Fine-Scale Spatial Prediction on the Risk of Infection in the Republic of Korea.

Journal: Journal of Korean medical science
Published Date: Jun 10, 2024

Abstract

BACKGROUND: Malaria elimination strategies in the Republic of Korea (ROK) have decreased malaria incidence but face challenges due to delayed case detection and response. To improve this, machine learning models for predicting malaria, focusing on high-risk areas, have been developed.

Authors

  • Kyung-Duk Min
    College of Veterinary Medicine, Chungbuk National University, Cheongju, Korea.
  • Yae Jee Baek
    Division of Infectious Diseases, Department of Internal Medicine, College of Medicine, Soonchunhyang University, Asan, Korea.
  • Kyungwon Hwang
    Division of Control for Zoonotic and Vector Borne Disease, Korea Disease Control and Prevention Agency, Cheongju, Korea.
  • Na-Ri Shin
    Division of Control for Zoonotic and Vector Borne Disease, Korea Disease Control and Prevention Agency, Cheongju, Korea.
  • So-Dam Lee
    Division of Control for Zoonotic and Vector Borne Disease, Korea Disease Control and Prevention Agency, Cheongju, Korea.
  • Hyesu Kan
    Division of Control for Zoonotic and Vector Borne Disease, Korea Disease Control and Prevention Agency, Cheongju, Korea.
  • Joon-Sup Yeom
    Division of Infectious Disease, Department of Internal Medicine, Yonsei University College of Medicine, Seoul, Korea. joonsup.yeom@yuhs.ac.

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