Health is a very important prerequisite in peoples well-being and happiness. Several studies were more focused on presenting the occurrence on specific disease like forecasting the number of dengue and malaria cases. This paper utilized the time series data for trend analysis and data forecasting using ARIMA model to visualize the trends of health data on the ten leading causes of deaths, leading cause of morbidity and leading cause of infants deaths particularly in the Philippines presented in a tabular data. Figures for each disease trend are presented individually with the use of the GRETL software. Forecasting results of the leading causes of death showed that Diseases of the heart, vascular system, accidents, Chronic lower respiratory diseases and Chronic Tuberculosis (all forms) showed a slight changed of the forecasted data, Malignant neoplasms showed unstable behavior of the forecasted data, and Pneumonia, diabetes mellitus, Nephritis, nephrotic syndrome and nephrosis and certain conditions originating in perinatal showed a decreasing patterns based on the forecasted data.
翻译:这份论文利用时间序列数据进行趋势分析和数据预报,利用ARIMA模型对趋势进行分析和数据预报,利用该数据对10种主要死亡原因、主要发病原因和婴儿死亡主要原因的卫生数据趋势进行视觉分析,特别是在菲律宾,以表格形式提供的数据显示,每种疾病趋势的数字均使用GRETL软件逐个列出,主要死亡原因的预测结果显示,心脏病、血管系统、事故、慢性下呼吸道疾病和慢性肺结核(各种形式的)显示预测数据略有变化,恶性肿瘤显示预测数据的不稳定行为,肺炎、糖尿病、内膜炎、肾炎综合症和肾病以及围产期的某些情况根据预测数据呈现出一种下降模式。