Zhang Tao, Yin Fei, Zhou Ting, Zhang Xing-Yu, Li Xiao-Song
West China School of Public Health, Sichuan University, Chengdu, China.
Sci Rep. 2016 Dec 23;6:29. doi: 10.1038/s41598-016-0020-5.
The surveillance of infectious diseases is of great importance for disease control and prevention, and more attention should be paid to the Class B notifiable diseases in China. Meanwhile, according to the International Monetary Fund (IMF), the annual growth of Chinese gross domestic product (GDP) would decelerate below 7% after many years of soaring. Under such circumstances, this study aimed to answer what will happen to the incidence rates of infectious diseases in China if Chinese GDP growth remained below 7% in the next five years. Firstly, time plots and cross-correlation matrices were presented to illustrate the characteristics of data. Then, the multivariate time series (MTS) models were proposed to explore the dynamic relationship between incidence rates and GDP. Three kinds of MTS models, i.e., vector auto-regressive (VAR) model for original series, VAR model for differenced series and error-correction model (ECM), were considered in this study. The rank of error-correction term was taken as an indicator for model selection. Finally, our results suggested that four kinds of infectious diseases (epidemic hemorrhagic fever, pertussis, scarlet fever and syphilis) might need attention in China because their incidence rates have increased since the year 2010.
传染病监测对于疾病控制和预防至关重要，在中国应更加关注乙类法定传染病。同时，根据国际货币基金组织（IMF）的数据，经过多年的高速增长后，中国国内生产总值（GDP）的年增长率将降至7%以下。在这种情况下，本研究旨在回答如果未来五年中国GDP增长率保持在7%以下，中国传染病发病率会发生什么变化。首先，给出时间序列图和交叉相关矩阵以说明数据特征。然后，提出多元时间序列（MTS）模型以探索发病率与GDP之间的动态关系。本研究考虑了三种MTS模型，即原始序列的向量自回归（VAR）模型、差分序列的VAR模型和误差修正模型（ECM）。误差修正项的秩被用作模型选择的指标。最后，我们的结果表明，中国可能需要关注四种传染病（流行性出血热、百日咳、猩红热和梅毒），因为自2010年以来它们的发病率有所上升。
