Evidence map›Paper›PMID 39530400›Full record

ArticleGlobal health action2024

Measuring influencing factors affecting mortality rates during the COVID-19 pandemic.

Jih-Shong Wu, Kuo-Kuang Huang

Abstract read
In one paragraph

Article in Global health action, 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. Review
  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

2 authors.

Jih-Shong WuCollege of General Education, Chihlee University of Technology, New Taipei City, Taiwan.ORCID 0000-0001-5136-2739
Kuo-Kuang HuangDepartment of International Trade, Chihlee University of Technology, New Taipei City, Taiwan.ORCID 0000-0003-2998-2426

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe COVID-19 pandemic has revealed clear deficiencies in global public health policies and healthcare systems when confronted with the emergence of a novel and deadly infectious disease.

objectivesWith 4 years elapsed since the onset of the pandemic, ample data now exist to analyse the associations between the implementation of diverse public health policies, sociodemographic factors and COVID-19 mortality rates.

methodsThis study utilised the dataset compiled by 'Our World in Data' spanning the period of the COVID-19 pandemic from 2020 to 2022. Stochastic frontier analysis was employed to assess the influencing factors and their relationship with mortality rates resulting from COVID-19 infections across 156 countries or regions.

resultsThis study yielded several key findings: (1) There remains a 33% margin for improvement in the global mortality rate concerning the COVID-19 pandemic; (2) During the initial stage of the pandemic, when an effective vaccine was not yet available, implementing public health control policies could reduce both the infection and mortality rates; (3) Areas characterised by higher population densities, a greater proportion of individuals aged 65 and over, and elevated prevalence rates of diabetes demonstrated higher mortality rates; and (4) Increasing vaccination coverage emerged as an effective strategy for reducing mortality rates.

conclusionsAs our understanding of the COVID-19 virus improves, global economies and social interactions have gradually returned to normality. It is anticipated that the findings of this study can serve as a valuable reference in combating potential future pandemics caused by unknown viruses.

Indexed as

COVID-19SARS-CoV-2AgedGlobal HealthHealth PolicyHumansMortalityPandemicsSociodemographic FactorsVaccination CoverageCOVID-19inefficiencyinfectionmortalitystochastic Frontier analysis

Identifiers

PMID39530400
PMCPMC11559029

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.