title: Examining Road Traffic Mortality Status in China: A Simulation Study.
abstract: BACKGROUND
  Data from the Chinese police service suggest substantial reductions in road traffic injuries since 2002, but critics have questioned the accuracy of those data, especially considering conflicting data reported by the health department.
  
  
  METHODS
  To address the gap between police and health department data and to determine which may be more accurate, we conducted a simulation study based on the modified Smeed equation, which delineates a non-linear relation between road traffic mortality and the level of motorization in a country or region. Our goal was to simulate trends in road traffic mortality in China and compare performances in road traffic safety management between China and 13 other countries.
  
  
  RESULTS
  Chinese police data indicate a peak in road traffic mortalities in 2002 and a significant and a gradual decrease in population-based road traffic mortality since 2002. Health department data show the road traffic mortality peaked in 2012. In addition, police data suggest China's road traffic mortality peaked at a much lower motorization level (0.061 motor vehicles per person) in 2002, followed by a reduction in mortality to a level comparable to that of developed countries. Simulation results based on health department data suggest high road traffic mortality, with a mortality peak in 2012 at a moderate motorization level (0.174 motor vehicles per person). Comparisons to the other 13 countries suggest the health data from China may be more valid than the police data.
  
  
  CONCLUSIONS
  Our simulation data indicate China is still at a stage of high road traffic mortality, as suggested by health data, rather than a stage of low road traffic mortality, as suggested by police data. More efforts are needed to integrate safety into road design, improve road traffic management, improve data quality, and alter unsafe behaviors of pedestrians, drivers and passengers in China.
authors.affiliation: Urban Transport Research Center, School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China.
authors.forename: Helai
authors.initials: H
authors.lastname: Huang
authors.affiliation: Urban Transport Research Center, School of Traffic and Transportation Engineering, Central South University, Changsha, 410075, China.
authors.forename: Qingyi
authors.initials: Q
authors.lastname: Yin
authors.affiliation: Department of Psychology, University of Alabama at Birmingham, Birmingham, 35294, United States of America.
authors.forename: David C
authors.initials: DC
authors.lastname: Schwebel
authors.affiliation: Department of Epidemiology, School of Public Health, West Virginia University, Morgantown, West Virginia, United States America.
authors.forename: Li
authors.initials: L
authors.lastname: Li
authors.affiliation: Department of Epidemiology and Health Statistics, Xiangya School of Public Health, Central South University, Changsha, 410078, China.
authors.forename: Guoqing
authors.initials: G
authors.lastname: Hu
mesh_terms: D000063:Accidents, Traffic / Q000401:mortality*; D002681:China / Q000453:epidemiology; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D016014:Linear Models; D018986:Motor Vehicles / Q000706:statistics & numerical data; D017711:Nonlinear Dynamics; D016495:Police / Q000706:statistics & numerical data; D011634:Public Health / Q000706:statistics & numerical data; D017751:Safety Management / Q000706:statistics & numerical data