IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v12y2014i1p354-370d44080.html
   My bibliography  Save this article

Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies

Author

Listed:
  • Min Xu

    (State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China)

  • Chunxiang Cao

    (State Key Laboratory of Remote Sensing Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China
    These authors contributed equally to this work.)

  • Duochun Wang

    (State Key Laboratory for Infectious Disease Prevention and Control, Institute for Infectious Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
    These authors contributed equally to this work.)

  • Biao Kan

    (State Key Laboratory for Infectious Disease Prevention and Control, Institute for Infectious Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China
    These authors contributed equally to this work.)

Abstract

Satellites contribute significantly to environmental quality and public health. Environmental factors are important indicators for the prediction of disease outbreaks. This study reveals the environmental factors associated with cholera in Zhejiang, a coastal province of China, using both Remote Sensing (RS) and Geographic information System (GIS). The analysis validated the correlation between the indirect satellite measurements of sea surface temperature (SST), sea surface height (SSH) and ocean chlorophyll concentration (OCC) and the local cholera magnitude based on a ten-year monthly data from the year 1999 to 2008. Cholera magnitude has been strongly affected by the concurrent variables of SST and SSH, while OCC has a one-month time lag effect. A cholera prediction model has been established based on the sea environmental factors. The results of hot spot analysis showed the local cholera magnitude in counties significantly associated with the estuaries and rivers.

Suggested Citation

  • Min Xu & Chunxiang Cao & Duochun Wang & Biao Kan, 2014. "Identifying Environmental Risk Factors of Cholera in a Coastal Area with Geospatial Technologies," IJERPH, MDPI, vol. 12(1), pages 1-17, December.
    • Handle: RePEc:gam:jijerp:v:12:y:2014:i:1:p:354-370:d:44080
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/12/1/354/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/12/1/354/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Katia Koelle & Xavier Rodó & Mercedes Pascual & Md. Yunus & Golam Mostafa, 2005. "Refractory periods and climate forcing in cholera dynamics," Nature, Nature, vol. 436(7051), pages 696-700, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fatima Khalique & Shoab Ahmed Khan & Wasi Haider Butt & Irum Matloob, 2020. "An Integrated Approach for Spatio-Temporal Cholera Disease Hotspot Relation Mining for Public Health Management in Punjab, Pakistan," IJERPH, MDPI, vol. 17(11), pages 1-18, May.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Pearce, Joshua M. & Johnson, Sara J. & Grant, Gabriel B., 2007. "3D-mapping optimization of embodied energy of transportation," Resources, Conservation & Recycling, Elsevier, vol. 51(2), pages 435-453.
    2. Margherita Grasso & Matteo Manera & Aline Chiabai & Anil Markandya, 2012. "The Health Effects of Climate Change: A Survey of Recent Quantitative Research," IJERPH, MDPI, vol. 9(5), pages 1-25, April.
    3. Pamela P Martinez & Robert C Reiner Jr. & Benjamin A Cash & Xavier Rodó & Mohammad Shahjahan Mondal & Manojit Roy & Mohammad Yunus & A S G Faruque & Sayeeda Huq & Aaron A King & Mercedes Pascual, 2017. "Cholera forecast for Dhaka, Bangladesh, with the 2015-2016 El Niño: Lessons learned," PLOS ONE, Public Library of Science, vol. 12(3), pages 1-12, March.
    4. Adeboyejo Aina Thompson & Lirvhuwani Matamale & Shonisani Danisa Kharidza, 2012. "Impact of Climate Change on Children’s Health in Limpopo Province, South Africa," IJERPH, MDPI, vol. 9(3), pages 1-24, March.
    5. Maile T Phillips & Katharine A Owers & Bryan T Grenfell & Virginia E Pitzer, 2020. "Changes in historical typhoid transmission across 16 U.S. cities, 1889-1931: Quantifying the impact of investments in water and sewer infrastructures," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 14(3), pages 1-22, March.
    6. Chengcheng Bei & Shiping Liu & Yin Liao & Gaoliang Tian & Zichen Tian, 2021. "Predicting new cases of COVID‐19 and the application to population sustainability analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 61(3), pages 4859-4884, September.
    7. Wang, Jinliang & Wu, Wenjing & Kuniya, Toshikazu, 2023. "Global threshold analysis on a diffusive host–pathogen model with hyperinfectivity and nonlinear incidence functions," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 203(C), pages 767-802.
    8. Sara L. M. Trærup & Ramon A. Ortiz & Anil Markandya, 2011. "The Costs of Climate Change: A Study of Cholera in Tanzania," IJERPH, MDPI, vol. 8(12), pages 1-20, November.
    9. Stephen Tennenbaum & Caroline Freitag & Svetlana Roudenko, 2014. "Modeling the Influence of Environment and Intervention onCholera in Haiti," Mathematics, MDPI, vol. 2(3), pages 1-36, September.
    10. Basilua Andre Muzembo & Kei Kitahara & Anusuya Debnath & Ayumu Ohno & Keinosuke Okamoto & Shin-Ichi Miyoshi, 2022. "Cholera Outbreaks in India, 2011–2020: A Systematic Review," IJERPH, MDPI, vol. 19(9), pages 1-27, May.
    11. Rachel E. Baker & Ayesha S. Mahmud & C. Jessica E. Metcalf, 2018. "Dynamic response of airborne infections to climate change: predictions for varicella," Climatic Change, Springer, vol. 148(4), pages 547-560, June.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:12:y:2014:i:1:p:354-370:d:44080. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.