Evidence map›Paper›PMID 41694520›Full record

ArticleFrontiers in public health2026

Spatial-temporal patterns, seasonality, and age-specific trends of varicella in Hangzhou, China, 2019-2024.

Lintao Gu, Yan Liu, Xiaoping Zhang, Yuyang Xu, Xuechao Zhang, Xinren Che, Wenwen Gu, Yingying Yang, Lu Zj

Abstract read
In one paragraph

Article in Frontiers in public health, 2026. 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
–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

1 citing paper in PubMed.

  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

9 authors.

Lintao GuHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Yan LiuHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Xiaoping ZhangHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Yuyang XuHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Xuechao ZhangHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Xinren CheHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Wenwen GuHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Yingying YangHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.
Lu ZjHangzhou Center for Disease Control and Prevention (Hangzhou Health Supervision Institution), Hangzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Varicella has been subject to mandatory reporting to the China Information System for Disease Control and Prevention (CISDCP) by health agencies within 24 h of diagnosis since 2019. However, even if two-dose varicella vaccination has been recommended to be administered to children at 1 and 4 years of age in Hangzhou since 2014, emerging evidence of increasing breakthrough varicella cases in outbreaks challenges the present varicella vaccination schedule and its protective effect. We seek to identify hotspot areas and temporal trends of varicella at the township level in Hangzhou in the recent 6 years by using spatiotemporal analysis. Methodology: Varicella cases diagnosed by medical practitioners from 2019 to 2024, demographic data, and clinical data were extracted from CISDCP. Township-level population figures were estimated using a constant-share proportional allocation method based on the seventh census data in China. Global I statistics and the local index spatial autocorrelation (LISA) method were used to identify global autocorrelation and local autocorrelation, respectively. Retrospective spatial scan statistics were undertaken to explore potential spatiotemporal clusters of varicella. A harmonic regression model was used to quantify seasonality, and an age-specific trend was evaluated through the Cochrane-Armitage test. Result: A continuous decline in reported incidence of varicella in Hangzhou from 2019 to 2024 was observed, with 97.95 per 100,000 and 52.23 per 100,000 in 2019 and 2024, respectively. Seasonality of the bimodal peak was observed, with the first peak of varicella cases observed from May to July, whereas the second peak typically occurs from November to February of the following year. A pronounced reduction in varicella incidence among younger children (5-9) and a relatively slower decline in older pediatric and adolescent groups (10-19) were found. The spatial distribution pattern of varicella in Hangzhou at township levels was non-random, and hotspots tend to be more frequent in the suburbs than in downtown areas. A total of 34 significant varicella spatiotemporal clusters were identified by retrospective space-time scan statistics, the vast majority of which were located in suburban areas. Conclusion: Varicella incidence has dramatically declined over the past 6 years. The 10-19-year-old age band exhibited a slower reduction than the 5-9-year-old age-band. Moreover, the tendency for varicella clusters to appear more frequently in suburban areas reflects disparities in varicella incidence geographically. Specific surveillance and control measures should be undertaken in high-incidence regions in Hangzhou.

Indexed as

ChickenpoxSeasonsAdolescentAge FactorsChickenpox VaccineChildChild, PreschoolChinaFemaleHumansIncidenceInfantMaleRetrospective StudiesSpatio-Temporal AnalysisChickenpox Vaccineage-specific trendsharmonic regression modelseasonalityspatial analysisvaricella (chickenpox)

Identifiers

PMID41694520
PMCPMC12901367

What OpenQuestion holds

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LicenceCC BY
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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.