Evidence map›Paper›PMID 42366842›Full record

ArticleJournal of medical virology2026

How Many Veteran COVID-19 Cases Were There during the Pandemic?

Wathsala N Widanagamaachchi, Ariana R Callahan, Tina M Willson, Bree Barbeau, Julia E Lewis, Christian D Dalton, Vanessa W Stevens, Matthew Samore, Nathorn Chaiyakunapruk, Makoto M Jones

Abstract read
In one paragraph

Article in Journal of medical virology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Wathsala N WidanagamaachchiDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.
Ariana R CallahanDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.ORCID https://orcid.org/0009-0003-1897-8840
Tina M WillsonDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.
Bree BarbeauDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.
Julia E LewisIDEAS Center, Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, Utah, USA.
Christian D DaltonDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.
Vanessa W StevensDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.
Matthew SamoreDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.
Nathorn ChaiyakunaprukIDEAS Center, Veterans Affairs Salt Lake City Healthcare System, Salt Lake City, Utah, USA.ORCID https://orcid.org/0000-0003-4572-8794
Makoto M JonesDivision of Epidemiology, Department of Internal Medicine, Spencer Fox Eccles School of Medicine, University of Utah, Salt Lake City, Utah, USA.

Funding

CDC HHS 200-2016-91799CDC HHS CDC-RFA-FT-23-0069
6 · The paper itself

Abstract

This study estimates the incidence of symptomatic COVID-19 cases, both documented and undocumented, among U.S. Veterans across demographic groups from the beginning of the pandemic to the end of the public health emergency on May 11, 2023. By analyzing a cohort of Veterans alive as of March 1, 2020, we extended a mortality-based estimation approach to measure COVID-19 incidence. We relaxed the assumptions of a constant infection fatality rate (IFR) over time and across age groups and broadened the model from considering only excess respiratory deaths to including excess all-cause deaths. Descriptive analyses were performed to understand differential ascertainment biases among demographic groups. Resulting estimates suggested a significantly higher number of COVID-19 cases among Veterans than those documented in the electronic health record. We also identified varying biases among different demographic groups. These estimates offer a clearer view of COVID-19's impact on Veterans, accounting for missed cases among those who sought care outside of the VA. Differences between documented and estimated cases were substantial. Policymakers should recognize that actual numbers are likely much higher than documented and that documented rates may not be directly comparable across populations or time periods.

Indexed as

COVID-19VeteransAdultAgedAged, 80 and overFemaleHumansIncidenceMiddle AgedPandemicsSARS-CoV-2United StatesYoung AdultbiasCOVID‐19incidencepandemicspolicyUnited Statesveterans

Identifiers

PMID42366842
PMCPMC13311740

What Socratic holds

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LicenceCC BY
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Registered trials

None linked

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 Socratic graph.