School of Mathematics and Statistics - Research Publications

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    From Climate Change to Pandemics: Decision Science Can Help Scientists Have Impact
    Baker, CM ; Campbell, PT ; Chades, I ; Dean, AJ ; Hester, SM ; Holden, MH ; McCaw, JM ; McVernon, J ; Moss, R ; Shearer, FM ; Possingham, HP (FRONTIERS MEDIA SA, 2022-02-14)
    Scientific knowledge and advances are a cornerstone of modern society. They improve our understanding of the world we live in and help us navigate global challenges including emerging infectious diseases, climate change and the biodiversity crisis. However, there is a perpetual challenge in translating scientific insight into policy. Many articles explain how to better bridge the gap through improved communication and engagement, but we believe that communication and engagement are only one part of the puzzle. There is a fundamental tension between science and policy because scientific endeavors are rightfully grounded in discovery, but policymakers formulate problems in terms of objectives, actions and outcomes. Decision science provides a solution by framing scientific questions in a way that is beneficial to policy development, facilitating scientists’ contribution to public discussion and policy. At its core, decision science is a field that aims to pinpoint evidence-based management strategies by focussing on those objectives, actions, and outcomes defined through the policy process. The importance of scientific discovery here is in linking actions to outcomes, helping decision-makers determine which actions best meet their objectives. In this paper we explain how problems can be formulated through the structured decision-making process. We give our vision for what decision science may grow to be, describing current gaps in methodology and application. By better understanding and engaging with the decision-making processes, scientists can have greater impact and make stronger contributions to important societal problems.
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    Development 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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    Modelling the impact of COVID-19 in Australia to inform transmission reducing measures and health system preparedness
    Moss, R ; Wood, J ; Brown, D ; Shearer, F ; Black, AJ ; Cheng, AC ; McCaw, JM ; McVernon, J ( 2020-04-11)

    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
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    Constructing an ethical framework for priority allocation of pandemic vaccines
    Fielding, J ; Sullivan, SG ; Beard, F ; Macartney, K ; Williams, J ; Dawson, A ; Gilbert, GL ; Massey, P ; Crooks, K ; Moss, R ; McCaw, JM ; McVernon, J (ELSEVIER SCI LTD, 2021-01-21)
    BACKGROUND: Allocation of scarce resources during a pandemic extends to the allocation of vaccines when they eventually become available. We describe a framework for priority vaccine allocation that employed a cross-disciplinary approach, guided by ethical considerations and informed by local risk assessment. METHODS: Published and grey literature was reviewed, and augmented by consultation with key informants, to collate past experience, existing guidelines and emerging strategies for pandemic vaccine deployment. Identified ethical issues and decision-making processes were also included. Concurrently, simulation modelling studies estimated the likely impacts of alternative vaccine allocation approaches. Assembled evidence was presented to a workshop of national experts in pandemic preparedness, vaccine strategy, implementation and ethics. All of this evidence was then used to generate a proposed ethical framework for vaccine priorities best suited to the Australian context. FINDINGS: Published and emerging guidance for priority pandemic vaccine distribution differed widely with respect to strategic objectives, specification of target groups, and explicit discussion of ethical considerations and decision-making processes. Flexibility in response was universally emphasised, informed by real-time assessment of the pandemic impact level, and identification of disproportionately affected groups. Model outputs aided identification of vaccine approaches most likely to achieve overarching goals in pandemics of varying transmissibility and severity. Pandemic response aims deemed most relevant for an Australian framework were: creating and maintaining trust, promoting equity, and reducing harmful outcomes. INTERPRETATION: Defining clear and ethically-defendable objectives for pandemic response in context aids development of flexible and adaptive decision support frameworks and facilitates clear communication and engagement activities.
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    Coronavirus Disease Model to Inform Transmission -Reducing Measures and Health System Preparedness, Australia
    Moss, R ; Wood, J ; Brown, D ; Shearer, FM ; Black, AJ ; Glass, K ; Cheng, AC ; McCaw, JM ; McVernon, J (CENTERS DISEASE CONTROL & PREVENTION, 2020-12-01)
    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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    Infectious disease pandemic planning and response: Incorporating decision analysis
    Shearer, FM ; Moss, R ; McVernon, J ; Ross, JV ; McCaw, JM (PUBLIC LIBRARY SCIENCE, 2020-01-01)
    Freya Shearer and co-authors discuss the use of decision analysis in planning for infectious disease pandemics.
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    Early analysis of the Australian COVID-19 epidemic
    Price, 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).
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    Diagnosis and Antiviral Intervention Strategies for Mitigating an Influenza Epidemic
    Moss, R ; McCaw, JM ; McVernon, J ; Davis, CT (PUBLIC LIBRARY SCIENCE, 2011-02-04)
    BACKGROUND: Many countries have amassed antiviral stockpiles for pandemic preparedness. Despite extensive trial data and modelling studies, it remains unclear how to make optimal use of antiviral stockpiles within the constraints of healthcare infrastructure. Modelling studies informed recommendations for liberal antiviral distribution in the pandemic phase, primarily to prevent infection, but failed to account for logistical constraints clearly evident during the 2009 H1N1 outbreaks. Here we identify optimal delivery strategies for antiviral interventions accounting for logistical constraints, and so determine how to improve a strategy's impact. METHODS AND FINDINGS: We extend an existing SEIR model to incorporate finite diagnostic and antiviral distribution capacities. We evaluate the impact of using different diagnostic strategies to decide to whom antivirals are delivered. We then determine what additional capacity is required to achieve optimal impact. We identify the importance of sensitive and specific case ascertainment in the early phase of a pandemic response, when the proportion of false-positive presentations may be high. Once a substantial percentage of ILI presentations are caused by the pandemic strain, identification of cases for treatment on syndromic grounds alone results in a greater potential impact than a laboratory-dependent strategy. Our findings reinforce the need for a decentralised system capable of providing timely prophylaxis. CONCLUSIONS: We address specific real-world issues that must be considered in order to improve pandemic preparedness policy in a practical and methodologically sound way. Provision of antivirals on the scale proposed for an effective response is infeasible using traditional public health outbreak management and contact tracing approaches. The results indicate to change the transmission dynamics of an influenza epidemic with an antiviral intervention, a decentralised system is required for contact identification and prophylaxis delivery, utilising a range of existing services and infrastructure in a "whole of society" response.
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    Likely effectiveness of pharmaceutical and non-pharmaceutical interventions for mitigating influenza virus transmission in Mongolia
    Bolton, KJ ; McCaw, JM ; Moss, R ; Morris, RS ; Wang, S ; Burma, A ; Darma, B ; Narangerel, D ; Nymadawa, P ; McVernon, J (WORLD HEALTH ORGANIZATION, 2012-04-01)
    OBJECTIVE: To assess the likely benefit of the interventions under consideration for use in Mongolia during future influenza pandemics. METHODS: A stochastic, compartmental patch model of susceptibility, exposure, infection and recovery was constructed to capture the key effects of several interventions--travel restrictions, school closure, generalized social distancing, quarantining of close contacts, treatment of cases with antivirals and prophylaxis of contacts--on the dynamics of influenza epidemics. The likely benefit and optimal timing and duration of each of these interventions were assessed using Latin-hypercube sampling techniques, averaging across many possible transmission and social mixing parameters. FINDINGS: Timely interventions could substantially alter the time-course and reduce the severity of pandemic influenza in Mongolia. In a moderate pandemic scenario, early social distancing measures decreased the mean attack rate from around 10% to 7-8%. Similarly, in a severe pandemic scenario such measures cut the mean attack rate from approximately 23% to 21%. In both moderate and severe pandemic scenarios, a suite of non-pharmaceutical interventions proved as effective as the targeted use of antivirals. Targeted antiviral campaigns generally appeared more effective in severe pandemic scenarios than in moderate pandemic scenarios. CONCLUSION: A mathematical model of pandemic influenza transmission in Mongolia indicated that, to be successful, interventions to prevent transmission must be triggered when the first cases are detected in border regions. If social distancing measures are introduced at this stage and implemented over several weeks, they may have a notable mitigating impact. In low-income regions such as Mongolia, social distancing may be more effective than the large-scale use of antivirals.
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    Reducing disease burden in an influenza pandemic by targeted delivery of neuraminidase inhibitors: mathematical models in the Australian context
    Moss, R ; McCaw, JM ; Cheng, AC ; Hurt, AC ; McVernon, J (BMC, 2016-10-10)
    BACKGROUND: Many nations maintain stockpiles of neuraminidase inhibitor (NAI) antiviral agents for use in influenza pandemics to reduce transmission and mitigate the course of clinical infection. Pandemic preparedness plans include the use of these stockpiles to deliver proportionate responses, informed by emerging evidence of clinical impact. Recent uncertainty about the effectiveness of NAIs has prompted these nations to reconsider the role of NAIs in pandemic response, with implications for pandemic planning and for NAI stockpile size. METHODS: We combined a dynamic model of influenza epidemiology with a model of the clinical care pathways in the Australian health care system to identify effective NAI strategies for reducing morbidity and mortality in pandemic events, and the stockpile requirements for these strategies. The models were informed by a 2015 assessment of NAI effectiveness against susceptibility, pathogenicity, and transmission of influenza. RESULTS: Liberal distribution of NAIs for early treatment in outpatient settings yielded the greatest benefits in all of the considered scenarios. Restriction of community-based treatment to risk groups was effective in those groups, but failed to prevent the large proportion of cases arising from lower risk individuals who comprise the majority of the population. CONCLUSIONS: These targeted strategies are only effective if they can be deployed within the constraints of existing health care infrastructure. This finding highlights the critical importance of identifying optimal models of care delivery for effective emergency health care response.