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Data Modelling to Optimise Emergency Healthcare Responses
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Dissertation
Data Modelling to Optimise Emergency Healthcare Responses
2024
Overview
Public health emergencies can arise from many different sources and have a wide range of potential impacts. In general, planning and preparation is key in mitigating the effects of these emergencies. In this thesis, we carry out statistical analyses of the two most significant public health emergencies to have occurred in the United Kingdom in recent years; the 2017 Manchester Arena bombing and the COVID-19 pandemic. We demonstrate applications of a variety of modelling techniques in regression analysis to data from each of these events. Such analyses are important in understanding the impacts of public health emergencies, and in turn guiding the preparation for subsequent emergencies. More specifically, we consider the effects of treatment wait times following the Manchester Arena bombing on final patient outcomes. Further, we investigate characteristics of patients affecting their probability of self-presenting to hospital following the attack. For the COVID-19 pandemic, we investigate the effects of the disease on care homes in England, with particular focus on factors affecting the risks of mortality. We investigate how this risk changes over time, through the type and size of care home, and through geographical space. The results of our analyses for the Manchester Arena bombing could be used to guide planning around events to mitigate the risks and impacts of potential future mass casualty incidents. Conversely, our investigations into COVID-19 in care homes were used throughout the COVID-19 pandemic to inform policy.
Publisher
ProQuest Dissertations & Theses
Subject
ISBN
9798290987316
