Evidence map›Paper›PMID 36202641›Full record

ArticleVaccine2022

Supply, then demand? Health expenditure, political leanings, cost obstacles to care, and vaccine hesitancy predict state-level COVID-19 vaccination rates.

Joshua Teperowski Monrad, Sebastian Quaade, Timothy Powell-Jackson

Abstract read
In one paragraph

Article in Vaccine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Trial
  2. Review
  3. 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

3 authors.

Joshua Teperowski MonradFuture of Humanity Institute, University of Oxford, Oxford, UK. Electronic address: joshua.monrad@gmail.com.
Sebastian QuaadeIndependent Researcher, CA, United States.
Timothy Powell-JacksonFaculty of Public Health and Policy, London School of Hygiene and Tropical Medicine, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo examine predictors of state-level COVID-19 vaccination rates during the first nine months of 2021.

methodsUsing publicly available data, we employ a robust, iteratively re-weighted least squares multivariable regression with state characteristics as the independent variables and vaccinations per capita as the outcome. We run this regression for each day between February 1 and September 21, the last day before vaccine booster rollout.

resultsWe identify associations between vaccination rates and several state characteristics, including health expenditure, vaccine hesitancy, cost obstacles to care, Democratic voting, and elderly population share. We show that the determinants of vaccination rates have evolved: while supply-side factors were most clearly associated with early vaccination uptake, demand-side factors have become increasingly salient over time. We find that our results are generally robust to a range of alternative specifications.

conclusionsBoth supply and demand-side factors relate to vaccination coverage and the determinants of success have changed over time. POLICY IMPLICATIONS: Investing in health capacity may improve early vaccine distribution and administration, while overcoming vaccine hesitancy and cost obstacles to care may be crucial for later immunisation campaign stages.

Indexed as

COVID-19VaccinesAgedCOVID-19 VaccinesHealth ExpendituresHumansVaccinationVaccination HesitancyCOVID-19 VaccinesVaccines

Identifiers

PMID36202641
PMCPMC9452439

What OpenQuestion holds

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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 OpenQuestion graph.