system (SMR 0.95; -4,277 deaths), and respiratory system (SMR 0.88; -1,945). We found a 26% increase in Diabetes Mellitus mortality (SMR 1.26; 2885 deaths) during the pandemic year. Our findings corroborate the need to create and strengthen policies aimed at the prevention and control of NCDs, in order to mitigate the impact of future infectious disease pandemics.

Effect of the COVID-19 pandemic on life expectancy in Australia, 2020-22

BACKGROUND

Australia provides a valuable international case study of life expectancy during the pandemic. In contrast to many other countries, it experienced relatively stringent restrictions and low COVID-19 mortality during 2020-21, followed by relaxation of these restrictions when high vaccination rates were achieved. This study measures Australia's life expectancy trends and the contributions of age group and causes of death, during the pandemic.

METHODS

Trends in life expectancy at birth in Australia and its states and territories were measured from 2020 to 2022. The contributions of age group and cause of death to these trends were measured using decomposition methods. Life expectancy was compared with other high-income countries.

RESULTS

Australia's life expectancy fell by more than half a year in 2022, following a sharp increase in 2020 and moderate decline in 2021. For the 3 years 2020 to 2022, life expectancy was 0.13 years (95% confidence interval 0.07-0.19) higher for males and 0.09 years (0.03-0.14) higher for females versus 2017-19. Australia's life expectancy increase in 2020 was larger than that in the vast majority of other high-income countries, but its decline in 2022 was greater than in other countries whose life expectancy rose in the first year of the pandemic. The small negative contribution of COVID-19 deaths to life expectancy in Australia was more than offset by lower non-communicable disease mortality. There were only small differences in life expectancy change between the states with the most stringent restrictions (Victoria and New South Wales) and the rest of Australia.

CONCLUSIONS

Australia's life expectancy trends during 2020-22 were relatively favourable compared with other high-income countries, with the exception of its sharp decline in 2022 once restrictions were loosened.

Unmasking the COVID-19 pandemic prevention gains: excess mortality reversal in 2022

OBJECTIVES

The purpose of this study was to assess the long-term effectiveness of COVID-19 pandemic prevention measures in saving lives after European governments began to lift restrictions.

STUDY DESIGN

Excess mortality interrupted time series.

METHODS

Country-level weekly data on deaths were fitted to the Poisson mixed linear model to estimate excess deaths. Based on this estimate, the percentage of excess deaths above the baseline during the pandemic (week 11 in 2020 to week 15 in 2022) (when public health interventions were in place) and during the post-pandemic period (week 16 in 2022 to week 52 in 2022) were calculated. These results were fitted to the linear regression model to determine any potential relationship between mortality during these two periods.

RESULTS

The model used in this study had high predictive value (adjusted R2 = 59.4%). Mortality during the endemic (post-pandemic) period alone increased by 7.2% (95% confidence interval [CI]: 5.7, 8.6) above baseline, while each percentage increase in mortality during the pandemic corresponded to a 0.357% reduction (95% CI: 0.243, 0.471) in mortality during the post-pandemic period.

CONCLUSIONS

The most successful countries in terms of protective measures also experienced the highest mortality rates after restrictions were lifted. The model used in this study clearly shows a measure of bidirectional mortality displacement that is sufficiently clear to mask any impact of long COVID on overall mortality. Results from this study also seriously impact previous cost-benefit analyses of pandemic prevention measures, since, according to the current model, 12.2% (95% CI: 8.3, 16.1) of the gains achieved in pandemic containment were lost after restrictions were lifted.

Long-Term Outcomes of Breast Cancer Patients Receiving Levobupivacaine Wound Infiltration or Diclofenac for Postoperative Pain Relief

Breast cancer is the most common malignant disease in women. Preclinical studies have confirmed that the local anesthetic levobupivacaine has a cytotoxic effect on breast cancer cells. We examined whether postoperative wound infiltration with levobupivacaine influences survival in 120 patients who were operated on for breast cancer and underwent quadrantectomy or mastectomy with axillary lymph node dissection. Groups with continuous levobupivacaine wound infiltration, bolus wound infiltration, and diclofenac analgesia were compared. Long-term outcomes examined were quality of life, shoulder disability, and hand grip strength (HGS) after one year and survival after 5 and 10 years. Groups that had infiltration analgesia had better shoulder function compared to diclofenac after one year. The levobupivacaine PCA group had the best-preserved HGS after 1 year (P = 0.022). The most significant predictor of the 5-year outcome was HGS (P = 0.03). Survival at 10 years was 85%, 92%, and 77% in the diclofenac, levobupivacaine bolus, and levobupivacaine PCA groups (ns. P = 0.36). The extent of the disease at the time of surgery is the most important predictor of long-term survival (P = 0.03). A larger prospective clinical study could better confirm the effect of levobupivacaine wound infiltration on outcomes after breast cancer surgery observed in this pilot study-trial number NCT05829707.

Policies on children and schools during the SARS-CoV-2 pandemic in Western Europe

During the pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), mitigation policies for children have been a topic of considerable uncertainty and debate. Although some children have co-morbidities which increase their risk for severe coronavirus disease (COVID-19), and complications such as multisystem inflammatory syndrome and long COVID, most children only get mild COVID-19. On the other hand, consistent evidence shows that mass mitigation measures had enormous adverse impacts on children. A central question can thus be posed: What amount of mitigation should children bear, in response to a disease that is disproportionally affecting older people? In this review, we analyze the distinct child versus adult epidemiology, policies, mitigation trade-offs and outcomes in children in Western Europe. The highly heterogenous European policies applied to children compared to adults did not lead to significant measurable differences in outcomes. Remarkably, the relative epidemiological importance of transmission from school-age children to other age groups remains uncertain, with current evidence suggesting that schools often follow, rather than lead, community transmission. Important learning points for future pandemics are summarized.

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

The Nordic countries offer an ideal case study of the COVID-19 pandemic due to their comparability, high data quality, and variable mitigations. We investigated the age- and sex-specific mortality patterns during 2020-2021 for the five Nordic countries and analysed the total age- and sex-adjusted excess deaths, ratios of actual to expected death rates, and age-standardized excess death estimates. We assessed excess deaths using several time periods and sensitivity tests, and 42 sex and age groups. Declining pre-pandemic age-specific death rates reflected improving health demographics. These affect the expected death estimates and should be accounted for in excess mortality models. Denmark had the highest death rates both before and during the pandemic, whereas in 2020 Sweden had the largest mortality increase. The age-standardized mortality of Denmark, Iceland and Norway was lowest in 2020. 2021 was one of the lowest mortality years for all Nordic countries. The total excess deaths in 2020-2021 were dominated by 70-89-year-olds, were not identified in children, and were more pronounced among men than women. Sweden had more excess deaths in 2020 than in 2021, whereas Finland, Norway and Denmark had the opposite. Our study provides new details on Nordic sex- and age-specific mortality during the first two years of the pandemic and shows that several metrics are important to enable a full understanding and comparison of the pandemic mortality.

Estimates of excess mortality during the COVID-19 pandemic strongly depend on subjective methodological choices

Excess mortality is often used to assess the health impact of the COVID-19 pandemic. It involves comparing the number of deaths observed during the pandemic with the number of deaths that would counterfactually have been expected in the absence of the pandemic. However, published data on excess mortality often vary even for the same country. The reason for these discrepancies is that the estimation of excess mortality involves a number of subjective methodological choices. The aim of this paper was to summarize these subjective choices. In several publications, excess mortality was overestimated because population aging was not adjusted for. Another important reason for different estimates of excess mortality is the choice of different pre-pandemic reference periods that are used to estimate the expected number of deaths (e.g., only 2019 or 2015-2019). Other reasons for divergent results include different choices of index periods (e.g., 2020 or 2020-2021), different modeling to determine expected mortality rates (e.g., averaging mortality rates from previous years or using linear trends), the issue of accounting for irregular risk factors such as heat waves and seasonal influenza, and differences in the quality of the data used. We suggest that future studies present the results not only for a single set of analytic choices, but also for sets with different analytic choices, so that the dependence of the results on these choices becomes explicit.

Assessing COVID-19-Related Excess Mortality Using Multiple Approaches-Italy, 2020-2021

INTRODUCTION

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.

METHODS

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.

RESULTS

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.

DISCUSSION

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.