Evidence map›Paper›PMID 39924641›Full record

ArticleHuman vaccines & immunotherapeutics2025

Pertussis epidemiological surveillance and immunization history in children under five years in a megacity in China from 2019 to 2023.

Yang Liu, Jing Chen, Ning Yao, Xiaoxiao Hu, Nian Yu, Qing Wang, Jiawei Xu

Abstract read
In one paragraph

Article in Human vaccines & immunotherapeutics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. 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.

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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

7 authors.

Yang LiuEPI Department, Chongqing Center for Disease Control and Prevention, Chongqing, China.
Jing ChenEPI Department, Liangping District Center for Disease Control and Prevention, Chongqing, China.
Ning YaoEPI Department, Chongqing Center for Disease Control and Prevention, Chongqing, China.
Xiaoxiao HuEPI Department, Liangping District Center for Disease Control and Prevention, Chongqing, China.
Nian YuEPI Department, Liangping District Center for Disease Control and Prevention, Chongqing, China.
Qing WangEPI Department, Chongqing Center for Disease Control and Prevention, Chongqing, China.
Jiawei XuEPI Department, Chongqing Center for Disease Control and Prevention, Chongqing, China.ORCID 0000-0003-1492-7571

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To analyze the epidemiological characteristics and influencing factors of pertussis in children under five years in Chongqing from 2019 to 2023, providing scientific evidence for further prevention and control. The epidemiological characteristics of pertussis cases in children under five years and vaccination history with pertussis-containing vaccines were described, and the influencing factors and cumulative risk of disease onset after vaccination were analyzed using the Cox proportional hazards regression model. From 2019 to 2023, a total of 4,135 pertussis cases were reported in children under five years in Chongqing, with cases occurring predominantly between April and August. Infants under 1 year accounted for the highest proportion of cases at 66.82% (2,763/4,135); the annual reported incidence was higher in boys (141.26/100,000) than in girls (122.09/100,000). Over half of the cases, 59.78% (2,472/4,135) had received at least one dose of a pertussis-containing vaccine, and there were significant differences in vaccination history among different age groups (χ

Indexed as

Epidemiological MonitoringPertussis VaccineVaccinationWhooping CoughChild, PreschoolChinaFemaleHumansIncidenceInfantInfant, NewbornMaleProportional Hazards ModelsPertussis VaccinechildrenmorbidityPertussisvaccines

Identifiers

PMID39924641
PMCPMC11812399

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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.