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Abstract

Background

Timely monitoring of COVID-19 impact on mortality is critical for rapid risk assessment and public health action.

Aim

Building upon well-established models to estimate influenza-related mortality, we propose a new statistical Attributable Mortality Model (AttMOMO), which estimates mortality attributable to one or more pathogens simultaneously (e.g. SARS-CoV-2 and seasonal influenza viruses), while adjusting for seasonality and excess temperatures.

Methods

Data from Nationwide Danish registers from 2014-week(W)W27 to 2020-W22 were used to exemplify utilities of the model, and to estimate COVID-19 and influenza attributable mortality from 2019-W40 to 2020-W20.

Results

SARS-CoV-2 was registered in Denmark from 2020-W09. Mortality attributable to COVID-19 in Denmark increased steeply, and peaked in 2020-W14. As preventive measures and national lockdown were implemented from 2020-W12, the attributable mortality started declining within a few weeks. Mortality attributable to COVID-19 from 2020-W09 to 2020-W20 was estimated to 16.2 (95% confidence interval (CI): 12.0 to 20.4) per 100,000 person-years. The 2019/20 influenza season was mild with few deaths attributable to influenza, 3.2 (95% CI: 1.1 to 5.4) per 100,000 person-years.

Conclusion

AttMOMO estimates mortality attributable to several pathogens simultaneously, providing a fuller picture of mortality by COVID-19 during the pandemic in the context of other seasonal diseases and mortality patterns. Using Danish data, we show that the model accurately estimates mortality attributable to COVID-19 and influenza, respectively. We propose using standardised indicators for pathogen circulation in the population, to make estimates comparable between countries and applicable for timely monitoring.

© Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
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2021-02-25
2024-05-08
http://instance.metastore.ingenta.com/content/10.2807/1560-7917.ES.2021.26.8.2001646
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Estimates of mortality attributable to COVID-19: a statistical model for monitoring COVID-19 and seasonal influenza, Denmark, spring 2020
<p class="citation"> <span>Citation style for this article:</span> <span class="meta-value authors"> <a href="/search?value1=Jens+Nielsen&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Nielsen Jens</a>, <a href="/search?value1=Naja+Hulvej+Rod&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Rod Naja Hulvej</a>, <a href="/search?value1=Lasse+S+Vestergaard&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Vestergaard Lasse S</a>, <a href="/search?value1=Theis+Lange&option1=author&noRedirect=true" class="nonDisambigAuthorLink">Lange Theis</a></span>. Estimates of mortality attributable to COVID-19: a statistical model for monitoring COVID-19 and seasonal influenza, Denmark, spring 2020. <a href="/content/ecdc">Euro Surveill.</a> 2021;26(8):pii=2001646. <a href="https://doi.org/10.2807/1560-7917.ES.2021.26.8.2001646" title="doi link" target="_blank">https://doi.org/10.2807/1560-7917.ES.2021.26.8.2001646</a> <span class="ES_Article_citation"> <span class="generated">Received</span>: 10 Sept 2020;&nbsp;&nbsp; <span class="generated">Accepted</span>: 10 Nov 2020 </span> </p>
/content/10.2807/1560-7917.ES.2021.26.8.2001646
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