Evidence map›Paper›PMID 37885754›Full record

ArticleAJPM focus2023

Seroprevalence as an Indicator of Undercounting of COVID-19 Cases in a Large Well-Described Cohort.

Kevin M Taylor, Keersten M Ricks, Paul A Kuehnert, Angelia A Eick-Cost, Mark R Scheckelhoff, Andrew R Wiesen, Tamara L Clements, Zheng Hu, Samantha E Zak, Scott P Olschner and 5 more

Open access · goldAbstract read
In one paragraph

Article in AJPM focus, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
1.2field-weighted citation impact, top 22% of its field
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

5 citing papers in PubMed, 6 citations in OpenAlex.

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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

15 authors at 4 institutions in 1 country.

Kevin M TaylorArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Keersten M RicksUnited States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland.
Paul A KuehnertUnited States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland.
Angelia A Eick-CostArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Mark R ScheckelhoffArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Andrew R WiesenHealth Readiness Policy and Oversight, Office of the Assistant Secretary of Defense for Health Affairs, Washington, District of Columbia.
Tamara L ClementsUnited States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland.
Zheng HuArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Samantha E ZakUnited States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland.
Scott P OlschnerUnited States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland.
Andrew S HerbertUnited States Army Medical Research Institute of Infectious Diseases, Frederick, Maryland.
Sara L BazacoArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Kathleen E CreppageArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Michael T FanArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Jose L SanchezArmed Forces Health Surveillance Division, Defense Health Agency, Silver Spring, Maryland.
Defense Health Agency · USUnited States Army Medical Research Institute of Infectious Diseases · USOffice of the Secretary of Defense · USUniformed Services University of the Health Sciences · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Reported confirmed cases represent a small portion of overall true cases for many infectious diseases. The undercounting of true cases can be considerable when a significant portion of infected individuals are asymptomatic or minimally symptomatic, as is the case with COVID-19. Seroprevalence studies are an efficient way to assess the extent to which true cases are undercounted during a large-scale outbreak and can inform efforts to improve case identification and reporting. Methods: A longitudinal seroprevalence study of active duty U.S. military members was conducted from May 2020 through June 2021. A random selection of service member serum samples submitted to the Department of Defense Serum Repository was analyzed for the presence of antibodies reactive to SARS-CoV-2. The monthly seroprevalence rates were compared with those of cumulative confirmed cases reported during the study period. Results: Seroprevalence was 2.3% in May 2020 and increased to 74.0% by June 2021. The estimated true case count based on seroprevalence was 9.3 times greater than monthly reported cases at the beginning of the study period and fell to 1.7 by the end of the study. Conclusions: In our sample, confirmed case counts significantly underestimated true cases of COVID-19. The increased availability of testing over the study period and enhanced efforts to detect asymptomatic and minimally symptomatic cases likely contributed to the fall in the seroprevalence to reported case ratio.

Indexed as

COVID-19infectious disease surveillancemilitary public healthSARS-CoV-2seroprevalence

Identifiers

PMID37885754
PMCPMC10598697
OpenAlexW4385840709

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

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 OpenQuestion graph.