斯里兰卡科伦坡地区登革热周发病率建模与预测

K. Arachchi, T. Peiris
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引用次数: 0

摘要

本研究旨在建立斯里兰卡科伦坡地区登革热周发病率的时间序列模型。研究使用了卫生部流行病学报告中2015年1月至2020年8月登革热每周发生计数。ARIMA(2,1,0)加上AR(16)被认为是最有效的模型。该模型使用2015年1月至2019年12月的数据进行训练。利用平衡数据对模型进行验证。模型残差满足随机和常方差,但残差明显偏离正态性。结果表明,预报数据与观测序列基本一致。然而,在20世纪20年代末,连续观察到明显的百分比误差。这些错误可能是由于Covid-19大流行的社会和业务冲击导致登革热病例报告不足。关键词:ARIMA,登革热,时间序列分析
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modeling and Forecasting of the Weekly Incidence of Dengue in Colombo District of Sri Lanka
This study was designed to develop a time series model for the weekly incidence of dengue in the Colombo district of Sri Lanka. Weekly occurrence of dengue fever counts from January 2015 to August 2020 in the Epidemiological Report by the Ministry of Health was used for the study . ARIMA (2,1,0) with the addition of AR (16) was identified as the most effective model. The model was trained using data from January 2015 to December 2019. The balance data was used to validate the model. The residuals of the model satisfied the randomness and constant variance, but the residuals significantly deviated from the normality. The results showed that the forecasted figures were consistent with the observed series. However, a noticeable percentage error was observed sequentially in the late 2020s. Those errors could be attributable to the fact that there was an underreporting of dengue fever cases due to social and operational shocks of the Covid-19 Pandemic. Keywords: ARIMA, Dengue, Time series analysis
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