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Spatial Heterogeneity and Its Influencing Factors of Syphilis in Ningxia, Northwest China, from 2004 to 2017: A Spatial Analysis

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  • Ruonan Wang

    (Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750001, China
    Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, 1160 Shengli Street, Xingqing District, Yinchuan 750001, China
    These authors contribute to this study equally, and thus they are joint first authors.)

  • Xiaolong Li

    (Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750001, China
    Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, 1160 Shengli Street, Xingqing District, Yinchuan 750001, China
    These authors contribute to this study equally, and thus they are joint first authors.)

  • Zengyun Hu

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Wenjun Jing

    (School of Statistics, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Yu Zhao

    (Department of Epidemiology and Health Statistics, School of Public Health and Management, Ningxia Medical University, Yinchuan 750001, China
    Ningxia Key Laboratory of Environmental Factors and Chronic Disease Control, 1160 Shengli Street, Xingqing District, Yinchuan 750001, China)

Abstract

Syphilis remains a growing and resurging infectious disease in China. However, exploring the influence of environmental factors on the spatiotemporal distribution of syphilis remains under explore. This study aims to analyze the spatiotemporal distribution characteristics of syphilis in Ningxia, Northwest China, and its potential environmental influencing factors. Based on the standardized incidence ratio of syphilis for 22 administrative areas in Ningxia from 2004 to 2017, spatiotemporal autocorrelation and scan analyses were employed to analyze the spatial and temporal distribution characteristics of syphilis incidence, while a fixed-effect spatial panel regression model identified the potential factors affecting syphilis incidence. Syphilis incidence increased from 3.78/100,000 in 2004 to 54.69/100,000 in 2017 with significant spatial clustering in 2007 and 2009–2013. The “high–high” and “low–low” clusters were mainly distributed in northern and southern Ningxia, respectively. The spatial error panel model demonstrated that the syphilis incidence may be positively correlated with the per capita GDP and tertiary industry GDP and negatively correlated with the number of health facilities and healthcare personnel. Sex ratio and meteorological factors were not significantly associated with syphilis incidence. These results show that the syphilis incidence in Ningxia is still increasing and has significant spatial distribution differences and clustering. Socio-economic and health-resource factors could affect the incidence; therefore, strengthening syphilis surveillance of migrants in the economically developed region and allocating health resources to economically underdeveloped areas may effectively help prevent and control syphilis outbreaks in high-risk cluster areas of Ningxia.

Suggested Citation

  • Ruonan Wang & Xiaolong Li & Zengyun Hu & Wenjun Jing & Yu Zhao, 2022. "Spatial Heterogeneity and Its Influencing Factors of Syphilis in Ningxia, Northwest China, from 2004 to 2017: A Spatial Analysis," IJERPH, MDPI, vol. 19(17), pages 1-14, August.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:17:p:10541-:d:896208
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    References listed on IDEAS

    as
    1. Shangqing Tang & Lishuo Shi & Wen Chen & Peizhen Zhao & Heping Zheng & Bin Yang & Cheng Wang & Li Ling, 2021. "Spatiotemporal distribution and sociodemographic and socioeconomic factors associated with primary and secondary syphilis in Guangdong, China, 2005–2017," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 15(8), pages 1-14, August.
    2. Kurubaran Ganasegeran & Mohd Fadzly Amar Jamil & Maheshwara Rao Appannan & Alan Swee Hock Ch’ng & Irene Looi & Kalaiarasu M. Peariasamy, 2022. "Spatial Dynamics and Multiscale Regression Modelling of Population Level Indicators for COVID-19 Spread in Malaysia," IJERPH, MDPI, vol. 19(4), pages 1-13, February.
    3. Caique J N Ribeiro & Allan D dos Santos & Shirley V M A Lima & Eliete R da Silva & Bianca V S Ribeiro & Andrezza M Duque & Marcus V S Peixoto & Priscila L dos Santos & Iris M de Oliveira & Michael W L, 2021. "Space-time risk cluster of visceral leishmaniasis in Brazilian endemic region with high social vulnerability: An ecological time series study," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 15(1), pages 1-20, January.
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