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Objective <p>Syphilis remains a major public health issue worldwide. Spatiotemporal analysis can offer insight to the geographic variation of the syphilis epidemic and contribute to the development of targeted prevention and control programs in public health practice. This study aimed to investigate the spatial and temporal distribution of syphilis incidence and the sociodemographic factors influencing it in mainland China from 2004—2020.</p> Methods <p>Syphilis incidence data from 2004–2020 were extracted from the China Public Health Science Data Center, and socio-demographic data from 2004–2020 were extracted from the official website of the National Bureau of Statistics. Spatial autocorrelation analysis, retrospective time scanning, and panel data regression analysis were used to investigate the spatial and temporal distribution of syphilis incidence and the sociodemographic factors influencing it.</p> Results <p>The global spatial autocorrelation showed that there was spatial aggregation in the distribution of syphilis incidence in mainland China from 2004 to 2010 (Moran’s I = 0.1561 ~ 0.3782 <i>P</i> &lt; 0.05), and there was no spatial aggregation in the distribution of syphilis incidence in mainland China from 2011 to 2020 (Moran’s I = -0.0145 ~ 0.1511, <i>P</i> &gt; 0.05). One most likely and four secondary clustering areas of syphilis rates were identified. The unmarried rate was negatively correlated with the incidence of syphilis, while gross domestic product per capita, consumption expenditure per capita, the number of medical institutions, the divorce rate, passenger turnover, and population density were positively correlated with the incidence of syphilis.</p> Conclusion <p>The spatiotemporal distribution of syphilis incidence is heterogeneous and influenced by multiple sociodemographic variables. A spatiotemporal scanning statistics and spatial panel regression are effective tools for identifying clusters and analyzing factors that determine syphilis incidence. The findings can be used to develop targeted prevention and control programs in public health.</p>

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Spatiotemporal distribution of syphilis in Mainland China during the 17 years from 2004 to 2020

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月25日

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  • Ying Zheng,
  • Shu-Hao Fan,
  • Hui-Lin Zhang,
  • Jia-Wen Xie,
  • Yin-Feng Guo,
  • Xiao-Lu Yu,
  • Yan Zhang,
  • Li-Rong Lin

摘要

Objective

Syphilis remains a major public health issue worldwide. Spatiotemporal analysis can offer insight to the geographic variation of the syphilis epidemic and contribute to the development of targeted prevention and control programs in public health practice. This study aimed to investigate the spatial and temporal distribution of syphilis incidence and the sociodemographic factors influencing it in mainland China from 2004—2020.

Methods

Syphilis incidence data from 2004–2020 were extracted from the China Public Health Science Data Center, and socio-demographic data from 2004–2020 were extracted from the official website of the National Bureau of Statistics. Spatial autocorrelation analysis, retrospective time scanning, and panel data regression analysis were used to investigate the spatial and temporal distribution of syphilis incidence and the sociodemographic factors influencing it.

Results

The global spatial autocorrelation showed that there was spatial aggregation in the distribution of syphilis incidence in mainland China from 2004 to 2010 (Moran’s I = 0.1561 ~ 0.3782 P < 0.05), and there was no spatial aggregation in the distribution of syphilis incidence in mainland China from 2011 to 2020 (Moran’s I = -0.0145 ~ 0.1511, P > 0.05). One most likely and four secondary clustering areas of syphilis rates were identified. The unmarried rate was negatively correlated with the incidence of syphilis, while gross domestic product per capita, consumption expenditure per capita, the number of medical institutions, the divorce rate, passenger turnover, and population density were positively correlated with the incidence of syphilis.

Conclusion

The spatiotemporal distribution of syphilis incidence is heterogeneous and influenced by multiple sociodemographic variables. A spatiotemporal scanning statistics and spatial panel regression are effective tools for identifying clusters and analyzing factors that determine syphilis incidence. The findings can be used to develop targeted prevention and control programs in public health.