Evidence map›Paper›PMID 34561932›Full record

ArticleHealth economics2021

Immediate and informative feedback during a pandemic: Using stated preference analysis to predict vaccine uptake rates.

William F Vásquez, Jennifer M Trudeau, Jessica Alicea-Planas

Abstract read
In one paragraph

Article in Health economics, 2021. 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. Achilles' heel: elderly COVID-19 vaccination policy in China.Health research policy and systems · 2024
    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

3 authors.

William F VásquezDepartment of Economics, Fairfield University, Fairfield, Connecticut, USA.
Jennifer M TrudeauDepartment of Business Economics, Sacred Heart University, Fairfield, Connecticut, USA.ORCID 0000-0002-1502-4940
Jessica Alicea-PlanasEgan School of Nursing and Health Sciences, Fairfield University, Fairfield, Connecticut, USA.

Funding

Fairfield UniversityWellcome Trust
6 · The paper itself

Abstract

In response to an emerging pandemic, there is urgent need for information regarding individual evaluation of risk and preferences toward mitigation strategies such as vaccinations. However, with social distancing policies and financial stress during an outbreak, traditional robust survey methodologies of face-to-face, probabilistic sampling, may not be feasible to deploy quickly, especially in developing countries. We recommend a protocol that calls for a sensitive survey design, acceptance of a web-based approach and adjustments for uncertainty of respondents, to deliver urgently needed information to policymakers as the public health crisis unfolds, rather than in its aftermath. This information is critical to tailor comprehensive vaccination campaigns that reach critical immunity thresholds. We apply our recommendations in a regional study of 16 Latin American countries in the month following index cases of COVID-19. We use a split-sample, contingent valuation approach to evaluate the effects of cost, duration of immunity and effectiveness of the vaccine. Our results show that cost and duration of immunity are significant factors in the decision to vaccinate, while the degree of effectiveness is insignificant, unless the vaccine is 100% effective. Income as well as perceived risk and severity of the virus are important determinants also.

Indexed as

COVID-19VaccinesFeedbackHumansPandemicsSARS-CoV-2VaccinationVaccinescontingent behaviorLatin Americapandemicvaccine uptake ratewillingness to pay

Identifiers

PMID34561932
PMCPMC8646631

What OpenQuestion holds

Textmetadata
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.