Evidence map›Paper›PMID 39807479›Full record

ArticleVaccine: X2025

A discrete choice experiment on Chinese parents' preferences of vaccine schedules against six childhood infectious diseases.

Aodi Huang, Lin Tang, Lifang Huang, Jun Li, Xue Zhang, Jiajie Liu, Yang Zhou, Bingling Zhang, Lei Wang, Qian Zhang and 8 more

Abstract read
In one paragraph

Article in Vaccine: X, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

18 authors.

Aodi HuangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Lin TangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Lifang HuangFujian Provincial Center for Disease Control and Prevention, Fuzhou, China.
Jun LiHenan Provincial Center for Disease Control and Prevention, Zhengzhou, China.
Xue ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Jiajie LiuSichuan Provincial Center for Disease Control and Prevention, Chengdu, China.
Yang ZhouZhejiang Provincial Center for Disease Control and Prevention, Hangzhou, China.
Bingling ZhangGansu Provincial Center for Disease Control and Prevention, Lanzhou, China.
Lei WangHubei Provincial Center for Disease Control and Prevention, Wuhan, China.
Qian ZhangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Xia XuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Zemei ZhouNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Yu WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Xiaoqi WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Qianqian LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Siyu LiuNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Zundong YinNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.
Fuzhen WangNational Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Immunization Program, Chinese Center for Disease Control and Prevention, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: China's Expanded Program on Immunization (EPI) provides vaccinations against 12 vaccine preventable diseases (VPDs) at no cost to families. For some VPDs, parents may opt to substitute equivalent non-program vaccines, including combination vaccines, for EPI vaccines; substitute vaccines must be paid for by the family. Although parents have several choices for vaccinating their children, their preferences for vaccines and immunization schedules have not been systematically evaluated. We used a discrete choice experiment to evaluate four attributes of vaccines for routine immunization: number of injections, risk of mild side-effects, out-of-pocket cost, and location of manufacturer (domestic or imported). Methods: In a questionnaire-based survey conducted in vaccination clinics, guardians were asked to select their preferred vaccination schedule from five options in ten choice sets with the four attributes. We used a mixed logit model to determine parental preferences for vaccination schedules, relative importance of attributes, and predict the likelihood of successful vaccination under different scenarios. Results: A total of 581 parents from seven provinces and cities in China participated in the survey, and 488 respondents had internally consistent responses and were included in the analysis. The number of injections in the schedule was the most important attribute for predicting uptake, followed by risk of mild side-effects. Preferences varied by region and parental role. Predicted uptake in the preferred vaccination scenario relative to base-case schedule uptake was a 99.55 % increase. Conclusions: Number of injections and risk of mild side-effects were the two most important attributes of the routine immunization schedule. Results from this study can help optimize the immunization schedule in China to improve coverage of childhood vaccines.

Indexed as

CoverageDiscrete choice experimentParental preferenceVaccination program

Identifiers

PMID39807479
PMCPMC11728966

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LicenceCC BY-NC-ND
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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.