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    Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia.

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    Author
    Gardiner, FW; Johns, H; Bishop, L; Churilov, L
    Date
    2020-09
    Source Title
    Air Medical Journal
    Publisher
    Elsevier BV
    University of Melbourne Author/s
    Churilov, Leonid; Johns, Hannah
    Affiliation
    Medicine and Radiology
    Medicine and Radiology
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Gardiner, F. W., Johns, H., Bishop, L. & Churilov, L. (2020). Royal Flying Doctor Service Coronavirus Disease 2019 Activity and Surge Modeling in Australia.. Air Med J, 39 (5), pp.404-409. https://doi.org/10.1016/j.amj.2020.05.011.
    Access Status
    Access this item via the Open Access location
    URI
    http://hdl.handle.net/11343/254483
    DOI
    10.1016/j.amj.2020.05.011
    Open Access URL
    https://europepmc.org/articles/PMC7229980?pdf=render
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7229980
    Abstract
    Objective: There is a coronavirus disease 2019 (COVID-19) pandemic. We aimed to describe the characteristics of patients transported by the Royal Flying Doctor Service (RFDS) for confirmed or suspected COVID-19 and to investigate the surge capacity of and operational implications for the RFDS in dealing with COVID-19. Methods: This was a prospective cohort study. To determine the characteristics of patients transported for confirmed or suspected COVID-19, we included patient data from February 2, 2020, to May 6, 2020. To investigate the surge capacity and operational implications for the RFDS in dealing with COVID-19, we built and validated an interactive operations area-level discrete event simulation decision support model underpinned by RFDS air medical activity data from 2015 to 2019 (4 years). This model was subsequently used in a factorial in silico experiment to systematically investigate both the supply of RFDS air medical services and the increased rates of demand for these services for diseases of the respiratory system. Results: The RFDS conducted 291 patient episodes of care for confirmed or suspected COVID-19. This included 288 separate patients, including 136 men and 119 women (sex missing = 33), with a median age of 62.0 years (interquartile range, 43.5-74.9 years). The simulation decision support model we developed is capable of providing dynamic and real-time support for RFDS decision makers in understanding the system's performance under uncertain COVID-19 demand. With increased COVID-19-related demand, the ability of the RFDS to cope will be driven by the number of aircraft available. The simulation model provided each aviation section with estimated numbers of aircraft required to meet a range of anticipated demands. Conclusion: Despite the lack of certainty in the actual level of COVID-19-related demand for RFDS services, modeling demonstrates that the robustness of meeting such demand increases with the number of operational and medically staffed aircraft.

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