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Data Analysis

Anthropometry

  • Tosi, 20191: The Anthropometric Reference Data

Crash data analysis

  • Bareiss, 2020 2: Estimating near side crash injury risk in best performing passenger vehicles in the United States

This work suggests that injury risk in near-side impacts is higher when crash delta-v is higher, the occupant is over the age of 65, the occupant is female, the occupant’s BMI is higher, or the occupant’s vehicle received a lower score in the NCAP MDB test.

  • Pipkorn, 2020 3: Occupant injuries in light passenger vehicles: A {NASS} study to enable priorities for development of injury prediction capabilities of human body models

  • Miller, 20204: Patient Age Is Inversely Associated with Injury Counts Caused by Motor Vehicle Crashes.

  • Joodaki, 20195: Comparison of injuries of belted occupants among different BMI categories in frontal crashes

Vulnerable Road Users

  • Weaver, 20196: Sarcopenia and osteosarcopenia in seriously injured motor vehicle crash occupants

  • Meredith, 20207: Mapping fractures from traffic accidents in Sweden: How do cyclists compare to other road users?

  • Rizzi, 2020 8: The potential of different countermeasures to prevent injuries with high risk of health loss among bicyclists in Sweden

Improved maintenance by deicing and removal of snow from bicycle infrastructure was found to have the highest potential (8%), followed by improved crashworthiness of passenger cars (5%) and safer bicycle crossings (4%).

Child

  • Durbin, 20189: Child Passenger Safety

Falls

  • Ekbrand, 202010: Fall-related injuries for three ages groups- Analysis of Swedish registry data 1999-2013

  • Kleiven, 202011: Hip fracture risk functions for elderly men and women in sideways falls

Miscellaneous

  • Bhalla, 202012: Monitoring India's progress on road safety will require investment in data systems

  1. Francesca Tosi. The anthropometric reference data. In Springer Series in Design and Innovation, pages 217–231. Springer International Publishing, nov 2019. doi:10.1007/978-3-030-33562-5_11. ↩

  2. Max Bareiss and Hampton C. Gabler. Estimating near side crash injury risk in best performing passenger vehicles in the united states. Accident Analysis & Prevention, 138:105434, apr 2020. doi:10.1016/j.aap.2020.105434. ↩

  3. Bengt Pipkorn, Johan Iraeus, Mats Lindkvist, Pradeep Puthan, and Olle Bunketorp. Occupant injuries in light passenger vehicles—a NASS study to enable priorities for development of injury prediction capabilities of human body models. Accident Analysis & Prevention, 138:105443, apr 2020. doi:10.1016/j.aap.2020.105443. ↩

  4. Anna N. Miller, Justin Tilan, Alexandria Wellman, Jennifer Talton, Andrew Usoro, Katherine Sun, Scott Wuertzer, Leon Lenchik, Joel Stitzel, and Ashley Weaver. Patient age is inversely associated with injury counts caused by motor vehicle crashes. Journal of surgical orthopaedic advances, 29:36–38, 2020. ↩

  5. Hamed Joodaki, Bronislaw Gepner, Timothy McMurry, and Jason Kerrigan. Comparison of injuries of belted occupants among different BMI categories in frontal crashes. International Journal of Obesity, nov 2019. doi:10.1038/s41366-019-0481-2. ↩

  6. Ashley A. Weaver, Casey Costa, Alexander Ambrosini, Josh Tan, Lisa Maez, Xin Ye, Joel D. Stitzel, and Leon Lenchik. Sarcopenia and osteosarcopenia in seriously injured motor vehicle crash occupants. Traffic Injury Prevention, 20sup2:S195–S197, nov 2019. doi:10.1080/15389588.2019.1659620. ↩

  7. Lauren Meredith, Jordanka Kovaceva, and András Bálint. Mapping fractures from traffic accidents in sweden: how do cyclists compare to other road users? Traffic Injury Prevention, pages 1–6, mar 2020. doi:10.1080/15389588.2020.1724979. ↩

  8. Maria C. Rizzi, Matteo Rizzi, Anders Kullgren, and Beatrix Algurén. The potential of different countermeasures to prevent injuries with high risk of health loss among bicyclists in sweden. Traffic Injury Prevention, pages 1–7, mar 2020. doi:10.1080/15389588.2020.1730827. ↩

  9. Dennis R. Durbin and Benjamin D. Hoffman and. Child passenger safety. Pediatrics, 1425:e20182461, aug 2018. doi:10.1542/peds.2018-2461. ↩

  10. Hans Ekbrand, Robert Ekman, Charlotta Thodelius, and Michael Möller. Fall-related injuries for three ages groups – analysis of swedish registry data 1999–2013. Journal of Safety Research, 73:143–152, jun 2020. doi:10.1016/j.jsr.2020.02.016. ↩

  11. Svein Kleiven. Hip fracture risk functions for elderly men and women in sideways falls. Journal of Biomechanics, pages 109771, apr 2020. doi:10.1016/j.jbiomech.2020.109771. ↩

  12. Kavi Bhalla. Monitoring india\textquotesingle s progress on road safety will require investment in data systems. The Lancet Public Health, 52:e82, feb 2020. doi:10.1016/s2468-26671930252-x. ↩