COVID-19 control measure effects suggest excess winter mortality is more sensitive to infection control than warmer temperatures

  1. Lucy Telfar-Barnard
  2. Michael G Baker
  3. Amanda Kvalsvig
  4. Nick Wilson

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Abstract

Background

Excess winter mortality (EWM) has been attributed to both seasonal cold exposure, and to infectious disease. In 2020, New Zealand’s border management and lockdown measures successfully eliminated community transmission of SARS-CoV-2, and also largely eliminated influenza and many other respiratory viruses. This study investigates the contribution of infections and temperature to EWM and typical extended winter (May to October) deaths in this natural experiment created by New Zealand’s COVID-19 pandemic response.

Methods

We used age-standardised weekly deaths to measure EWM 2011 to 2019, then used historical patterns to estimate high, medium and low scenario 2020 EWMs. We then modelled typical year and 2020 heating degree day: mortality relationships to estimate relative contributions of cold temperature and infection to typical EWEDs.

Results

EWM 2011 to 2019 averaged 14.7% (low 11.4%, high 20.9%). In contrast, 2020 EWM was estimated at 1.6%, 2.7%, or 3.8% under high, medium, and low spring-summer mortality scenarios. Between 2011 and 2019, temperature was estimated to explain 47% of extended winter deaths, and infection 27%, with the remaining 26% attributable to the interaction between infection and temperature.

Discussion

The society-wide response to COVID-19 in 2020 resulted in a major reduction of winter mortality in this high-income nation with a temperate climate. In addition to influenza, other respiratory pathogens likely also make a significant contribution to EWM. Low cost protection measures such as mask wearing (eg, in residential care facilities), discouragement of sick presenteeism, and increased influenza vaccine coverage, all have potential to reduce future winter mortality.

Research in context

Evidence before this study

Excess winter mortality (EWM) is a widely observed phenomenon, commonly attributed to physiological responses to short and long-term outdoor and indoor cold exposure (and associated increased air pollution); other seasonal physiology changes; and higher incidence of some infectious diseases. Previous estimates of EWM in New Zealand range from 10.3% to 25.6%, with influenza estimated to make up roughly a third of that excess. Internationally, deaths attributable to cold temperatures are also found outside the traditional winter period, with influenza making a large contribution to cold temperature deaths.

Added value of this study

This study finds that following a successful COVID-19 elimination strategy, which simultaneously prevented the annual winter influenza season, and likely other winter respiratory infections, New Zealand is likely in 2020 to experience less than a third of the usual winter mortality excess. Further, this study for the first time estimates the relative contributions of cold temperature and infection, and the interaction between the two, to New Zealand winter deaths. We estimate that of the 9.5% fewer deaths than in typical years recorded between 1 May and 31 October 2020, 92.5% were prevented by infection control measures; 1.4% by the 1.14°C warmer than average winter; and 6.1% by the interaction between infection and low temperature.

Implications of all the available evidence

Influenza and other infectious respiratory pathogens appear to make a much larger contribution to winter mortality than previously recognised. Low cost protection measures such as mask wearing (eg, in residential care facilities), discouragement of sick presenteeism, and increased influenza vaccine coverage, all have potential to reduce future winter deaths, and lower overall annual mortality rates.

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  1. ScreenIT

    SciScore for 10.1101/2020.12.19.20248531: (What is this?)

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

    Table 1: Rigor

    NIH rigor criteria are not applicable to paper type.

    Table 2: Resources

    No key resources detected.

    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: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.

    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.

    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.

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  2. Version published to 10.1101/2020.12.19.20248531 on medRxiv