School of BioSciences - Research Publications

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    Cost-benefit analysis of the yellow crazy ant eradication program. Technical Report prepared for the Wet Tropics Management Authority
    Spring, D ; Kompas, T ; Bradhurst, R (Centre of Excellence for Biosecurity Risk Analysis, 2019)
    Yellow crazy ants (Anoplolepis gracilipes) (YCA) are one of the world’s 100 worst invasive species (Lowe et al. 2000). Previous assessments of YCA invasions have demonstrated that YCA can dramatically reduce native species richness in invaded areas, including in the Seychelles (Bos et al. 2008), Christmas Island (O'Dowd et al. 2003), and Hawaii (Plentovich et al. 2011). Native species losses include direct losses of competing invertebrate species and indirect losses resulting from ecological interdependencies, which can result in “ecological meltdown” in extreme cases such as Christmas Island (O'Dowd et al. 2003). YCA can also cause large losses to people living in infested areas through nuisance and health effects (Lach and Hoskin 2015) and can also adversely affect agricultural producers (Young et al. 2001) through reducing yields and/or increasing pesticide costs. YCA was first detected in Cairns and its southern suburbs in 2001, and an eradication program was initiated by the Department of Natural Resources and Mines (DNRM) and Biosecurity Queensland as part of a larger state-wide program. Later discoveries of YCA across the state, including in and around the WTWHA led to the state-wide eradication program being discontinued. An application was then made by WTMA to continue eradication efforts in and around the WTWHA. The program has been funded by the Australian Government and the Queensland Government in two overlapping projects, as described in the Executive Summary.
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    Vector-borne spread of Animal Disease (CEBRA Project 1608B). Technical Report for the Department of Agriculture, Water and Environment
    Bradhurst, R ; Garner, G ; East, I ; Iglesias, R ; Stevenson, M ; AL-RIYAMI, S ; Kompas, T (University of Melbourne, 2018)
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    Reconstructing foot-and-mouth disease outbreaks: a methods comparison of transmission network models
    Firestone, SM ; Hayama, Y ; Bradhurst, R ; Yamamoto, T ; Tsutsui, T ; Stevenson, MA (NATURE PORTFOLIO, 2019-03-18)
    A number of transmission network models are available that combine genomic and epidemiological data to reconstruct networks of who infected whom during infectious disease outbreaks. For such models to reliably inform decision-making they must be transparently validated, robust, and capable of producing accurate predictions within the short data collection and inference timeframes typical of outbreak responses. A lack of transparent multi-model comparisons reduces confidence in the accuracy of transmission network model outputs, negatively impacting on their more widespread use as decision-support tools. We undertook a formal comparison of the performance of nine published transmission network models based on a set of foot-and-mouth disease outbreaks simulated in a previously free country, with corresponding simulated phylogenies and genomic samples from animals on infected premises. Of the transmission network models tested, Lau's systematic Bayesian integration framework was found to be the most accurate for inferring the transmission network and timing of exposures, correctly identifying the source of 73% of the infected premises (with 91% accuracy for sources with model support >0.80). The Structured COalescent Transmission Tree Inference provided the most accurate inference of molecular clock rates. This validation study points to which models might be reliably used to reconstruct similar future outbreaks and how to interpret the outputs to inform control. Further research could involve extending the best-performing models to explicitly represent within-host diversity so they can handle next-generation sequencing data, incorporating additional animal and farm-level covariates and combining predictions using Ensemble methods and other approaches.
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    Does Size Matter to Models? Exploring the Effect of Herd Size on Outputs of a Herd-Level Disease Spread Simulator
    Van Andel, M ; Hollings, T ; Bradhurst, R ; Robinson, A ; Burgman, M ; Gates, MC ; Bingham, P ; Carpenter, T (FRONTIERS MEDIA SA, 2018-05-04)
    Disease spread modeling is widely used by veterinary authorities to predict the impact of emergency animal disease outbreaks in livestock and to evaluate the cost-effectiveness of different management interventions. Such models require knowledge of basic disease epidemiology as well as information about the population of animals at risk. Essential demographic information includes the production system, animal numbers, and their spatial locations yet many countries with significant livestock industries do not have publically available and accurate animal population information at the farm level that can be used in these models. The impact of inaccuracies in data on model outputs and the decisions based on these outputs is seldom discussed. In this analysis, we used the Australian Animal Disease model to simulate the spread of foot-and-mouth disease seeded into high-risk herds in six different farming regions in New Zealand. We used three different susceptible animal population datasets: (1) a gold standard dataset comprising known herd sizes, (2) a dataset where herd size was simulated from a beta-pert distribution for each herd production type, and (3) a dataset where herd size was simplified to the median herd size for each herd production type. We analyzed the model outputs to compare (i) the extent of disease spread, (ii) the length of the outbreaks, and (iii) the possible impacts on decisions made for simulated outbreaks in different regions. Model outputs using the different datasets showed statistically significant differences, which could have serious implications for decision making by a competent authority. Outbreak duration, number of infected properties, and vaccine doses used during the outbreak were all significantly smaller for the gold standard dataset when compared with the median herd size dataset. Initial outbreak location and disease control strategy also significantly influenced the duration of the outbreak and number of infected premises. The study findings demonstrate the importance of having accurate national-level population datasets to ensure effective decisions are made before and during disease outbreaks, reducing the damage and cost.
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    Management strategies for vaccinated animals after an outbreak of foot-and-mouth disease and the impact on return to trade
    Bradhurst, R ; Garner, G ; East, I ; Death, C ; Dodd, A ; Kompas, T ; Parida, S (PUBLIC LIBRARY SCIENCE, 2019-10-11)
    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. Two case studies are provided that compare the retention of vaccinated animals with removal for waste/salvage, and the impact on recovery of FMD-sensitive markets per OIE guidelines. It was found that a vaccinate-and-retain strategy was associated with lower post-outbreak management costs, however this advantage was outweighed by significantly higher trade losses. Under the assumptions of the study there was no cost advantage to salvaging the removed vaccinated animals.