Evidence map›Paper›PMID 40170694›Full record

ArticleInternational journal of public health2025

Spatio-Temporal Distribution Characteristics of Syphilis: on the Scale of Towns (Streets) in Nantong City, Jiangsu Province, China.

Zhihai Zhang, Xiaoyan Hou, Maomao Liu, Maoxuan Wu, Ping Zhu, Xiaoyi Zhou

Abstract read
In one paragraph

Article in International journal of public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 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

6 authors.

Zhihai Zhang *Department of STD and AIDS Control and Prevention, Nantong Center for Disease Control and Prevention, Nantong, Jiangsu, China.
Xiaoyan Hou *Department of STD and AIDS Control and Prevention, Nantong Center for Disease Control and Prevention, Nantong, Jiangsu, China.
Maomao LiuDepartment of STD and AIDS Control and Prevention, Nantong Center for Disease Control and Prevention, Nantong, Jiangsu, China.
Maoxuan WuDepartment of STD and AIDS Control and Prevention, Nantong Center for Disease Control and Prevention, Nantong, Jiangsu, China.
Ping ZhuDepartment of STD and AIDS Control and Prevention, Nantong Center for Disease Control and Prevention, Nantong, Jiangsu, China.
Xiaoyi ZhouDepartment of STD and AIDS Control and Prevention, Nantong Center for Disease Control and Prevention, Nantong, Jiangsu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objectives: To investigate the spatio-temporal distribution characteristics and changing trends of syphilis in Nantong city. Methods: Joinpoint regression model, spatial autocorrelation and SaTScan spatio-temporal scanning were used to analyze the trend of syphilis reported incidence and spatio-temporal distribution characteristics in Nantong City. Results: From 2013 to 2022, the reported incidence of syphilis in Nantong City increased at an average annual rate of 6.60%, of which the increase rate of latent syphilis was 13.45%. The high-high clustering areas were mainly distributed in 15 streets of Chongchuan District and all streets of Nantong Development Zone. SaTScan spatio-temporal scanning detected a total of two clustering areas, all from 2021 to 2022. The first cluster includes 24 streets with a radius of 16.27 km, and the second cluster includes 18 streets within a radius of 34.90 km. Conclusion: The reported incidence of syphilis in Nantong City showed an increasing trend, mainly manifested as an increase in latent syphilis, and the reported incidence of syphilis in various towns (streets) showed obvious spatial clustering, and attention should be paid to key areas and targeted interventions should be formulated.

Indexed as

SyphilisChinaCitiesCluster AnalysisHumansIncidenceMaleSpatio-Temporal Analysisclusterepidemiologyspatial autocorrelationspatio-temporal scanningsyphilis

Identifiers

PMID40170694
PMCPMC11957987

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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.