High excess mortality in areas with young and socially vulnerable populations during the COVID-19 outbreak in Stockholm Region, Sweden

  1. Amaia Calderón-Larrañaga
  2. Davide L Vetrano
  3. Debora Rizzuto
  4. Tom Bellander
  5. Laura Fratiglioni
  6. Serhiy Dekhtyar

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Abstract

We aimed to describe the distribution of excess mortality (EM) during the first weeks of the COVID-19 outbreak in the Stockholm Region, Sweden, according to age, sex and sociodemographic context.

Methods

Weekly all-cause mortality data were obtained from Statistics Sweden for the period 1 January 2015 to 17 May 2020. EM during the first 20 weeks of 2020 was estimated by comparing observed mortality rates with expected mortality rates during the five previous years (N=2 379 792). EM variation by socioeconomic status (tertiles of income, education, Swedish-born, gainful employment) and age distribution (share of 70+-year-old persons) was explored based on Demographic Statistics Area (DeSO) data.

Results

EM was first detected during the week of 23–29 March 2020. During the peak week of the epidemic (6–12 April 2020), an EM of 150% was observed (152% in 80+-year-old women; 183% in 80+-year-old men). During the same week, the highest EM was observed for DeSOs with lowest income (171%), lowest education (162%), lowest share of Swedish-born (178%) and lowest share of gainfully employed residents (174%). EM was further increased in areas with higher versus lower proportion of younger people (magnitude of increase: 1.2–1.7 times depending on socioeconomic measure).

Conclusion

Living in areas characterised by lower socioeconomic status and younger populations was linked to excess mortality during the COVID-19 pandemic in the Stockholm Region. These conditions might have facilitated viral spread. Our findings highlight the well-documented vulnerability linked to increasing age and sociodemographic context for COVID-19–related death.

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  1. Version published to 10.1136/bmjgh-2020-003595
  2. ScreenIT

    SciScore for 10.1101/2020.07.07.20147983: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board Statementnot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Stata 16 (StataCorp) has been used for all the analyses.
    StataCorp
    suggested: (Stata, RRID:SCR_012763)

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).

    Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:
    The lack of availability of electronic records with wide individual and contextual data coverage has in fact been pointed out as one of the weaknesses of the current response to the COVID-19 pandemic in developed countries, and referred to as one of the most important strategies to successfully cope with future similar scenarios.24 Study limitations: For confidentiality reasons, we did not have data on DeSO-level mortality, which prevented us from obtaining variance estimates within DeSO groups. Given the lack of availability of individual-level data, we cannot ascertain the age of subjects contributing to the exceptionally high rates of excess mortality seen in the deprived young neighborhoods of the Stockholm Region. Still, we have reasons to believe that they are most likely 65 years or older, as is the case for the rest of the population. If, in the worst-case scenario, all people dying in these areas were below 65, the mortality rate for this age group during e.g. the peak week of 6-12 April 2020 would not make up for the actual number of deaths observed during that week (expected: 16 deaths; observed: 132-150 deaths depending on the socioeconomic indicator considered). Considering that the 2019-2020 winter in Stockholm was one of the mildest on record, the observed mortality in the period before the COVID-19 outbreak was in the low range in comparison with previous years.25 Thus, it is likely that the calculated excess mortality is underestimated. In fact, when comparin...

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    Results from JetFighter: We did not find any issues relating to colormaps.

    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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  3. Version published to 10.1101/2020.07.07.20147983v1 on medRxiv