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Time series modeling of pertussis incidence in China from 2004 to 2018 with a novel wavelet based SARIMA-NAR hybrid model

机译：基于新型小波的SARIMA-NAR混合模型的2004年至2018年中国百日咳发病率的时间序列建模

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摘要

BackgroundIt is a daunting task to discontinue pertussis completely in China owing to its growing increase in the incidence. While basic to any formulation of prevention and control measures is early response for future epidemic trends. Discrete wavelet transform(DWT) has been emerged as a powerful tool in decomposing time series into different constituents, which facilitates better improvement in prediction accuracy. Thus we aim to integrate modeling approaches as a decision-making supportive tool for formulating health resources.

机译：背景技术由于百日咳的发病率不断增加，在中国完全停止百日咳是一项艰巨的任务。尽管任何预防和控制措施的制定都是对未来流行趋势的早期反应。离散小波变换（DWT）已成为一种强大的工具，可以将时间序列分解为不同的成分，从而有助于更好地提高预测精度。因此，我们旨在整合建模方法，将其作为制定卫生资源的决策支持工具。

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期刊名称 other
作者
Yongbin Wang; Chunjie Xu; Zhende Wang; Shengkui Zhang; Ying Zhu; Juxiang Yuan;
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年(卷),期 -1(13),12
年度 -1
页码 e0208404
总页数 23
原文格式 PDF
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6. Seasonality and trend prediction of scarlet fever incidence in mainland China from 2004 to 2018 using a hybrid SARIMA-NARX model [O] . Yongbin Wang, Chunjie Xu, Zhende Wang, -1

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7. Time series modeling of pertussis incidence in China from 2004 to 2018 with a novel wavelet based SARIMA-NAR hybrid model [O] . Yongbin Wang, Chunjie Xu, Zhende Wang, 2018

机译：2004年至2018年中国百日咳发病率的时间序列建模与基于小波的Sarima-NAR混合模型

Time series modeling of pertussis incidence in China from 2004 to 2018 with a novel wavelet based SARIMA-NAR hybrid model

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