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Cluster of Human Infections with Avian Influenza A (H7N9) Cases: A Temporal and Spatial Analysis

Author

Listed:
  • Yi Zhang

    (Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China
    These authors contributed equally to this work.)

  • Zhixiong Shen

    (Department of Earth and Environmental Sciences, Tulane University, New Orleans, LA 70118, USA
    Department of Marine Science, Coastal Carolina University, 301 Allied Drive, Conway, SC 29526, USA
    These authors contributed equally to this work.)

  • Chunna Ma

    (Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China
    These authors contributed equally to this work.)

  • Chengsheng Jiang

    (Maryland Institute for Applied Environmental Health, School of Public Health in University of Maryland, College Park, MD 20742, USA
    These authors contributed equally to this work.)

  • Cindy Feng

    (School of Public Health & The Western College of Veterinary Medicine, University of Saskatchewan, Saskatoon, SK S7N 5E5, Canada)

  • Nivedita Shankar

    (Saw Swee Hock School of Public Health, National University of Singapore, Singapore)

  • Peng Yang

    (Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China)

  • Wenjie Sun

    (School of Food Science, Guangdong Pharmaceutical University, Zhongshan 528458, China
    Department of Global Environmental Health Sciences, School of Public Health and Tropical Medicine, Tulane University, New Orleans, LA 70112, USA)

  • Quanyi Wang

    (Beijing Center for Disease Prevention and Control (CDC), Beijing 100013, China)

Abstract

Objectives : This study aims to describe the spatial and temporal characteristics of human infections with H7N9 virus in China using data from February 2013 to March 2014 from the websites of every province’s Population and Family Planning Commission. Methods : A human infection with H7N9 virus dataset was summarized by county to analyze its spatial clustering, and by date of illness onset to analyze its space-time clustering using the ESRI ® Geographic Information System (GIS) software ArcMap™ 10.1 and SatScan. Results : Based on active surveillance data, the distribution map of H7N9 cases shows that compared to the rest of China, the areas from near the Yangtze River delta (YRD) to farther south around the Pearl River delta (PRD) had the highest densities of H7N9 cases. The case data shows a strong space-time clustering in the areas on and near the YRD from 26 March to 18 April 2013 and a weak space-time clustering only in the areas on and near the PRD between 3 and 4 February 2014. However, for the rest of the study period, H7N9 cases were spatial-temporally randomly distributed. Conclusions : Our results suggested that the spatial-temporal clustering of H7N9 in China between 2013 and 2014 is fundamentally different.

Suggested Citation

  • Yi Zhang & Zhixiong Shen & Chunna Ma & Chengsheng Jiang & Cindy Feng & Nivedita Shankar & Peng Yang & Wenjie Sun & Quanyi Wang, 2015. "Cluster of Human Infections with Avian Influenza A (H7N9) Cases: A Temporal and Spatial Analysis," IJERPH, MDPI, vol. 12(1), pages 1-13, January.
    • Handle: RePEc:gam:jijerp:v:12:y:2015:i:1:p:816-828:d:44762
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    Citations

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    Cited by:

    1. Zu-Qun Wu & Yi Zhang & Na Zhao & Zhao Yu & Hao Pan & Ta-Chien Chan & Zhi-Ruo Zhang & She-Lan Liu, 2017. "Comparative Epidemiology of Human Fatal Infections with Novel, High (H5N6 and H5N1) and Low (H7N9 and H9N2) Pathogenicity Avian Influenza A Viruses," IJERPH, MDPI, vol. 14(3), pages 1-20, March.
    2. Zeng Li & Jingying Fu & Gang Lin & Dong Jiang, 2019. "Spatiotemporal Variation and Hotspot Detection of the Avian Influenza A(H7N9) Virus in China, 2013–2017," IJERPH, MDPI, vol. 16(4), pages 1-13, February.
    3. Wen Dong & Kun Yang & Quan-Li Xu & Yu-Lian Yang, 2015. "A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014," IJERPH, MDPI, vol. 12(12), pages 1-18, December.
    4. Zhenyi Wang & Wen Dong & Kun Yang, 2022. "Spatiotemporal Analysis and Risk Assessment Model Research of Diabetes among People over 45 Years Old in China," IJERPH, MDPI, vol. 19(16), pages 1-26, August.

    More about this item

    Keywords

    H7N9; influenza A; GIS; SatScan; space-time; clustering;
    All these keywords.

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