Spatiotemporal variation in the risk of out-of-hospital cardiac arrests in Queensland, Australia

Doan, Tan N., Wilson, Daniel, Rashford, Stephen, Ball, Stephen, and Bosley, Emma (2021) Spatiotemporal variation in the risk of out-of-hospital cardiac arrests in Queensland, Australia. Resuscitation Plus, 8. 100166.

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Abstract

Background: Spatiotemporal analysis of out-of-hospital cardiac arrest (OHCA) risk is essential to design targeted public health strategies. Such information is lacking in the state of Queensland and Australia more broadly.

Methods: We developed a spatiotemporal Bayesian model accounting for spatial and temporal dimensions, space-time interactions, and demographic factors. The model was fit to data of all OHCA cases attended by paramedics in Queensland between January 2007 and December 2019. Parameter inference was performed using the integrated nested Laplace approximation method. We estimated and thematically mapped area-year risk of OHCA occurrence for all 78 local government areas (LGAs) in Queensland.

Results: We observed spatial variability in OHCA risk among the LGAs. Areas in the north half of the state and two areas in the south exhibited the highest risk; whereas OHCA risk was lowest in the west and south west parts of the state. Demographic factors did not have significant impact on the heterogeneity of risk between the LGAs. An overall trend of modestly decreasing risk of OHCA was found.

Conclusions: This study identified areas of high OHCA risk in Queensland, providing valuable information to guide public health policy and optimise resource allocation. Further research is needed to investigate the specifics of the areas that may explain their risk profile.

Item ID: 72283
Item Type: Article (Research - C1)
ISSN: 2666-5204
Keywords: Bayesian, Out-of-hospital cardiac arrest, Spatiotemporal model
Copyright Information: © 2021 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Date Deposited: 09 Feb 2022 12:51
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