Evidence map›Paper›PMID 42106351›Full record

ArticleNPJ vaccines2026

Global patterns of pertussis incidence and vaccination strategies: implications of divergent surveillance data.

Kangguo Li, Yulun Xie, Jiadong Wu, Yunzhi Zenghuang, Tao Chen, Juan Li, Sha Chen, Ziyan Liu, Honglian Liu, Jia Rui and 5 more

Abstract read
In one paragraph

Article in NPJ vaccines, 2026. 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

15 authors.

Kangguo LiState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Yulun XieState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Jiadong WuState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Yunzhi ZenghuangState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Tao ChenState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Juan LiSchool of Nursing, Shaoyang University, Shaoyang, China.
Sha ChenState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Ziyan LiuHunan Provincial Center for Disease Control and Prevention, Changsha, China.
Honglian LiuXiamen Center for Disease Control and Prevention, Xiamen, China.
Jia RuiState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Zeyu ZhaoState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China.
Mingzhai WangXiamen Center for Disease Control and Prevention, Xiamen, China. 32639937@qq.com.
Kaiwei LuoHunan Provincial Center for Disease Control and Prevention, Changsha, China. 87616498@qq.com.
Yanhua SuState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China. suyanhua813@xmu.edu.cn.
Tianmu ChenState Key Laboratory of Vaccines for Infectious Diseases, Xiang An Biomedicine Laboratory, National Innovation Platform for Industry-Education Integration in Vaccine Research, School of Public Health, Xiamen University, Xiamen, China. chentianmu@xmu.edu.cn.

Funding

National Key Research and Development Program of China 2024YFC2311404National Natural Science Foundation of China 825B2104Scientific Research Project of the Hunan Provincial Health Commission 20254440Self-supporting Program of Guangzhou Laboratory GZNL2024A01004
6 · The paper itself

Abstract

Pertussis remains a global threat for infants, and recent increases in notifications have renewed interest in optimising vaccination strategies and improving vaccines. At the biological level, the rationale for maternal pertussis immunization extends beyond passive antibody transfer alone and may also involve broader maternal-infant immune interactions; however, at the population level these mechanisms are operationalized through policy adoption, timing recommendations, and coverage. We compared incidence constructs from WHO routine notifications and Global Burden of Disease (GBD) modelled estimates and assessed how associations with vaccination policy indicators change across outcome definitions. Trends were characterised with Joinpoint regression; policy associations were estimated using Bayesian hierarchical models fitted separately to each dataset with Universal Health Coverage stratified random intercepts. Incidence levels and trends differed markedly between WHO and GBD. Unadjusted analyses showed heterogeneous, sometimes opposing, associations for maternal immunization and schedule timing. After adjustment, most schedule parameters were small and imprecise, whereas DTP3 coverage remained strongly inversely associated with incidence in GBD but not in WHO. Surveillance and modelled estimates should not be interpreted interchangeably; harmonized constructs and routine implementation and ascertainment metadata are needed for robust cross-country inference.

Identifiers

PMID42106351
PMCPMC13376431

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.