The injury epidemiology of cyclists based on a road trauma registry

<p>Abstract</p> <p>Background</p> <p>Bicycle use has increased in some of France's major cities, mainly as a means of transport. Bicycle crashes need to be studied, preferably by type of cycling. Here we conduct a descriptive analysis.</p> <p>Method</p> <p>A road trauma registry has been in use in France since 1996, in a large county around Lyon (the Rhône, population 1.6 million). It covers outpatients, inpatients and fatalities. All injuries are coded using the Abbreviated Injury Scale (AIS). Proxies were used to identify three types of cycling: learning = children (0-10 years old); sports cycling = teenagers and adults injured outside towns; cycling as means of transport = teenagers and adults injured in towns. The study is based on 13,684 cyclist casualties (1996-2008).</p> <p>Results</p> <p>The percentage of cyclists injured in a collision with a motor vehicle was 8% among children, 17% among teenagers and adults injured outside towns, and 31% among those injured in towns. The percentage of serious casualties (MAIS 3+) was 4.5% among children, 10.9% among adults injured outside towns and 7.2% among those injured in towns. Collisions with motor-vehicles lead to more internal injuries than bicycle-only crashes.</p> <p>Conclusion</p> <p>The description indicates that cyclist type is associated with different crash and injury patterns. In particular, cyclists injured in towns (where cycling is increasing) are generally less severely injured than those injured outside towns for both types of crash (bicycle-only crashes and collisions with a motor vehicle). This is probably due to lower speeds in towns, for both cyclists and motor vehicles.</p

Integrity and Trust of Geographic Information

International audienceThis chapter presents the concepts of integrity and trust in the context of the assessment of spatial data quality. It describes approaches that can be used to assess the internal and external quality of geolocated information produced by mobile objects. The first step, a bottom‐up approach, suggests assessing the integrity of information based on the database structure. The second step, a top‐down approach, suggests assessing the trust that should be given to information based on the measures that can be applied to a dataset. Taking the example of geolocation data, in particular, in the context of maritime navigation, the chapter demonstrates how these concepts and methods may be used to define the integrity and trust of the data produced by a vessel monitoring system. Characterizing the integrity and trust of geographic information makes it possible to provide better information about the uncertainty of the data used in decision‐making processes in maritime safety