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Spatial Effect of Ecological Environmental Factors on Mumps in China during 2014–2018

Author

Listed:
  • Li Wen

    (Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
    These authors contributed equally to this work.)

  • Danling Yang

    (Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China
    These authors contributed equally to this work.)

  • Yanning Li

    (Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China)

  • Dongjia Lu

    (Guangxi Key Laboratory of AIDS Prevention and Treatment, Guangxi Universities Key Laboratory of Prevention and Control of Highly Prevalent Disease, Nanning 530021, China)

  • Haixia Su

    (Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China)

  • Mengying Tang

    (Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China)

  • Xiaokun Song

    (Department of Biostatistics, School of Public Health, Guangxi Medical University, Nanning 530021, China)

Abstract

(1) Background: although mumps vaccines have been introduced in most countries around the world in recent years, mumps outbreaks have occurred in countries with high vaccination rates. At present, China remains the focus of the global fight against mumps. This study aims to observe the epidemic characteristics and spatial clustering patterns of mumps and to investigate the potential factors affecting the disease incidence, which could provide novel ideas and avenues for future research as well as the prevention and control of mumps. (2) Methods: we used ArcGIS software to visualize the spatial distribution and variation of mumps. Spatial autocorrelation analysis was applied to detect the spatial dependence and clustering patterns of the incidence. We applied the Spatial Durbin Panel Model (SDPM) to explore the spatial associations of ecological environmental factors with mumps. (3) Results: overall, the incidence rate showed a significant upward trend from 2014 to 2018, with the highest number of cases in the 10–15-year age group and from May to June. Geographically, the high incidence clusters were concentrated in southern regions, including Hunan, Hubei, Chongqing, Guizhou, Guangdong, and Guangxi. This study also found that mumps has a positive spatial spillover effect in the study area. The average temperature and GDP of the local and adjacent areas have a significant impact on mumps. The increase in PM2.5 contributes to the rise in the incidence of mumps in this region. (4) Conclusions: these results can offer some novel ideas for policymakers and researchers. Local meteorological conditions and economic levels can extend to surrounding areas to affect the occurrence of mumps, so regional cooperation becomes particularly important. We recommend investment of public health funds in areas with a high incidence of mumps and developing economies to reduce and control the incidence of mumps.

Suggested Citation

  • Li Wen & Danling Yang & Yanning Li & Dongjia Lu & Haixia Su & Mengying Tang & Xiaokun Song, 2022. "Spatial Effect of Ecological Environmental Factors on Mumps in China during 2014–2018," IJERPH, MDPI, vol. 19(23), pages 1-16, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:23:p:15429-:d:980004
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    References listed on IDEAS

    as
    1. Yuchen Zhu & Dandan Zhang & Yuchen Hu & Chunyu Li & Yan Jia & Kaili She & Tingxuan Liu & Qing Xu & Ying Zhang & Xiujun Li, 2021. "Exploring the Relationship between Mumps and Meteorological Factors in Shandong Province, China Based on a Two-Stage Model," IJERPH, MDPI, vol. 18(19), pages 1-13, October.
    2. Ying Mao & Rongxin He & Bin Zhu & Jinlin Liu & Ning Zhang, 2020. "Notifiable Respiratory Infectious Diseases in China: A Spatial–Temporal Epidemiology Analysis," IJERPH, MDPI, vol. 17(7), pages 1-15, March.
    3. Yanchao Feng & Xiaohong Wang & Wenchao Du & Jun Liu, 2018. "Effects of Air Pollution Control on Urban Development Quality in Chinese Cities Based on Spatial Durbin Model," IJERPH, MDPI, vol. 15(12), pages 1-21, December.
    4. Xueli Wang & Caizhi Sun & Song Wang & Zhixiong Zhang & Wei Zou, 2018. "Going Green or Going Away? A Spatial Empirical Examination of the Relationship between Environmental Regulations, Biased Technological Progress, and Green Total Factor Productivity," IJERPH, MDPI, vol. 15(9), pages 1-23, September.
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