title: Temporal and long-term trend analysis of class C notifiable diseases in China from 2009 to 2014.
abstract: Time series models are effective tools for disease forecasting. This study aims to explore the time series behaviour of 11 notifiable diseases in China and to predict their incidence through effective models.
  
  
  
  The Chinese Ministry of Health started to publish class C notifiable diseases in 2009. The monthly reported case time series of 11 infectious diseases from the surveillance system between 2009 and 2014 was collected.
  
  
  
  We performed a descriptive and a time series study using the surveillance data. Decomposition methods were used to explore (1) their seasonality expressed in the form of seasonal indices and (2) their long-term trend in the form of a linear regression model. Autoregressive integrated moving average (ARIMA) models have been established for each disease.
  
  
  
  The number of cases and deaths caused by hand, foot and mouth disease ranks number 1 among the detected diseases. It occurred most often in May and July and increased, on average, by 0.14126/100 000 per month. The remaining incidence models show good fit except the influenza and hydatid disease models. Both the hydatid disease and influenza series become white noise after differencing, so no available ARIMA model can be fitted for these two diseases.
  
  
  
  Time series analysis of effective surveillance time series is useful for better understanding the occurrence of the 11 types of infectious disease.
authors: Department of Epidemiology & Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China.|Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand.
authors: Xingyu
authors: X
authors: Zhang
authors: Sun Yat-sen Global Health Institute, School of Public Health, Sun Yat-sen University, Guangzhou, Guangdong, China.
authors: Fengsu
authors: F
authors: Hou
authors: Department of Epidemiology & Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China.
authors: Zhijiao
authors: Z
authors: Qiao
authors: Department of Epidemiology & Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China.
authors: Xiaosong
authors: X
authors: Li
authors: Department of Respiratory, Sichuan Centre for Disease Control and Prevention, Sichuan, China.
authors: Lijun
authors: L
authors: Zhou
authors: Department of Epidemiology & Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China.
authors: Yuanyuan
authors: Y
authors: Liu
authors: Department of Epidemiology & Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, China.
authors: Tao
authors: T
authors: Zhang
mesh_terms: D002681:China / Q000453:epidemiology; D003141:Communicable Diseases / Q000453:epidemiology*; D018563:Disease Notification / Q000379:methods*; D005544:Forecasting; D006302:Health Services Research; D006801:Humans; D015994:Incidence; D065186:Interrupted Time Series Analysis; D011159:Population Surveillance / Q000379:methods*; D012621:Seasons
keywords: Seasonality; infectious disease; long term trend; time series