Publications by authors named "Tom Kompas"

Climate change has direct impacts on current and future agricultural productivity. Statistical meta-analysis models can be used to generate expectations of crop yield responses to climatic factors by pooling data from controlled experiments. However, methodological challenges in performing these meta-analyses, together with combined uncertainty from various sources, make it difficult to validate model results.

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Objective: To estimate the number of people in Australia with long COVID by age group, and the associated medium term productivity and economic losses.

Study Design: Modelling study: a susceptible-exposed-infected-recovered (SEIR) model to estimate the number of people with long COVID over time following single infections, and a labour supply model to estimate productivity losses as a proportion of gross domestic product (GDP).

Setting: Australia, 2022-2024.

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In contrast to most integrated assessment models, with limited transparency on damage functions and recursive temporal dynamics, we use a unique large-dimensional computational global climate and trade model, GTAP-DynW, to directly project the possible intertemporal impacts of water and heat stress on global food supply and food security to 2050. The GTAP-DynW model uses GTAP production and trade data for 141 countries and regions, with varying water and heat stress baselines, and results are aggregated into 30 countries/regions and 30 commodity sectors. Blue water stress projections are drawn from WRI source material and a GTAP-Water database to incorporate dynamic changes in water resources and their availability in agricultural production and international trade, thus providing a more general measure for severe food insecurity from water and heat stress damages with global warming.

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This paper proposes a surveillance model for plant pests that can optimally allocate resources among survey tools with varying properties. While some survey tools are highly specific for the detection of a single pest species, others are more generalized. There is considerable variation in the cost and sensitivity of these tools, but there are no guidelines or frameworks for identifying which tools are most cost-effective when used in surveillance programs that target the detection of newly invaded populations.

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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.

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Foot-and-mouth disease (FMD) affects cloven-hoofed livestock and causes devastating damages to the world's economies. Being endemic in developing countries, FMD has imposed a significant threat to the FMD-freedom status in developed countries. The globally-concerted effort to eradicate FMD at its source has faced a substantial challenge of having little knowledge about how FMD spreads in developing countries.

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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.

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Background: We investigated the public health and economy outcomes of different levels of social distancing to control a 'second wave' outbreak in Australia and identify implications for public health management of COVID-19.

Methods: Individual-based and compartment models were used to simulate the effects of different social distancing and detection strategies on Australian COVID-19 infections and the economy from March to July 2020. These models were used to evaluate the effects of different social distancing levels and the early relaxation of suppression measures, in terms of public health and economy outcomes.

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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.

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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.

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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.

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Climate change threatens biodiversity directly by influencing biophysical variables that drive species' geographic distributions and indirectly through socio-economic changes that influence land use patterns, driven by global consumption, production and climate. To date, no detailed analyses have been produced that assess the relative importance of, or interaction between, these direct and indirect climate change impacts on biodiversity at large scales. Here, we apply a new integrated modelling framework to quantify the relative influence of biophysical and socio-economically mediated impacts on avian species in Vietnam and Australia and we find that socio-economically mediated impacts on suitable ranges are largely outweighed by biophysical impacts.

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Differences in COVID-19 testing and tracing across countries, as well as changes in testing within each country over time, 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 to estimate a distribution for the true (population) cumulative number of infections (infected and recovered) for 15 developed countries. Our sample comprised countries with similar levels of medical care and with populations that have similar age distributions.

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Decisions surrounding the presence of infectious diseases are typically made in the face of considerable uncertainty. However, the development of models to guide these decisions has been substantially constrained by computational difficulty. This paper focuses on the case of finding the optimal level of surveillance against a highly infectious animal disease where time, space and randomness are fully considered.

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An incursion of Foot-and-mouth disease (FMD) in a previously FMD-free country can cause significant economic damage from immediate and prolonged closure of FMD-sensitive markets. Whilst emergency vaccination may help contain disease, the presence of vaccinated animals complicates post-outbreak management and the recovery of FMD-free status for return to trade. We present enhancements to the Australian Animal DISease (AADIS) model that allow comparisons of post-outbreak management strategies for vaccinated animals, for the purposes of securing the earliest possible return to trade.

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Accurate delimitation of the geographic range of a species is important for control of biological invasions, conservation of threatened species, and understanding species range dynamics under environmental change. However, estimating range boundaries is challenging because monitoring methods are imperfect, the area that might contain individuals is often incompletely surveyed, and species may have patchy distributions. In these circumstances, large areas can be surveyed without finding individuals despite occupancy extending beyond surveyed areas, resulting in underestimation of range limits.

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When freshwater resources become scarce there is a trade-off between human resource demands and environmental sustainability. The cost of conserving freshwater ecosystems can potentially be reduced by implementing institutional reforms that endow environmental water managers with a permanent water entitlement and the capacity to store, trade and release water. Australia's Murray Darling Basin Plan (MDBP) includes one of the world's most ambitious programs to recover water for the environment, supported by institutional reforms that allow environmental water managers to operate in water markets.

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Disease managers face many challenges when deciding on the most effective control strategy to manage an outbreak of foot-and-mouth disease (FMD). Decisions have to be made under conditions of uncertainty and where the situation is continually evolving. In addition, resources for control are often limited.

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The Asia-Pacific region, the largest and fastest growing liquefied natural gas (LNG) market in the world, has been undergoing radical changes over the past few years. These changes include considerable additional supplies from North America and Australia, and a recent LNG price slump resulting from an oil-linked pricing mechanism and demand uncertainties. This paper develops an Asia-Pacific Gas Model (APGM), based on a structural, stochastic and optimising framework, providing a valuable tool for the projection of LNG trade in the Asia-Pacific region.

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Background: Although tuberculosis is a major cause of morbidity and mortality worldwide, available funding falls far short of that required for effective control. Economic and spillover consequences of investments in the treatment of tuberculosis are unclear, particularly when steep gradients in the disease and response are linked by population movements, such as that between Papua New Guinea (PNG) and the Australian cross-border region.

Objective: To undertake an economic evaluation of Australian support for the expansion of basic Directly Observed Treatment, Short Course in the PNG border area of the South Fly from the current level of 14% coverage.

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To help manage the fluctuations inherent in fish populations scientists have argued for both an ecosystem approach to management and the greater use of marine reserves. Support for reserves includes empirical evidence that they can raise the spawning biomass and mean size of exploited populations, increase the abundance of species and, relative to reference sites, raise population density, biomass, fish size and diversity. By contrast, fishers often oppose the establishment and expansion of marine reserves and claim that reserves provide few, if any, economic payoffs.

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