School of BioSciences - Research Publications
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ItemWhat vaccination rate(s) minimize total societal costs after 'opening up' to COVID-19? Age-structured SIRM results for the Delta variant in Australia (New South Wales, Victoria and Western Australia).(Public Library of Science (PLoS), 2022)Using three age-structured, stochastic SIRM models, calibrated to Australian data post July 2021 with community transmission of the Delta variant, we projected possible public health outcomes (daily cases, hospitalisations, ICU beds, ventilators and fatalities) and economy costs for three states: New South Wales (NSW), Victoria (VIC) and Western Australia (WA). NSW and VIC have had on-going community transmission from July 2021 and were in 'lockdown' to suppress transmission. WA did not have on-going community transmission nor was it in lockdown at the model start date (October 11th 2021) but did maintain strict state border controls. We projected the public health outcomes and the economic costs of 'opening up' (relaxation of lockdowns in NSW and VIC or fully opening the state border for WA) at alternative vaccination rates (70%, 80% and 90%), compared peak patient demand for ICU beds and ventilators to staffed state-level bed capacity, and calculated a 'preferred' vaccination rate that minimizes societal costs and that varies by state. We found that the preferred vaccination rate for all states is at least 80% and that the preferred population vaccination rate is increasing with: (1) the effectiveness (infection, hospitalization and fatality) of the vaccine; (2) the lower is the daily lockdown cost; (3) the larger are the public health costs from COVID-19; (4) the higher is the rate of community transmission before opening up; and (5) the less effective are the public health measures after opening up.
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ItemConsidering health damages and co-benefits in climate change policy assessment.(Elsevier BV, 2022-09)
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ItemNo Preview AvailableIntegrated perspective on translating biophysical to economic impacts of climate change(NATURE PORTFOLIO, 2021-07)
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ItemEarly Decision Indicators for Foot-and-Mouth Disease Outbreaks in Non-Endemic Countries(Frontiers Media, 2016)This Research Topic presents valuable studies presenting different aspects and implementations of mathematical modeling for disease spread and control in the veterinary field.
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ItemComment 2 on 'Natural resource management' by Pannell, Doole and Cheung(WILEY-BLACKWELL, 2016-10)
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ItemOptimal surveillance against bioinvasions: a sample average approximation method applied to an agent-based spread model(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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ItemEquilibrium Modeling for Environmental Science: Exploring the Nexus of Economic Systems and Environmental Change(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.