Related Experiment Video
Updated: Mar 9, 2026

A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
Published on: December 9, 2015
Multivariate time series analysis on the dynamic relationship between Class B notifiable diseases and gross domestic
Tao Zhang1, Fei Yin1, Ting Zhou1
1West China School of Public Health, Sichuan University, Chengdu, China.
Abstract:
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.
Related Concept Videos
Steps in Outbreak Investigation
Statistical Methods for Analyzing Epidemiological Data
Causality in Epidemiology
Single Nucleotide Polymorphisms-SNPs
Scatter Plot
Principles of Disease Surveillance