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Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea

Author

Listed:
  • Jaewon Kwak

    (Forecast and Control Division, Nakdong River Flood Control Office, Busan 604-851, Korea)

  • Soojun Kim

    (Columbia Water Center, Columbia University, New York, NY 10027, USA)

  • Gilho Kim

    (Department of Hydro Science and Engineering, Korea Institute of Civil Engineering and Building Technology, Goyang-si, Gyeonggi-do 411-712, Korea)

  • Vijay P. Singh

    (Department of Biological & Agricultural Engineering and Zachry Dept. of Civil Engineering, Texas A & M University, TX 77843, USA)

  • Seungjin Hong

    (Department of Civil Engineering, Inha University, Incheon 402-751, Korea)

  • Hung Soo Kim

    (Department of Civil Engineering, Inha University, Incheon 402-751, Korea)

Abstract

Since its recurrence in 1986, scrub typhus has been occurring annually and it is considered as one of the most prevalent diseases in Korea. Scrub typhus is a 3rd grade nationally notifiable disease that has greatly increased in Korea since 2000. The objective of this study is to construct a disease incidence model for prediction and quantification of the incidences of scrub typhus. Using data from 2001 to 2010, the incidence Artificial Neural Network (ANN) model, which considers the time-lag between scrub typhus and minimum temperature, precipitation and average wind speed based on the Granger causality and spectral analysis, is constructed and tested for 2011 to 2012. Results show reliable simulation of scrub typhus incidences with selected predictors, and indicate that the seasonality in meteorological data should be considered.

Suggested Citation

  • Jaewon Kwak & Soojun Kim & Gilho Kim & Vijay P. Singh & Seungjin Hong & Hung Soo Kim, 2015. "Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea," IJERPH, MDPI, vol. 12(7), pages 1-20, June.
    • Handle: RePEc:gam:jijerp:v:12:y:2015:i:7:p:7254-7273:d:51811
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    References listed on IDEAS

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    1. Li-Ping Yang & Si-Yuan Liang & Xian-Jun Wang & Xiu-Jun Li & Yan-Ling Wu & Wei Ma, 2015. "Burden of Disease Measured by Disability-Adjusted Life Years and a Disease Forecasting Time Series Model of Scrub Typhus in Laiwu, China," PLOS Neglected Tropical Diseases, Public Library of Science, vol. 9(1), pages 1-9, January.
    2. Granger, C W J, 1969. "Investigating Causal Relations by Econometric Models and Cross-Spectral Methods," Econometrica, Econometric Society, vol. 37(3), pages 424-438, July.
    3. Hyndman, Rob J. & Khandakar, Yeasmin, 2008. "Automatic Time Series Forecasting: The forecast Package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i03).
    4. Jonathan A. Patz & Diarmid Campbell-Lendrum & Tracey Holloway & Jonathan A. Foley, 2005. "Impact of regional climate change on human health," Nature, Nature, vol. 438(7066), pages 310-317, November.
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    Cited by:

    1. Kyung-Duk Min & Ju-Yeun Lee & Yeonghwa So & Sung-il Cho, 2019. "Deforestation Increases the Risk of Scrub Typhus in Korea," IJERPH, MDPI, vol. 16(9), pages 1-10, April.

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