School of BioSciences - Research Publications

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    Integrated perspective on translating biophysical to economic impacts of climate change
    Piontek, F ; Drouet, L ; Emmerling, J ; Kompas, T ; Mejean, A ; Otto, C ; Rising, JS ; Soergel, B ; Taconet, N ; Tavoni, M (NATURE PORTFOLIO, 2021-07)
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    Optimal surveillance against bioinvasions: a sample average approximation method applied to an agent-based spread model
    Hoa-Thi-Minh, N ; Pham, VH ; Kompas, T (WILEY, 2021-12)
    Trade-offs exist between the point of early detection and the future cost of controlling any invasive species. Finding optimal levels of early detection, with post-border active surveillance, where time, space and randomness are explicitly considered, is computationally challenging. We use a stochastic programming model to find the optimal level of surveillance and predict damages, easing the computational challenge by combining a sample average approximation (SAA) approach and parallel processing techniques. The model is applied to the case of Asian Papaya Fruit Fly (PFF), a highly destructive pest, in Queensland, Australia. To capture the non-linearity in PFF spread, we use an agent-based model (ABM), which is calibrated to a highly detailed land-use raster map (50 m × 50 m) and weather-related data, validated against a historical outbreak. The combination of SAA and ABM sets our work apart from the existing literature. Indeed, despite its increasing popularity as a powerful analytical tool, given its granularity and capability to model the system of interest adequately, the complexity of ABM limits its application in optimizing frameworks due to considerable uncertainty about solution quality. In this light, the use of SAA ensures quality in the optimal solution (with a measured optimality gap) while still being able to handle large-scale decision-making problems. With this combination, our application suggests that the optimal (economic) trap grid size for PFF in Queensland is ˜0.7 km, much smaller than the currently implemented level of 5 km. Although the current policy implies a much lower surveillance cost per year, compared with the $2.08 million under our optimal policy, the expected total cost of an outbreak is $23.92 million, much higher than the optimal policy of roughly $7.74 million.
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    Equilibrium Modeling for Environmental Science: Exploring the Nexus of Economic Systems and Environmental Change
    Cantele, M ; Bal, P ; Kompas, T ; Hadjikakou, M ; Wintle, B (AMER GEOPHYSICAL UNION, 2021-09)
    Abstract Equilibrium models (EMs) are frequently employed to examine the potential impacts of economic, energy, and trade policies as well as form the foundation of most integrated assessment models. Despite their central role coupling economic and environmental systems, environmental scientists are largely unfamiliar with the structure and methodology underpinning EMs, which serves as a barrier to interdisciplinary collaboration and model improvement. In this study we systematically extract data from 10 years of published EMs with a focus on how these models have been extended beyond their economic origins to encompass environmentally relevant sectors of interest. The results indicate that there is far greater spatial coverage of high income countries compared to low income countries, with notable gaps in Central America, Africa, the Middle East, and Central Asia. We also find a high degree of aggregation within production inputs and sectoral outputs, particularly within the context of global socioeconomic scenarios. For example, we were unable to identify a single temporally dynamic study that distinguished between products arising from managed versus natural forest, or pastures relative to natural grasslands. Due to the necessary breadth and associated knowledge gaps within a model of the entire global economy, we see considerable potential for cross‐disciplinary innovation as natural scientists gain familiarity into the role these models play in bridging the nexus between socioeconomic systems and environmental change.
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    Post-outbreak surveillance strategies to support proof of freedom from foot-and-mouth disease
    Bradhurst, R ; Garner, G ; East, I ; Death, C ; Dodd, A ; Kompas, T ( 2021-04-28)
    Abstract Whilst emergency vaccination may help contain foot-and-mouth disease in a previously FMD-free country, its use complicates post-outbreak surveillance and the recovery of FMD-free status. A structured surveillance program is required that can distinguish between vaccinated and residually infected animals, and provide statistical confidence that the virus is no longer circulating in previously infected areas. Epidemiological models have been well-used to investigate the potential benefits of emergency vaccination during a control progam and when/where/whom to vaccinate in the face of finite supplies of vaccine and personnel. Less well studied are post-outbreak issues such as the management of vaccinated animals and the implications of having used vaccination during surveillance regimes to support proof-of-freedom. This paper presents enhancements to the Australian Animal Disease Model (AADIS) that allow comparisons of different post-outbreak surveillance sampling regimes for establishing proof-of-freedom from FMD. A case study is provided that compares a baseline surveillance sampling regime (derived from current OIE guidelines), with an alternative less intensive sampling regime. It was found that when vaccination was not part of the control program, a reduced sampling intensity significantly reduced the number of samples collected and the cost of the post-outbreak surveillance program, without increasing the risk of missing residual infected herds.
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    Approaches for estimating benefits and costs of interventions in plant biosecurity across invasion phases
    Welsh, MJ ; Turner, JA ; Epanchin-Niell, RS ; Monge, JJ ; Soliman, T ; Robinson, AP ; Kean, JM ; Phillips, C ; Stringer, LD ; Vereijssen, J ; Liebhold, AM ; Kompas, T ; Ormsby, M ; Brockerhoff, EG (WILEY, 2021-07)
    Nonnative plant pests cause billions of dollars in damages. It is critical to prevent or reduce these losses by intervening at various stages of the invasion process, including pathway risk management (to prevent pest arrival), surveillance and eradication (to counter establishment), and management of established pests (to limit damages). Quantifying benefits and costs of these interventions is important to justify and prioritize investments and to inform biosecurity policy. However, approaches for these estimations differ in (1) the assumed relationship between supply, demand, and prices, and (2) the ability to assess different types of direct and indirect costs at invasion stages, for a given arrival or establishment probability. Here we review economic approaches available to estimate benefits and costs of biosecurity interventions to inform the appropriate selection of approaches. In doing so, we complement previous studies and reviews on estimates of damages from invasive species by considering the influence of economic and methodological assumptions. Cost accounting is suitable for rapid decisions, specific impacts, and simple methodological assumptions but fails to account for feedbacks, such as market adjustments, and may overestimate long-term economic impacts. Partial equilibrium models consider changes in consumer and producer surplus due to pest impacts or interventions and can account for feedbacks in affected sectors but require specialized economic models, comprehensive data sets, and estimates of commodity supply and demand curves. More intensive computable general equilibrium models can account for feedbacks across entire economies, including capital and labor, and linkages among these. The two major considerations in choosing an approach are (1) the goals of the analysis (e.g., consideration of a single pest or intervention with a limited range of impacts vs. multiple interventions, pests or sectors), and (2) the resources available for analysis such as knowledge, budget and time.
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    A Global MetaUniversity to Lead by Design to a Sustainable Well-Being Future
    Costanza, R ; Kubiszewski, I ; Kompas, T ; Sutton, PC (Frontiers, 2021-05-07)
    The COVID19 pandemic has revealed deep, ingrained problems with higher education, but also opportunities for positive transformation. In the post-COVID world, education at all levels has the chance to become: (1) universally available at low cost; (2) focused on developing competencies, (3) empowering fulfilling lives, not merely job training; and (4) engaged with communities to solve real-world problems. Achieving this will require overcoming the mass production model of higher education by utilizing the full potential of the Internet in creative ways balanced with face-to-face solutions-based integrated learning, research, and outreach agenda. Building a global collaborative consortium of universities and other educational institutions can move this agenda forward. We describe how this “MetaUniversity” could be structured and how it would serve to advance this agenda and lead the way to a sustainable well-being future for humanity and the rest of nature.
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    Estimating the true (population) infection rate for COVID-19: A Backcasting Approach with Monte Carlo Methods
    Phipps, S ; Grafton, Q ; Kompas, T ( 2020)

    ABSTRACT

    Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country overtime, make it difficult to estimate the true (population) infection rate based on the confirmed number of cases obtained through RNA viral testing. We applied a backcasting approach, coupled with Monte Carlo methods, to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 countries where reliable data are available. We find a positive relationship between the testing rate per 1,000 people and the implied true detection rate of COVID-19, and a negative relationship between the proportion who test positive and the implied true detection rate. Our estimates suggest that the true number of people infected across our sample of 15 developed countries is 18.2 (5-95% CI: 11.9-39.0) times greater than the reported number of cases. In individual countries, the true number of cases exceeds the reported figure by factors that range from 1.7 (5-95% CI: 1.1-3.6) for Australia to 35.6 (5-95% CI: 23.2-76.3) for Belgium.
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    Health and economic costs of early and delayed suppression and the unmitigated spread of COVID-19: The case of Australia
    Kompas, T ; Grafton, RQ ; Che, TN ; Chu, L ; Camac, J ; Devleesschauwer, B (PUBLIC LIBRARY SCIENCE, 2021-06-04)
    We compare the health and economic costs of early and delayed mandated suppression and the unmitigated spread of 'first-wave' COVID-19 infections in Australia in 2020. Using a fit-for-purpose SIQRM-compartment model for susceptible, infected, quarantined, recovered and mortalities on active cases, that we fitted from recorded data, a value of a statistical life year (VSLY) and an age-adjusted value of statistical life (A-VSL), we find that the economic costs of unmitigated suppression are multiples more than for early mandated suppression. We also find that using an equivalent VSLY welfare loss from fatalities to estimated GDP losses, drawn from survey data and our own estimates of the impact of suppression measures on the economy, means that for early suppression not to be the preferred strategy requires that Australia would have to incur more than 12,500-30,000 deaths, depending on the fatality rate with unmitigated spread, to the economy costs of early mandated suppression. We also find that early rather than delayed mandated suppression imposes much lower economy and health costs and conclude that in high-income countries, like Australia, a 'go early, go hard' strategy to suppress COVID-19 results in the lowest estimated public health and economy costs.
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    Rice land protection in a transitional economy: The case of Vietnam
    Long, C ; Hoa-Thi-Minh, N ; Kompas, T ; Khoi, D ; Trinh, B (ELSEVIER SCI LTD, 2021-04)
    Agricultural land protection (ALP) is a standard policy response to a desire for food security. However, ALP may result in a misallocation of resources. Examining rice land policy in Vietnam, we determine the optimal level of rice land protected against other crops using a stochastic optimization model built on top of a general equilibrium framework, combined with sequential micro-simulations on household data. We find that converting part of protected rice land enhances economic efficiency. Nonetheless, the policy is relatively pro-rich, implying a trade-off between poverty reduction and economic efficiency, making some households in already poor areas worse off. Our approach can be applied to land-use planning generally, highlighting the relevant tradeoffs and the search for needed optimal land-use policies.
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