A Bayesian assessment of the effect of highway bypasses in Iowa on crashes and crash rate

J Safety Res. 2011 Aug;42(4):241-52. doi: 10.1016/j.jsr.2011.05.007. Epub 2011 Jul 22.


Introduction: A common contention is that the construction of highway bypasses negatively impacts the economy of local communities by reducing pass-by traffic for businesses. However, as access to specific business' account records is limited, this impact is difficult to quantify. Another common contention is that bypasses contribute to a reduction in overall crashes in the community and in the surrounding areas. Even though a large number of bypasses have been constructed in the State of Iowa over the past several years, their actual impact in terms of traffic safety has not been quantified.

Objectives: This study seeks answers to the following questions: (a) Are bypasses in Iowa associated with a reduction in crash frequencies and crash rates on the bypassed highway? (b) Do bypasses in Iowa introduce a reduction of overall crash frequencies and rates or do they merely shift crashes from the highways through the communities to the bypasses with no significant overall reduction?

Method: We obtained crash information from the Iowa DOT at 19 sites on which a bypass was constructed sometime during the past 23 years. We also obtained the same information at six sites used as comparison sites on which no bypasses were constructed at least until 2005. We them employed a Bayesian approach to estimating the association between the construction of the bypass and crash rates, while also accounting for other factors.

Results: The construction of bypasses in Iowa is associated with a significant increase in traffic safety both on the main road through town and on the combined main road and bypass roadway.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic / prevention & control*
  • Accidents, Traffic / statistics & numerical data
  • Automobile Driving*
  • Automobiles*
  • Bayes Theorem*
  • Data Collection
  • Environment Design / statistics & numerical data*
  • Humans
  • Iowa
  • Poisson Distribution
  • Public Health / methods*
  • Risk Assessment
  • Safety*