Evidence map›Paper›PMID 33208743›Full record

ArticleScientific data2020

The landscape of childhood vaccine exemptions in the United States.

Casey M Zipfel, Romain Garnier, Madeline C Kuney, Shweta Bansal

Abstract readDataset
In one paragraph

Article in Scientific data, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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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

4 authors.

Casey M ZipfelDepartment of Biology, Georgetown University, Washington, DC, USA. cmz27@georgetown.edu.ORCID 0000-0002-7903-6318
Romain GarnierDepartment of Biology, Georgetown University, Washington, DC, USA.
Madeline C KuneyDepartment of Biology, Georgetown University, Washington, DC, USA.
Shweta BansalDepartment of Biology, Georgetown University, Washington, DC, USA. shweta.bansal@georgetown.edu.

Funding

Vaccine hesitancy and erosion of herd immunity: harnessing big data to forecast disease re-emergenceR01GM123007 · NIGMS · GEORGETOWN UNIVERSITY · PI BANSAL, SHWETA · 2017 to 2021
$2.1M
NIGMS NIH HHS R01 GM123007U.S. Department of Health & Human Services | National Institutes of Health (NIH) R01GM123007
6 · The paper itself

Abstract

Once-eliminated vaccine-preventable childhood diseases, such as measles, are resurging across the United States. Understanding the spatio-temporal trends in vaccine exemptions is crucial to targeting public health intervention to increase vaccine uptake and anticipating vulnerable populations as cases surge. However, prior available data on childhood disease vaccination is either at too rough a spatial scale for this spatially-heterogeneous issue, or is only available for small geographic regions, making general conclusions infeasible. Here, we have collated school vaccine exemption data across the United States and provide it at the county-level for all years included. We demonstrate the fine-scale spatial heterogeneity in vaccine exemption levels, and show that many counties may fall below the herd immunity threshold. We also show that vaccine exemptions increase over time in most states, and non-medical exemptions are highly prevalent where allowed. Our dataset also highlights the need for greater data sharing and standardized reporting across the United States.

Indexed as

ChildHumansImmunity, HerdSchoolsSpatial AnalysisUnited StatesVaccinationVaccination RefusalVaccine-Preventable Diseases

Identifiers

PMID33208743
PMCPMC7674502

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.