明天的登革热:来自孟加拉国ARIMA和SARIMA模型的预测见解:时间序列分析
Pratyay Hasan1, Tazdin Delwar Khan2, Ishteaque Alam3
1Department of Respiratory Medicine (OPD) Dhaka Medical College Hospital Dhaka Bangladesh.
Health science reports
|December 19, 2024
概括
使用时间序列分析预测孟加拉国登革热的情况,显示了对2024年的不同预测. 阿里马模型表明流行率稳定,而萨里马模型表明登革热病例的大幅波动.
科学领域:
- 流行病学 流行病学
- 公共卫生 公共卫生
- 时间序列分析时间序列分析
背景情况:
- 登革热在孟加拉国是一个重大和持续的公共卫生挑战.
- 最近登革热病例的激增凸显了迫切需要有效的预测方法.
研究的目的:
- 应用自动回归集成移动平均 (ARIMA) 和季节自动回归集成移动平均 (SARIMA) 模型进行登革热流行率分析.
- 预测未来12个月孟加拉国每月的登革热流行情况.
主要方法:
- 利用了来自IEDCR和DGHS的登革热发病率的二次数据.
- 使用ARIMA和SARIMA模型进行时间序列预测.
- 遵循STROBE关于观察性研究报告的指导方针.
主要成果:
- 确定了ARIMA (1,1,1) 和SARIMA (1,1,2) 作为表现最好的模型.
- 根据ARIMA的预测,到2024年登革热的流行率将保持稳定.
- 萨里马预测预测2024年登革热病例的显著波动.
结论:
- 开发的模型为公共卫生规划和资源分配提供了有价值的数据.
- 承认外部因素和复杂的相互作用对登革热传播的影响.
- 预计未来孟加拉国登革热患病率可能会增加.
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