title: Time Series Modelling of Syphilis Incidence in China from 2005 to 2012.
abstract: BACKGROUND
  The infection rate of syphilis in China has increased dramatically in recent decades, becoming a serious public health concern. Early prediction of syphilis is therefore of great importance for heath planning and management.
  
  
  METHODS
  In this paper, we analyzed surveillance time series data for primary, secondary, tertiary, congenital and latent syphilis in mainland China from 2005 to 2012. Seasonality and long-term trend were explored with decomposition methods. Autoregressive integrated moving average (ARIMA) was used to fit a univariate time series model of syphilis incidence. A separate multi-variable time series for each syphilis type was also tested using an autoregressive integrated moving average model with exogenous variables (ARIMAX).
  
  
  RESULTS
  The syphilis incidence rates have increased three-fold from 2005 to 2012. All syphilis time series showed strong seasonality and increasing long-term trend. Both ARIMA and ARIMAX models fitted and estimated syphilis incidence well. All univariate time series showed highest goodness-of-fit results with the ARIMA(0,0,1)×(0,1,1) model.
  
  
  CONCLUSIONS
  Time series analysis was an effective tool for modelling the historical and future incidence of syphilis in China. The ARIMAX model showed superior performance than the ARIMA model for the modelling of syphilis incidence. Time series correlations existed between the models for primary, secondary, tertiary, congenital and latent syphilis.
authors.affiliation: Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand.|Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, P.R.China.
authors.forename: Xingyu
authors.initials: X
authors.lastname: Zhang
authors.affiliation: Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, P.R.China.
authors.forename: Tao
authors.initials: T
authors.lastname: Zhang
authors.affiliation: Department of Science and Education, Sichuan Cancer Hospital & Institute, Sichuan, China.
authors.forename: Jiao
authors.initials: J
authors.lastname: Pei
authors.affiliation: Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, P.R.China.
authors.forename: Yuanyuan
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Epidemiology and Health Statistics, West China School of Public Health, Sichuan University, Chengdu, Sichuan, P.R.China.
authors.forename: Xiaosong
authors.initials: X
authors.lastname: Li
authors.affiliation: Department of Anatomy with Radiology, University of Auckland, Auckland, New Zealand.
authors.forename: Pau
authors.initials: P
authors.lastname: Medrano-Gracia
mesh_terms: D002681:China / Q000453:epidemiology; D006801:Humans; D015994:Incidence; D015233:Models, Statistical; D013587:Syphilis / Q000453:epidemiology*