Evidence map›Paper›PMID 36561183›Full record

ArticleResearch square2022

Understanding COVID-19 Vaccine Effectiveness Against Death Using a Novel Measure: COVID Excess Mortality Percentage.

Andy Yuan, Vladimir Atanasov, Paula Natalia Barreto Parra, Jeff Whittle, John Meurer, Benjamin Weston, Qian Eric Luo, Lorenzo Franchi, Ruohao Zhang, Bernard Black

Abstract readPreprint
In one paragraph

Article in Research square, 2022. 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

5 · Who and what money

Authors and funding

10 authors.

Andy YuanNorthwestern University.ORCID 0000-0002-1545-6129
Vladimir AtanasovWilliam & Mary.ORCID 0000-0002-1893-6187
Paula Natalia Barreto ParraUniversity of Illinois, Urbana-Champaign.
Jeff WhittleMedical College of Wisconsin.
John MeurerMedical College of Wisconsin.
Benjamin WestonMedical College of Wisconsin.
Qian Eric LuoGeorge Washington University.
Lorenzo FranchiNorthwestern University.
Ruohao ZhangCentre College.
Bernard BlackNorthwestern University.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 vaccines have saved millions of lives and prevented countless adverse patient disease outcomes. Understanding the long-term effectiveness of these vaccines is imperative to developing recommendations for precautions and booster doses. Comparisons between more and less vaccinated groups may be misleading due to selection bias, as these groups may differ in underlying health status and thus risk of adverse COVID-19 outcomes. We study all adult deaths over April 1, 2021-June 30, 2022 in Milwaukee County, Wisconsin, linked to vaccination records, use mortality from other natural causes to proxy for underlying health, and report relative COVID-19 mortality risk (RMR) for vaccinees versus the unvaccinated, using a novel outcome measure that controls for selection effects. This measure, COVID Excess Mortality Percentage (CEMP) uses the non-COVID natural mortality rate (Non-Covid-NMR) as a measure of population risk of COVID mortality without vaccination. We validate this measure during the pre-vaccine period (r = 0.97) and demonstrate that selection effects are large, with Non-Covid-NMRs for two-dose vaccinees less than half those for the unvaccinated, and Non-COVID NMRs still lower for three dose (booster) recipients. Progressive waning of two-dose effectiveness is observed, with relative mortality risk (RMR) for two-dose vaccinees aged 60 + versus the unvaccinated of 11% during April-June 2021, rising steadily to 36% during the Omicron period (January-June, 2022). Notably, a booster dose reduced RMR to 10-11% for ages 60+. Boosters thus provide important additional protection against mortality.

Identifiers

PMID36561183
PMCPMC9774224

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.