Evidence map›Paper›PMID 40127943›Full record

ReviewBMJ global health2025

Financing the introduction of new vaccines to the national immunisation programme in China: challenges and options for action.

Xinyu Zhang, Shu Chen, Kun Zhu, Shenglan Tang

Erratum issuedAbstract readReview
In one paragraph

Review in BMJ global health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Review
  3. Article
  4. Article
  5. Article
  6. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Xinyu ZhangGlobal Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China.ORCID http://orcid.org/0000-0002-5979-244X
Shu ChenDuke Global Health Institute, Duke University, Durham, North Carolina, USA.ORCID http://orcid.org/0000-0002-1108-3863
Kun ZhuChinese Academy of Fiscal Sciences, Beijing, China.ORCID http://orcid.org/0000-0002-0878-9160
Shenglan TangGlobal Health Research Center, Duke Kunshan University, Kunshan, Jiangsu, China shenglan.tang@duke.edu.ORCID http://orcid.org/0000-0001-5727-078X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Ensuring adequate and sustainable financing of national immunisation programmes (NIPs) is one of the important elements to achieve the Immunisation Agenda 2030. Many middle-income countries ineligible for support from the Global Alliance for Vaccines and Immunisation have relatively slow progress in introducing new critical vaccines, due largely to financial constraints. China has not introduced any vaccines into the NIP since 2008. Its funding for the NIP, relying solely on the government budget, has been decreasing as the number of targeted children has declined. This paper presents the current situation of NIP and identifies main challenges in vaccine introduction in China: fluctuating and insufficient financing, restrictions on using health insurance funds for immunisation, high prices for non-NIP vaccines and the complicated and non-transparent decision-making mechanism to adjust NIP. There are also opportunities for introducing vaccines, such as local pilots to provide free or subsidised new vaccines and reducing domestic vaccine prices. Feasible options to optimise NIP financing in China include increasing government funding, diversifying financing channels such as using health insurance funds, improving the vaccine procurement mechanism and optimising the new vaccine introduction decision-making process.

Indexed as

Financing, GovernmentImmunization ProgramsVaccinesChinaHumansVaccinesHealth policyImmunisationPublic HealthVaccines

Identifiers

PMID40127943
PMCPMC11934360

What OpenQuestion holds

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LicenceCC BY
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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.