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Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea

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Listed:
  • Jaewon Kwak

    (Hydroclimatic Statistical Research Group, Centre Eau Terre Environnement, INRS, Québec, QC G1K 9A9, Canada)

  • Huiseong Noh

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

  • Soojun Kim

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

  • Vijay P. Singh

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

  • Seung Jin Hong

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

  • Duckgil Kim

    (Water Environment Research Department, Water Quality Assessment Research Division, National Institute of Environmental Research, Incheon 404-708, Korea)

  • Keonhaeng Lee

    (Water Resources Research Division, Water Resources and Environment Research Department, Korea Institute of Civil Engineering and Building Technology, Goyang-si, Gyeonggi-do 411-712, Korea)

  • Narae Kang

    (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 reappearance at the Military Demarcation Line in 1993, malaria has been occurring annually in Korea. Malaria is regarded as a third grade nationally notifiable disease susceptible to climate change. The objective of this study is to quantify the effect of climatic factors on the occurrence of malaria in Korea and construct a malaria occurrence model for predicting the future trend of malaria under the influence of climate change. Using data from 2001–2011, the effect of time lag between malaria occurrence and mean temperature, relative humidity and total precipitation was investigated using spectral analysis. Also, a principal component regression model was constructed, considering multicollinearity. Future climate data, generated from RCP 4.5 climate change scenario and CNCM3 climate model, was applied to the constructed regression model to simulate future malaria occurrence and analyze the trend of occurrence. Results show an increase in the occurrence of malaria and the shortening of annual time of occurrence in the future.

Suggested Citation

  • Jaewon Kwak & Huiseong Noh & Soojun Kim & Vijay P. Singh & Seung Jin Hong & Duckgil Kim & Keonhaeng Lee & Narae Kang & Hung Soo Kim, 2014. "Future Climate Data from RCP 4.5 and Occurrence of Malaria in Korea," IJERPH, MDPI, vol. 11(10), pages 1-19, October.
    • Handle: RePEc:gam:jijerp:v:11:y:2014:i:10:p:10587-10605:d:41186
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    References listed on IDEAS

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