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Analysis of the spatio-temporal pattern and evolutionary trends of syphilis at township level in Xining City, Qinghai Province, China from 2008 to 2024
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  • Published: 25 May 2026

Analysis of the spatio-temporal pattern and evolutionary trends of syphilis at township level in Xining City, Qinghai Province, China from 2008 to 2024

  • Yitao Ren1,
  • Yongkai Shi2,
  • Jinxiong Lin3,4,
  • Ying Zhao2 &
  • …
  • Wei Li2 

Scientific Reports (2026) Cite this article

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Subjects

  • Diseases
  • Ecology
  • Health care
  • Medical research

Abstract

From 2008 to 2024, a total of 15,465 syphilis cases were reported in Xining City, Qinghai Province, yielding an average annual incidence of 4.44 per 10,000 population and a male-to-female ratio of 1.14. Temporal analysis revealed a steadily increasing trend over the 17‑year period, with a consistent seasonal peak in March. Spatial autocorrelation analysis showed significant clustering (global Moran’s I = 0.217, P < 0.05), with high‑high clusters concentrated in eastern urban districts and low‑low clusters predominantly in northern areas. The standard deviational ellipse indicated a dominant southeast–northwest directional trend. Spatio‑temporal scan statistics identified four statistically significant high‑incidence clusters, and Kriging interpolation produced a smoothed surface suggesting elevated transmission risk in the eastern and southern townships. These findings demonstrate that syphilis incidence in Xining increased steadily and expanded geographically from urban centers to peripheral areas over the study period, with pronounced spatial and spatio‑temporal heterogeneity. As a hypothesis‑generating descriptive spatial analysis, this study supports enhanced dynamic surveillance, targeted interventions in high‑risk regions, and locally adapted public health measures to strengthen syphilis control.

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Acknowledgements

The authors gratefully acknowledge the invaluable support from Xining Centre for Disease Control and Prevention in facilitating this research. We extend profound gratitude to all the public health professionals whose unwavering dedication in challenging environments exemplifies extraordinary commitment to public health.

Funding

This work was supported by the leading academic team established by the Xining Center for Disease Control and Prevention (Document No. Ningjikyeye [2025] 21).

Author information

Authors and Affiliations

  1. Department of Public Health, Qinghai Unversity Medical College, Xining, 810008, China

    Yitao Ren

  2. Xining Centre for Disease Control and Prevention, Lekang Road, Chengbei District, Xining, 810000, Qinghai, China

    Yongkai Shi, Ying Zhao & Wei Li

  3. Dermatology Hospital, Southern Medical University, Guangzhou, 510091, China

    Jinxiong Lin

  4. School of Health Management, Southern Medical University, Guangzhou, 510515, China

    Jinxiong Lin

Authors
  1. Yitao Ren
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  2. Yongkai Shi
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  3. Jinxiong Lin
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  4. Ying Zhao
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  5. Wei Li
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Corresponding author

Correspondence to Wei Li.

Ethics declarations

Competing interests

The authors declare no competing interests.

Ethics approval and consent to participate

This study was approved by the Ethics Review Committee of the Xining Center for Disease Control and Prevention (Approval No. qhxncdcllsc—2025020) and followed relevant guidelines. Patient data, summarized at the city level, were retrospective and involved low-risk studies. All personal information involved in this article was conducted under the supervision of the relevant researchers at the Xining Municipal Center for Disease Control and Prevention, and only secondary aggregated data were used in the analysis, which did not involve participants’ names, identifying information, telephone numbers, or residential addresses; therefore, the Ethics Review Committee of the Xining Center for Disease Control and Prevention waived written informed consent.

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Cite this article

Ren, Y., Shi, Y., Lin, J. et al. Analysis of the spatio-temporal pattern and evolutionary trends of syphilis at township level in Xining City, Qinghai Province, China from 2008 to 2024. Sci Rep (2026). https://doi.org/10.1038/s41598-026-53877-7

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  • Received: 28 November 2025

  • Accepted: 14 May 2026

  • Published: 25 May 2026

  • DOI: https://doi.org/10.1038/s41598-026-53877-7

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Keywords

  • Syphilis
  • Epidemiological characteristics
  • Spatial autocorrelation
  • Spatio-temporal scanning
  • Kriging interpolation
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