泰国登革热发病率预测模型

Jutatip Sillabutra, P. Soontornpipit, C. Viwatwongkasem, P. Satitvipawee, Sadiporn Phuthomdee
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引用次数: 0

摘要

登革热感染是公认的重大健康问题,在许多国家,特别是在热带和亚热带地区发现了登革热的传播。在过去十年中,死亡率和发病率急剧上升。这个数学模型现在被用来解释疾病的未来趋势,作为早期预警系统。它可以提供有用的信息,导致有关预防和控制规划和干预战略的及时决策进程,以减轻疾病负担。ARIMA模型是用来解释疾病流行病学的著名模型。因此,本研究的目的是建立ARIMA模型来解释登革热发病率。模型中包括平均温度和相对湿度。采用2006-2015年泰国登革热发病率、平均气温、相对湿度等历史数据进行分析。结果表明,ARIMA $\pmb{(3,0,1)_{12}}$随平均温度和相对湿度的调整是描述登革热发病率的最优模型。其Al最小(554.21),RMSE最小(0.652)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Forecasting Model for Dengue Morbidity Rate in Thailand
Dengue infectious is recognized as major health problem and the spread of dengue was found in many countries, especially in tropical and subtropical regions. The mortality rate and morbidity rate have been dramatically increasing in last decade. The mathematical model were now used for explaining the future trends of disease, as the early warning system. It can provide useful information leading to timely decision making process regarding prevention and control planning and intervention strategies in order to reduce the burden of disease. The ARIMA model is famously used to explain the epidemiology of disease. Therefore, the aim of this study was to develop the ARIMA model for explaining dengue morbidity rate. The Average temperature and relative humidity were included in the model. The historical data such as dengue morbidity rate, average temperature and relative humidity in Thailand from 2006–2015 were used in analysis. The result found that ARIMA $\pmb{(3,0,1)_{12}}$ adjusted with average temperature and relative humidity was the optimal model to describe dengue morbidity rate. It had the smallest Al (554.21) and RMSE (0.652).
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