A Case Study: Malaria Modeling Based on Climate Variables in Korea

Abstract

Malaria is influenced by climate variable and is the third grade infectious disease of Korea Government which has been slowly increasing patient in every year since its reocurrence in the Military Demarcation Line in Korea in 1993. This study is focused on the influence analysis with climate variable and malaria occurrence and construct the model for malaria prediction based on climate factor. To do so, data of monthly malaria infection,mean temperature, relative humidity and total precipitation will be collected. To observe time lag effect, auto and cross spectral density analysis will be applied. To consider multicollinearity of each climate variable, model of malaria infection will be structed based on principal components regression method. Result shows that model explains and verifies malaria"s infectivity using infection data from 2009 to 2011.