Scrub Typhus Incidence Modeling with Meteorological Factors in South Korea

Jaewon Kwak, Soojun Kim, Gilho Kim, Vijay P. Singh, Seungjin Hong and Hung Soo Kim
Additional contact information
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

IJERPH, 2015, vol. 12, issue 7, 1-20

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.

Keywords: scrub typhus; ANN; meteorological variables (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2015
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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