Evidence map›Paper›PMID 38432749›Full record

ArticleMayo Clinic proceedings2024

The Importance of Estimating Excess Deaths Regionally During the COVID-19 Pandemic.

Suzette J Bielinski, Sheila M Manemann, Guilherme S Lopes, Ruoxiang Jiang, Susan A Weston, R Ross Reichard, Aaron D Norman, Celine M Vachon, Paul Y Takahashi, Mandeep Singh and 3 more

Abstract read
In one paragraph

Article in Mayo Clinic proceedings, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Suzette J BielinskiDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN. Electronic address: bielinski.suzette@mayo.edu.
Sheila M ManemannDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
Guilherme S LopesDivision of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
Ruoxiang JiangDivision of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
Susan A WestonDivision of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
R Ross ReichardDepartment of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN.
Aaron D NormanDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
Celine M VachonDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
Paul Y TakahashiDivision of Community Internal Medicine, Department of Medicine, Mayo Clinic, Rochester, MN.
Mandeep SinghDepartment of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.
Nicholas B LarsonDivision of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.
Véronique L RogerDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN; Epidemiology and Community Health Branch, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, MD.
Jennifer L St SauverDivision of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN.

Funding

Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology ProjectR33AG058738 · NIA · MAYO CLINIC ROCHESTER · PI LEBRASSEUR, NATHAN K, OLSON, JANET E · 2020 to 2022
$2.4M
Interdisciplinary Infrastructure for Aging Research: Rochester Epidemiology ProjectR21AG058738 · NIA · MAYO CLINIC ROCHESTER · PI LEBRASSEUR, NATHAN K, OLSON, JANET E · 2018 to 2019
$437k
NIA NIH HHS R21 AG058738NIA NIH HHS R33 AG058738
6 · The paper itself

Abstract

National or statewide estimates of excess deaths have limited value to understanding the impact of the COVID-19 pandemic regionally. We assessed excess deaths in a 9-county geographically defined population that had low rates of COVID-19 and widescale availability of testing early in the pandemic, well-annotated clinical data, and coverage by 2 medical examiner's offices. We compared mortality rates (MRs) per 100,000 person-years in 2020 and 2021 with those in the 2019 reference period and MR ratios (MRRs). In 2020 and 2021, 177 and 219 deaths, respectively, were attributed to COVID-19 (MR = 52 and 66 per 100,000 person-years, respectively). COVID-19 MRs were highest in males, older persons, those living in rural areas, and those with 7 or more chronic conditions. Compared with 2019, we observed a 10% excess death rate in 2020 (MRR = 1.10 [95% CI, 1.04 to 1.15]), with excess deaths in females, older adults, and those with 7 or more chronic conditions. In contrast, we did not observe excess deaths overall in 2021 compared with 2019 (MRR = 1.04 [95% CI, 0.99 to 1.10]). However, those aged 18 to 39 years (MRR = 1.36 [95% CI, 1.03 to 1.80) and those with 0 or 1 chronic condition (MRR = 1.28 [95% CI, 1.05 to 1.56]) or 7 or more chronic conditions (MRR = 1.09 [95% CI, 1.03 to 1.15]) had increased mortality compared with 2019. This work highlights the value of leveraging regional populations that experienced a similar pandemic wave timeline, mitigation strategies, testing availability, and data quality.

Indexed as

COVID-19AgedAged, 80 and overChronic DiseaseData AccuracyFemaleHumansMalePandemics

Identifiers

PMID38432749
PMCPMC10914321

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.