School of BioSciences - Research Publications
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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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ItemNo Preview AvailablePost-outbreak surveillance strategies to support proof of freedom from foot-and-mouth disease( 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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ItemA generalised and scalable framework for modelling incursions, surveillance and control of plant and environmental pests(Elsevier BV, 2021-05)Invasive plant and environmental pests can seriously impact environment, economy, health and amenity. It is challenging to form response policies given the diversity of pest species; complex spatiotemporal interplay between arrival, spread, surveillance, and control; and limited field data when pests are rare/absent. Models can provide useful decision support through the exploration of incursion pathways and comparison of surveillance and control strategies. However, increased use of quantitative models to inform pest management requires adaptable modelling frameworks. The new Australian Priority Pest and Disease modelling framework (APPDIS) allows pest models to be constructed through user configuration choices for a broad range of different pest types. Pest populations may be defined as point incursions, established populations, or estimated mechanistically from environmental criteria. Spread occurs at multiple scales, through either simple mathematical kernels, or more complex spatial pathways, depending on data availability and pest type. Useful experiments can be conducted on general surveillance, specific surveillance, and treatment regimes. Control activities are dynamically resource-constrained and costed for relative comparisons in terms of benefit and cost. A case study on a tramp ant incursion is provided for illustrative purposes.
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ItemManagement strategies for vaccinated animals after an outbreak of foot-and-mouth disease and the impact on return to trade(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.
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ItemEarly Decision Indicators for Foot-and-Mouth Disease Outbreaks in Non-Endemic Countries(FRONTIERS MEDIA SA, 2016)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. A modeling study was carried out to identify characteristics measurable during the early phase of a FMD outbreak that might be useful as predictors of the total number of infected places, outbreak duration, and the total area under control (AUC). The study involved two modeling platforms in two countries (Australia and New Zealand) and encompassed a large number of incursion scenarios. Linear regression, classification and regression tree, and boosted regression tree analyses were used to quantify the predictive value of a set of parameters on three outcome variables of interest: the total number of infected places, outbreak duration, and the total AUC. The number of infected premises (IPs), number of pending culls, AUC, estimated dissemination ratio, and cattle density around the index herd at days 7, 14, and 21 following first detection were associated with each of the outcome variables. Regression models for the size of the AUC had the highest predictive value (R2 = 0.51-0.9) followed by the number of IPs (R2 = 0.3-0.75) and outbreak duration (R2 = 0.28-0.57). Predictability improved at later time points in the outbreak. Predictive regression models using various cut-points at day 14 to define small and large outbreaks had positive predictive values of 0.85-0.98 and negative predictive values of 0.52-0.91, with 79-97% of outbreaks correctly classified. On the strict assumption that each of the simulation models used in this study provide a realistic indication of the spread of FMD in animal populations. Our conclusion is that relatively simple metrics available early in a control program can be used to indicate the likely magnitude of an FMD outbreak under Australian and New Zealand conditions.