Evidence map›Paper›PMID 39218423›Full record

ArticleAmerican journal of epidemiology2025

Tracking vaccine effectiveness in an evolving pandemic, countering misleading hot takes and epidemiologic fallacies.

Jeffrey S Morris

Abstract read
In one paragraph

Article in American journal of epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

1 author.

Jeffrey S MorrisDepartment of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States.ORCID 0000-0002-8520-6088

Funding

Phenotypic Diversity in COVID-19UL1TR001878 · NCATS · UNIVERSITY OF PENNSYLVANIA · PI FITZGERALD, GARRET A · 2016 to 2025
$102.4M
NCATS NIH HHS UL1 TR001878
6 · The paper itself

Abstract

With the emergence of Omicron during the pandemic and the establishment of antibody waning over time, vaccine effectiveness, especially against infection, declined sharply from the original levels seen after the initial rollout. However, studies have demonstrated that they still provided substantial protection vs severe/fatal disease even with Omicron and after waning. Social media has been rife with reports claiming vaccines provided no benefit and some even claiming they made things worse, often driven by simple presentations of raw observational data using erroneous arguments involving epidemiologic fallacies including the base rate fallacy, Simpson's paradox, and the ecological fallacy and ignoring the extensive bias especially from confounding that is an inherent feature of these data. Similar fallacious arguments have been made by some in promoting vaccination policies, as well. Generally, vaccine effectiveness cannot be accurately estimated from raw population summaries but instead require rigorous, careful studies using epidemiologic designs and statistical analysis tools attempting to adjust for key confounders and sources of bias. This article summarizes what aggregated evidence across studies reveals about effectiveness of the mRNA vaccines as the pandemic has evolved, chronologically summarized with emerging variants and highlighting some of the fallacies and flawed arguments feeding social media-based claims that have obscured society's collective understanding.

Indexed as

COVID-19COVID-19 VaccinesPandemicsVaccine EfficacyBiasHumansSARS-CoV-2Social MediaCOVID-19 Vaccinesbase rate fallacyconfounding by indicationCOVID-19ecological fallacySimpson’s paradoxvaccine effectiveness

Identifiers

PMID39218423
PMCPMC11978612

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.