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Spatiotemporal mapping of major trauma in Victoria, Australia

Ben Beck Orcid Logo, Andrew Zammit-Mangion, Rich Fry Orcid Logo, Karen Smith, Belinda Gabbe Orcid Logo

PLOS ONE, Volume: 17, Issue: 7, Start page: e0266521

Swansea University Authors: Rich Fry Orcid Logo, Belinda Gabbe Orcid Logo

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Abstract

Background: Spatiotemporal modelling techniques allow one to predict injury across time and space. However, such methods have been underutilised in injury studies. This study demonstrates the use of statistical spatiotemporal modelling in identifying areas of significantly high injury risk, and area...

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Published in: PLOS ONE
ISSN: 1932-6203
Published: Public Library of Science 2022
Online Access: Check full text

URI: https://cronfa.swan.ac.uk/Record/cronfa60403
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Abstract: Background: Spatiotemporal modelling techniques allow one to predict injury across time and space. However, such methods have been underutilised in injury studies. This study demonstrates the use of statistical spatiotemporal modelling in identifying areas of significantly high injury risk, and areas witnessing significantly increasing risk over time. Methods: We performed a retrospective review of hospitalised major trauma patients from the Victorian State Trauma Registry, Australia, between 2007 and 2019. Geographical locations of injury events were mapped to the 79 local government areas (LGAs) in the state. We employed Bayesian spatiotemporal models to quantify spatial and temporal patterns, and analysed the results across a range of geographical remoteness and socioeconomic levels. Results: There were 31,317 major trauma patients included. For major trauma overall, we observed substantial spatial variation in injury incidence and a significant 2.1% increase in injury incidence per year. Area-specific risk of injury by motor vehicle collision was higher in regional areas relative to metropolitan areas, while risk of injury by low fall was higher in metropolitan areas. Significant temporal increases were observed in injury by low fall, and the greatest increases were observed in the most disadvantaged LGAs. Conclusions: These findings can be used to inform injury prevention initiatives, which could be designed to target areas with relatively high injury risk and with significantly increasing injury risk over time. Our finding that the greatest year-on-year increases in injury incidence were observed in the most disadvantaged areas highlights the need for a greater emphasis on reducing inequities in injury.
Item Description: Data Availability Statement: The Victorian State Trauma Registry (VSTR) is governed by the Victorian State Trauma Outcomes Registry Monitoring Group (VSTORM). Some authors (BB, KS, BG) are members of VSTORM, and BB and BG are Chief Investigators on the Victorian State Trauma Registry. Access to VSTR requiresapproval from the data custodians, VSTORM. Data requests can be made through Susan McLellan(susan.mclellan@monash.edu) or through the following link: https://www.monash.edu/medicine/ sphpm/vstorm/data-requests Sharing a deidentified data set is not possible due to restrictions imposed by the Victorian Department of Health Ethics Committee, which have provided ethical approval for the collection and subsequent use of VSTR data. Further, and as described above, data requests are managed by VSTORM and subject to a full and detailed review by the VSTORM group.
College: Faculty of Medicine, Health and Life Sciences
Funders: The VSTR is a Department of Health, State Government of Victoria, and Transport Accident Commission (TAC) funded project. BB and AZM were supported by Australian Research Council Discovery Early Career Researcher Award Fellowships (DE180100825 and DE180100203, respectively). BG was supported by an Australian Research Council Future Fellowship (FT170100048).
Issue: 7
Start Page: e0266521