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.
Highlights
Malaria is an acute infectious disease caused by plasmodium parasite infection in red blood cells and liver cells
Spectral analysis must be done to reflect the time lag between each variable and the BDS test was done to check the randomness of the time series
Autospectrum or crossspectrum is a method to explain the distribution of variance of frequency drawn from a single or multiple data [38]
Summary
Malaria is an acute infectious disease caused by plasmodium parasite infection in red blood cells and liver cells. The World Health Organization (WHO) has designated malaria as one of the six major tropical diseases. Infectious diseases that use host as a means of infection are highly susceptible to climate which influences interactions within the ecosystem [1]. Mosquito-borne diseases are especially susceptible and it is known that they are greatly influenced by temperature, precipitation, humidity and other factors. Amongst these diseases, malaria is the most well addressed infectious disease and it is most susceptible to climate change [2]
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