Evidence map›Paper›PMID 38793804›Full record

ArticleVaccines2024

Confronting Inequalities and Bridging the Divide: A Retrospective Study Assessment of Country-Level COVID-19 Vaccine Equality with a Cox Regression Model.

Lan Cheng, W K Chan, Lijie Zhu, Melody H Chao, Yang Wang

Abstract read
In one paragraph

Article in Vaccines, 2024. 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

5 authors.

Lan ChengBig Data Bio-Intelligence Laboratory, Big Data Institute, The Hong Kong University of Science and Technology, Hong Kong, China.
W K ChanDepartment of Computer Science and Engineering, The Chinese University of Hong Kong, Hong Kong, China.
Lijie ZhuFaculty of Medicine, The Chinese University of Hong Kong, Hong Kong, China.
Melody H ChaoCollege of Art and Design, Shenzhen University, Shenzhen 518060, China.
Yang WangBig Data Bio-Intelligence Laboratory, Big Data Institute, The Hong Kong University of Science and Technology, Hong Kong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 vaccination is vital in reducing illness, hospitalization, and mortality in the face of this global pandemic. However, COVID-19 vaccination rates worldwide remain below WHO public health targets, and persistent structural inequities reduce vaccine uptake likelihood among populations of low socioeconomic status. We conducted a cross-sectional study based on publicly available data from the Our World in Data project. We included all 124 countries with available open epidemic data and a population of more than 5 million. We used a Cox Regression Model, with population, population density, median age, human development index, GDP per capita, gender inequality index, healthcare access and quality index, hospital beds per thousand people, completion rate of primary education, infection cases of COVID-19 by the end of 2022, and death rate due to COVID-19 by the end of 2022 as predictors for model hazard rates of completion of 50% population vaccination. According to our study, countries with higher populations, higher population density, higher human development index, lower gender inequality index, and lower hospital beds per 1000 people had a higher hazard rate, which means they were more likely to achieve 50% population vaccination faster. By utilizing the time to achieve vaccination rate goals as our primary endpoint, we evaluated inequity from a dual perspective, considering both the differences in vaccination rates and the duration required to attain them. Consequently, this study employed survival analysis approaches to gain a comprehensive understanding of vaccine drivers and population-level trends nationally and inform all communities from a statistical perspective to prepare for health emergencies. Development-level standing modified the effects of equal access to COVID-19 vaccination on cumulative cases and mortality, for which countries of low or medium human development tended to fare worse in outcomes than high human development countries. As COVID-19 vaccination efforts evolve, healthcare professionals, scholars, and policymakers need to identify the structural impediments to equitable vaccination awareness, access, and uptake so that future vaccination campaigns are not impeded by these barriers to immunization. Recognizing the complex nature of this significant barrier, it is evident that no single statistical analysis method can comprehensively address all intricacies.

Indexed as

COVID-19 pandemicglobal health systemhuman development indexvaccine equity

Identifiers

PMID38793804
PMCPMC11125969

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.