Safety index of heat wave mortality using big data
Free (open access)
Volume 11 (2016), Issue 3
352 - 361
J.H. CHUNG, D.W. KIM, J.S. LEE & S.J. PARK
Safety-related research using big data is still in its early stage in Korea. Recently, we have tried to solve some safety-related problems using big data. In this research, we will attempt to solve heat wave-related death which is a significant potential concern associated with climate change.
Although deaths from heat disorders are a direct effect of heat wave incidences, only a few studies have addressed the causal factors between heat wave incidences and deaths from heat disorder. Regression analysis is applied to deduce the causal factors that affect the number of deaths from heat disorders (NDHD) in South Korea by using time-series dataset, which are the NDHD and climate data. Both are observational data from
1994 to 2012, collected from the National Statistical Office and the Korean Meteorological Agency, respec- tively. As a result, the duration of a heat wave and the age of the population are highly correlated with the NDHD. Based on this correlation, we also analyze the safety index of heat wave mortality.
The paper is structured as follows: First of all, it presents the data and methods, including our strategy for analysis of heat wave incidences based on observational and climate modeling datasets. The next section presents the results of regression models applied for predicting heat wave deaths in Korea and discusses the statistical analysis of the results
heat disorders, heat wave, heat wave-related big data, mortality, safety index