Highlights Crash records help fill gaps in traditional occupational surveillance systems. Crash records can guide traffic safety countermeasures targeting AgFF crashes. Machine learning can be applied to crash narratives to improve safety in AgFF.

    Abstract Problem: Fatal injuries in the agriculture, forestry, and fishing sector (AgFF) outweigh those across all sectors in the United States. Transportation-related injuries are among the top contributors to these fatal events. However, traditional occupational injury surveillance systems may not completely capture crashes involving farm vehicles and logging trucks, specifically nonfatal events. Methods: The study aimed to develop an integrated database of AgFF-related motor-vehicle crashes for the southwest (Arkansas, Louisiana, New Mexico, Oklahoma, and Texas) and to use these data to conduct surveillance and research. Lessons learned during the pursuit of these aims were cataloged. Activities centered around the conduct of traditional statistical and geospatial analyses of structured data fields and natural language processing of free-text crash narratives. Results: The structured crash data in each state include fields that allowed farm vehicles or equipment and logging trucks to be identified. The variable definitions and coding were not consistent across states but could be harmonized. All states recorded data fields pertaining to person, vehicle, and crash/environmental factors. Structured data supported the construction of crash severity models and geospatial analyses. Law enforcement provided additional details on crash causation in free-text narratives. Crash narratives contained sufficient text to support viable machine learning models for farm vehicle or equipment crashes, but not for logging truck narratives. Discussion: Crash records can help to fill research and surveillance gaps in AgFF in the southwest region. This supports traffic safety’s evolution to the current Safe System paradigm. There is a conceptual linkage between the Safe System and Total Worker Health approaches, providing a bridge between traffic safety and occupational health. Practical Applications : Despite limitations, crash records can be an important component of injury surveillance for events involving AgFF vehicles. They also can be used to inform the selection and evaluation of traffic countermeasures and behavioral interventions.


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    Titel :

    Using motor vehicle crash records for injury surveillance and research in agriculture and forestry


    Beteiligte:
    Shipp, Eva M. (Autor:in) / Trueblood, Amber B. (Autor:in) / Kum, Hye-Chung (Autor:in) / Perez, Marcie (Autor:in) / Vasudeo, Shubhangi (Autor:in) / Sinha, Nishita (Autor:in) / Pant, Ashesh (Autor:in) / Wu, Lingtao (Autor:in) / Ko, Myunghoon (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2023-06-05


    Format / Umfang :

    9 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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