- School of Mathematics and Statistics - Research Publications
School of Mathematics and Statistics - Research Publications
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ItemNo Preview AvailableDevelopment of an influenza pandemic decision support tool linking situational analytics to national response policy.Shearer, FM ; Moss, R ; Price, DJ ; Zarebski, AE ; Ballard, PG ; McVernon, J ; Ross, JV ; McCaw, JM (Elsevier, 2021-06-19)National influenza pandemic plans have evolved substantially over recent decades, as has the scientific research that underpins the advice contained within them. While the knowledge generated by many research activities has been directly incorporated into the current generation of pandemic plans, scientists and policymakers are yet to capitalise fully on the potential for near real-time analytics to formally contribute to epidemic decision-making. Theoretical studies demonstrate that it is now possible to make robust estimates of pandemic impact in the earliest stages of a pandemic using first few hundred household cohort (FFX) studies and algorithms designed specifically for analysing FFX data. Pandemic plans already recognise the importance of both situational awareness i.e., knowing pandemic impact and its key drivers, and the need for pandemic special studies and related analytic methods for estimating these drivers. An important next step is considering how information from these situational assessment activities can be integrated into the decision-making processes articulated in pandemic planning documents. Here we introduce a decision support tool that directly uses outputs from FFX algorithms to present recommendations on response options, including a quantification of uncertainty, to decision makers. We illustrate this approach using response information from within the Australian influenza pandemic plan.
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ItemModelling the impact of COVID-19 in Australia to inform transmission reducing measures and health system preparednessMoss, R ; Wood, J ; Brown, D ; Shearer, F ; Black, AJ ; Cheng, AC ; McCaw, JM ; McVernon, J ( 2020)
ABSTRACT
Background
The ability of global health systems to cope with increasing numbers of COVID-19 cases is of major concern. In readiness for this challenge, Australia has drawn on clinical pathway models developed over many years in preparation for influenza pandemics. These models have been used to estimate health care requirements for COVID-19 patients, in the context of broader public health measures.Methods
An age and risk stratified transmission model of COVID-19 infection was used to simulate an unmitigated epidemic with parameter ranges reflecting uncertainty in current estimates of transmissibility and severity. Overlaid public health measures included case isolation and quarantine of contacts, and broadly applied social distancing. Clinical presentations and patient flows through the Australian health care system were simulated, including expansion of available intensive care capacity and alternative clinical assessment pathways.Findings
An unmitigated COVID-19 epidemic would dramatically exceed the capacity of the Australian health system, over a prolonged period. Case isolation and contact quarantine alone will be insufficient to constrain case presentations within a feasible level of expansion of health sector capacity. Overlaid social restrictions will need to be applied at some level over the course of the epidemic to ensure that systems do not become overwhelmed, and that essential health sector functions, including care of COVID-19 patients, can be maintained. Attention to the full pathway of clinical care is needed to ensure access to critical care.Interpretation
Reducing COVID-19 morbidity and mortality will rely on a combination of measures to strengthen and extend public health and clinical capacity, along with reduction of overall infection transmission in the community. Ongoing attention to maintaining and strengthening the capacity of health care systems and workers to manage cases is needed.Funding
Australian Government Department of Health Office of Health Protection, Australian Government National Health and Medical Research Council -
ItemCoronavirus Disease Model to Inform Transmission -Reducing Measures and Health System Preparedness, AustraliaMoss, R ; Wood, J ; Brown, D ; Shearer, FM ; Black, AJ ; Glass, K ; Cheng, AC ; McCaw, JM ; McVernon, J (CENTERS DISEASE CONTROL & PREVENTION, 2020-12)The ability of health systems to cope with coronavirus disease (COVID-19) cases is of major concern. In preparation, we used clinical pathway models to estimate healthcare requirements for COVID-19 patients in the context of broader public health measures in Australia. An age- and risk-stratified transmission model of COVID-19 demonstrated that an unmitigated epidemic would dramatically exceed the capacity of the health system of Australia over a prolonged period. Case isolation and contact quarantine alone are insufficient to constrain healthcare needs within feasible levels of expansion of health sector capacity. Overlaid social restrictions must be applied over the course of the epidemic to ensure systems do not become overwhelmed and essential health sector functions, including care of COVID-19 patients, can be maintained. Attention to the full pathway of clinical care is needed, along with ongoing strengthening of capacity.
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ItemInfluencing public health policy with data-informed mathematical models of infectious diseases: Recent developments and new challengesAlahmadi, A ; Belet, S ; Black, A ; Cromer, D ; Flegg, JA ; House, T ; Jayasundara, P ; Keith, JM ; McCaw, JM ; Moss, R ; Ross, J ; Shearer, FM ; Sai, TTT ; Walker, J ; White, L ; Whyte, JM ; Yan, AWC ; Zarebski, AE (ELSEVIER, 2020-09)Modern data and computational resources, coupled with algorithmic and theoretical advances to exploit these, allow disease dynamic models to be parameterised with increasing detail and accuracy. While this enhances models' usefulness in prediction and policy, major challenges remain. In particular, lack of identifiability of a model's parameters may limit the usefulness of the model. While lack of parameter identifiability may be resolved through incorporation into an inference procedure of prior knowledge, formulating such knowledge is often difficult. Furthermore, there are practical challenges associated with acquiring data of sufficient quantity and quality. Here, we discuss recent progress on these issues.
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ItemInfectious disease pandemic planning and response: Incorporating decision analysisShearer, FM ; Moss, R ; McVernon, J ; Ross, JV ; McCaw, JM (PUBLIC LIBRARY SCIENCE, 2020-01)Freya Shearer and co-authors discuss the use of decision analysis in planning for infectious disease pandemics.
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ItemEarly analysis of the Australian COVID-19 epidemicPrice, DJ ; Shearer, FM ; Meehan, MT ; McBryde, E ; Moss, R ; Golding, N ; Conway, EJ ; Dawson, P ; Cromer, D ; Wood, J ; Abbott, S ; McVernon, J ; McCaw, JM (eLIFE SCIENCES PUBL LTD, 2020-08-13)As of 1 May 2020, there had been 6808 confirmed cases of COVID-19 in Australia. Of these, 98 had died from the disease. The epidemic had been in decline since mid-March, with 308 cases confirmed nationally since 14 April. This suggests that the collective actions of the Australian public and government authorities in response to COVID-19 were sufficiently early and assiduous to avert a public health crisis - for now. Analysing factors that contribute to individual country experiences of COVID-19, such as the intensity and timing of public health interventions, will assist in the next stage of response planning globally. We describe how the epidemic and public health response unfolded in Australia up to 13 April. We estimate that the effective reproduction number was likely below one in each Australian state since mid-March and forecast that clinical demand would remain below capacity thresholds over the forecast period (from mid-to-late April).