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Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005–2014

Author

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  • Gehendra Mahara

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China
    These authors contributed equally to this work.)

  • Chao Wang

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China
    These authors contributed equally to this work.)

  • Da Huo

    (Institute for Infectious Disease & Endemic Disease Control, Beijing Center for Disease Prevention & Control (CDC), Beijing Center for Preventive Medical Research, Beijing 100069, China)

  • Qin Xu

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Fangfang Huang

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Lixin Tao

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Jin Guo

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Kai Cao

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Liu Long

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Jagadish K. Chhetri

    (Department of Geriatrics, XuanWu Hospital of Capital Medical University, Beijing 100069, China)

  • Qi Gao

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

  • Wei Wang

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China
    Systems and Intervention Research Centre for Health, School of Medical Sciences, Edith Cowan University, Perth 6027, Australia)

  • Quanyi Wang

    (Institute for Infectious Disease & Endemic Disease Control, Beijing Center for Disease Prevention & Control (CDC), Beijing Center for Preventive Medical Research, Beijing 100069, China)

  • Xiuhua Guo

    (Department of Epidemiology and Biostatistics, School of Public Health, Capital Medical University, Beijing 100069, China
    Beijing Municipal Key Laboratory of Clinical Epidemiology, Beijing 100069, China)

Abstract

Objective : To probe the spatiotemporal patterns of the incidence of scarlet fever in Beijing, China, from 2005 to 2014. Methods : A spatiotemporal analysis was conducted at the district/county level in the Beijing region based on the reported cases of scarlet fever during the study period. Moran’s autocorrelation coefficient was used to examine the spatial autocorrelation of scarlet fever, whereas the Getis-Ord Gi* statistic was used to determine the hotspot incidence of scarlet fever. Likewise, the space-time scan statistic was used to detect the space-time clusters, including the relative risk of scarlet fever incidence across all settings. Results : A total of 26,860 scarlet fever cases were reported in Beijing during the study period (2005–2014). The average annual incidence of scarlet fever was 14.25 per 100,000 population (range, 6.76 to 32.03 per 100,000). The incidence among males was higher than that among females, and more than two-thirds of scarlet fever cases (83.8%) were among children 3–8 years old. The seasonal incidence peaks occurred from March to July. A higher relative risk area was mainly in the city and urban districts of Beijing. The most likely space-time clusters and secondary clusters were detected to be diversely distributed in every study year. Conclusions : The spatiotemporal patterns of scarlet fever were relatively unsteady in Beijing from 2005 to 2014. The at-risk population was mainly scattered in urban settings and dense districts with high population, indicating a positive relationship between population density and increased risk of scarlet fever exposure. Children under 15 years of age were the most susceptible to scarlet fever.

Suggested Citation

  • Gehendra Mahara & Chao Wang & Da Huo & Qin Xu & Fangfang Huang & Lixin Tao & Jin Guo & Kai Cao & Liu Long & Jagadish K. Chhetri & Qi Gao & Wei Wang & Quanyi Wang & Xiuhua Guo, 2016. "Spatiotemporal Pattern Analysis of Scarlet Fever Incidence in Beijing, China, 2005–2014," IJERPH, MDPI, vol. 13(1), pages 1-17, January.
  • Handle: RePEc:gam:jijerp:v:13:y:2016:i:1:p:131-:d:62253
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    References listed on IDEAS

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    2. Eyler, J.M., 1986. "The epidemiology of milk-borne scarlet fever: The case of Edwardian Brighton," American Journal of Public Health, American Public Health Association, vol. 76(5), pages 573-584.
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