ArticleBMC public health2026
Spatiotemporal distribution of syphilis in Mainland China during the 17 years from 2004 to 2020.
Article in BMC public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
objectiveSyphilis 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.
methodsSyphilis 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.
resultsThe 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.
conclusionThe 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.
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