In this paper, a unified susceptible-exposed-infected-susceptible-aware (SEIS-A) framework is proposed to combine epidemic spreading with individuals' on-line self-consultation behaviors. An epidemic spreading prediction model is established based on the SEIS-A framework. The prediction process contains two phases. In phase I, the time series data of disease density are decomposed through the empirical mode decomposition (EMD) method to obtain the intrinsic mode functions (IMFs). In phase II, the ensemble learning techniques which use the on-line query data as an additional input are applied to these IMFs. Finally, experiments for prediction of weekly consultation rates of Hand-foot-and-mouth disease (HFMD) in Hong Kong are conducted to validate the effectiveness of the proposed method. The main advantage of this method is that it outperforms other methods on fluctuating complex data.
翻译:本文提出统一的易感染性受感染认知框架(SEIS-A),将流行病传播与个人在线自我咨询行为相结合。根据SEIS-A框架,建立了流行病传播预测模型。预测过程分为两个阶段。在第一阶段,疾病密度的时间序列数据通过经验模式分解方法分解,以获得内在模式功能(IMFs)。在第二阶段,使用在线查询数据作为补充投入的混合学习技术适用于这些IMF。最后,对香港每周一次的手足和口腔疾病(HFMD)咨询率预测进行实验,以验证拟议方法的有效性。这种方法的主要优点是,它优于变化复杂数据的其他方法。