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4F.003 Spatially forecasting serious injury into the future
  1. Ben Beck,
  2. Belinda Gabbe
  1. Monash University, Melbourne, Australia


Background Understanding how injury varies across space and time is critical for informing injury prevention activities at a population level. The aim of this study was to use spatiotemporal modelling to investigate spatial and temporal variation in major trauma.

Methods A retrospective review of major trauma was conducted using the population-based Victorian State Trauma Registry (Victoria, Australia) from 2008 to 2018. Coordinates of ambulance attended major trauma event locations were mapped to small statistical areas. Bayesian spatiotemporal modelling was used to investigate spatial and temporal patterns and generate forecasted counts in each small area to 2023.

Results Over the 11-year period, there were 28,630 major trauma patients with known event coordinates. Substantial spatial variation in the incidence of all major trauma was observed. Generally, area-specific incidence rates were higher in regional areas than metropolitan areas. Global temporal trends in the incidence of major trauma demonstrated a significant increase, with relative increases greater in regional areas compared to metropolitan areas.

Differences in spatial and temporal variation were observed between causes of injury. For motor vehicle collisions, area-specific incidence rates were higher in regional areas than metropolitan areas. Conversely, for low falls, area-specific incidence rates were higher in metropolitan areas than regional areas.

Conclusion Spatiotemporal forecasting enables the identification of small areas of relatively high incidence and of increasing incidence over time. Furthermore, these models can be used to derive forecasted counts of trauma counts that can be used to inform injury prevention activities at the small spatial area.

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