Evidence map›Paper›PMID 37340788›Full record

ArticleHuman vaccines & immunotherapeutics2023

How can COVID-19 vaccines benefit people? A study based on the theory of the commons.

Yiqing Su, Yanyan Li, Shifei Zhang, Xiaohan Chen

Open access · goldAbstract read
In one paragraph

Article in Human vaccines & immunotherapeutics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 41% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

4 authors at 1 institution in 1 country.

Yiqing SuSchool of Public Policy and Management, Guangxi University, Nanning, China.
Yanyan LiSchool of Public Policy and Management, Guangxi University, Nanning, China.
Shifei ZhangSchool of Public Policy and Management, Guangxi University, Nanning, China.
Xiaohan Chen
Guangxi University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 vaccination is a fundamental step toward controlling the COVID-19 pandemic and defusing the public health crisis it has caused. Existing studies have demonstrated that equitable distribution of COVID-19 vaccines can only be achieved if these vaccines are treated as public goods. The question remains how to transform COVID-19 vaccines into public goods. In this paper, based on the theory of commons governance, the theoretical mechanism is analyzed to realize the adequate distribution of COVID-19 vaccines. Furthermore, feasible methods on how COVID-19 vaccines can benefit the people through the successful popularization of these vaccines in China are summarized. The results show that to ensure adequate supply of COVID-19 vaccines, government intervention is required because the government can expand the supply of the vaccine by balancing individual benefits for producing enterprises and the overall benefits for society. The government can also guarantee the right of every member in society to receive COVID-19 vaccines, thus enabling these vaccines to benefit the whole nation. By analyzing how COVID-19 vaccines benefit the people, this paper further verifies that national intervention plays an essential role in the supply and distribution of COVID-19 vaccines in both developed and developing countries. It may further mean that state intervention can play an essential role in continuing to respond to major public health events in the possible future.

Indexed as

COVID-19VaccinesChinaCOVID-19 VaccinesHumansPandemicsPublic HealthVaccinationCOVID-19 VaccinesVaccinesChinacommon pool resourcesCOVID-19 vaccinesdeveloping countries

Identifiers

PMID37340788
PMCPMC10332236
OpenAlexW4381469679

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.