Spatiotemporal mapping of major trauma in Victoria, Australia

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

doi:10.1371/journal.pone.0266521

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Spatiotemporal mapping of major trauma in Victoria, Australia

Ben Beck

, Andrew Zammit-Mangion, Rich Fry

, Karen Smith, Belinda Gabbe

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

Swansea University Authors: Rich Fry , Belinda Gabbe

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DOI (Published version): 10.1371/journal.pone.0266521

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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ISSN:	1932-6203
Published:	Public Library of Science 2022
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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.</abstract><type>Journal Article</type><journal>PLOS ONE</journal><volume>17</volume><journalNumber>7</journalNumber><paginationStart>e0266521</paginationStart><paginationEnd/><publisher>Public Library of Science</publisher><placeOfPublication/><isbnPrint/><isbnElectronic/><issnPrint/><issnElectronic>1932-6203</issnElectronic><keywords/><publishedDay>6</publishedDay><publishedMonth>7</publishedMonth><publishedYear>2022</publishedYear><publishedDate>2022-07-06</publishedDate><doi>10.1371/journal.pone.0266521</doi><url/><notes>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. 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BG was supported by an Australian Research Council Future Fellowship (FT170100048).</funders><lastEdited>2022-07-07T17:00:36.4808607</lastEdited><Created>2022-07-07T16:54:50.3896484</Created><path><level id="1">Faculty of Medicine, Health and Life Sciences</level><level id="2">Swansea University Medical School - Medicine</level></path><authors><author><firstname>Ben</firstname><surname>Beck</surname><orcid>0000-0003-3262-5956</orcid><order>1</order></author><author><firstname>Andrew</firstname><surname>Zammit-Mangion</surname><order>2</order></author><author><firstname>Rich</firstname><surname>Fry</surname><orcid>0000-0002-7968-6679</orcid><order>3</order></author><author><firstname>Karen</firstname><surname>Smith</surname><order>4</order></author><author><firstname>Belinda</firstname><surname>Gabbe</surname><orcid>0000-0001-7096-7688</orcid><order>5</order></author></authors><documents><document><filename>60403__24491__5dfb2c1505934619a369c9b1cf045893.pdf</filename><originalFilename>60403_VoR.pdf</originalFilename><uploaded>2022-07-07T16:58:37.8540825</uploaded><type>Output</type><contentLength>2352687</contentLength><contentType>application/pdf</contentType><version>Version of Record</version><cronfaStatus>true</cronfaStatus><documentNotes>© 2022 Beck et al. 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spelling	2022-07-07T17:00:36.4808607 v2 60403 2022-07-07 Spatiotemporal mapping of major trauma in Victoria, Australia d499b898d447b62c81b2c122598870e0 0000-0002-7968-6679 Rich Fry Rich Fry true false 4bdcc94332b2bd10530c5e71ceb04f14 0000-0001-7096-7688 Belinda Gabbe Belinda Gabbe true false 2022-07-07 HDAT 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. Journal Article PLOS ONE 17 7 e0266521 Public Library of Science 1932-6203 6 7 2022 2022-07-06 10.1371/journal.pone.0266521 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 NANME Health Data Science COLLEGE CODE HDAT Swansea University 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). 2022-07-07T17:00:36.4808607 2022-07-07T16:54:50.3896484 Faculty of Medicine, Health and Life Sciences Swansea University Medical School - Medicine Ben Beck 0000-0003-3262-5956 1 Andrew Zammit-Mangion 2 Rich Fry 0000-0002-7968-6679 3 Karen Smith 4 Belinda Gabbe 0000-0001-7096-7688 5 60403__24491__5dfb2c1505934619a369c9b1cf045893.pdf 60403_VoR.pdf 2022-07-07T16:58:37.8540825 Output 2352687 application/pdf Version of Record true © 2022 Beck et al. This is an open access article distributed under the terms of the Creative Commons Attribution License true eng http://creativecommons.org/licenses/by/4.0/
title	Spatiotemporal mapping of major trauma in Victoria, Australia
spellingShingle	Spatiotemporal mapping of major trauma in Victoria, Australia Rich Fry Belinda Gabbe
title_short	Spatiotemporal mapping of major trauma in Victoria, Australia
title_full	Spatiotemporal mapping of major trauma in Victoria, Australia
title_fullStr	Spatiotemporal mapping of major trauma in Victoria, Australia
title_full_unstemmed	Spatiotemporal mapping of major trauma in Victoria, Australia
title_sort	Spatiotemporal mapping of major trauma in Victoria, Australia
author_id_str_mv	d499b898d447b62c81b2c122598870e0 4bdcc94332b2bd10530c5e71ceb04f14
author_id_fullname_str_mv	d499b898d447b62c81b2c122598870e0_*_Rich Fry 4bdcc94332b2bd10530c5e71ceb04f14_*_Belinda Gabbe
author	Rich Fry Belinda Gabbe
author2	Ben Beck Andrew Zammit-Mangion Rich Fry Karen Smith Belinda Gabbe
format	Journal article
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publishDate	2022
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doi_str_mv	10.1371/journal.pone.0266521
publisher	Public Library of Science
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description	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.
published_date	2022-07-06T04:18:29Z
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Spatiotemporal mapping of major trauma in Victoria, Australia

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