Biology subjects

Theng, M.

Publications and source records attributed to Theng, M..

4 recordsLinked to original sources

bioRxiv2026

Forecasting high pathogenicity avian influenza with a stochastic mechanistic model: performance and lessons for Australia

High pathogenicity avian influenza (HPAI) H5N1 clade 2.3.4.4b has caused a global panzootic with unprecedented impacts on wildlife and livestock, making evidence-based disease mitigation and outbreak response critical. In this paper, we describe a spatiotemporal mechanistic model of infectious disease dynamics developed for the HPAI Modelling Challenge and its implications for forecasting and policy in Australia. To emulate emergency response conditions, we adapted an existing model for rapid deployment rather than developing a bespoke model. We refined the model iteratively across the challenge to better analyse the provided outbreak data. Throughout the challenge, we accurately forecast temporal trends and local outbreak spread, but could not predict rarer, long-distance dispersal events. The challenge ended before HPAI H5N1 was first detected in Australia (June 2026), providing a critical opportunity to test our response modelling readiness for an incursion in wildlife and potential spillover into commercial poultry. Our experience identifies three key considerations for Australia's HPAI H5N1 preparedness: targeted enhancements to our model to improve forecast precision and enable scenario-based policy evaluation; the critical value of pre-existing modelling infrastructure for rapid emergency response; and sustained collaboration between research and policy institutions to align modelling capabilities with outbreak response requirements.

bioinformatics↗

bioRxiv2025

Estimating the impact of invasive pests and diseases on ecosystem services: modelling carbon sequestration loss due to myrtle rust (Austropuccinia psidii exotic strains) in Australia

The impacts of invasive pests and diseases are routinely estimated and measured in the context of agriculture, but less so in the context of biodiversity and ecosystem services. In this study, we estimate the potential reduction of carbon sequestration in Australia due to exotic strains of myrtle rust (Austropuccinia psidii, also known as Puccinia psidii, guava rust, or [o]hia rust). We model the contribution of susceptible plants to carbon sequestration and use previously known myrtle rust damage estimates to susceptible plant species and the valuation of carbon sequestration in Australia to estimate the potential monetary impact. This method can be systematically extended to other pests impacting plant growth as well as other ecosystem services. In the case of myrtle rust, we estimate that it could cause up to a 1.6% (95% CI: 1.3-2.0%) annual reduction in national carbon sequestration if it were to spread across all climatically suitable areas in Australia, resulting in an estimated value loss of over $340 million AUD (over $220 million USD) per year. Compared with contemporary syntheses of known cost estimates, our results show that the potential consequences of invasive species can be substantially larger than reported, and may be currently undervalued. Our work shows the need to systematically compile the potential impacts and costs to the environment and ecosystem services globally, to support both biosecurity decision-making and climate-change related initiatives such as net-zero emissions targets and reforestation efforts.

ecology↗

bioRxiv2024

A real-time forecasting framework for emerging infectious diseases affecting animal populations

Infectious disease forecasting has become increasingly important in public health, as demonstrated during the COVID-19 pandemic. However, forecasting tools for emergency animal diseases, particularly those offering real-time decision support when parameters governing disease dynamics are unknown, remain limited. We introduce a generalised modelling framework for near-real-time forecasting of the temporal and spatial spread of infectious livestock diseases using data from the early stages of an outbreak. We applied the framework to the 2007 equine influenza outbreak in Australia, generating prediction targets at three timepoints across four regional clusters. Our targets included future daily case counts, outbreak size, peak timing and duration, and spatial distributions of future spread. We evaluated how well the forecasts predicted daily cases and the spatial distribution of case counts, using skill scores as a benchmark for future model improvements. Forecast accuracy, certainty, and skill improved significantly after the outbreaks peak, while early predictions were more variable, suggesting that pre-peak forecasts should be interpreted with caution. Spatial forecasts maintained positive skill throughout the outbreak, supporting their use in guiding response priorities. This framework provides a tool for real-time decision-making during livestock disease outbreaks and establishes a foundation for future refinements and applications to other animal diseases.

bioinformatics↗

bioRxiv2021

The integrated role of resource memory and scent-mediated territoriality in the emergence of home-ranges

Despite decades of animal movement research, an integrated understanding of the processes underlying the emergence of home-ranges remains inadequate. We explored the effects of integrating two key processes of home-ranging arising from individual movement decisions: (i) memory-based resource use; and (ii) scent-based territoriality. Both mechanisms together led to the formation of exclusive, resource- and population density-dependent home-ranges, which were responsive to perturbations in the conspecific environment (i.e., removing individuals). Home-range patterns (size, size skewness and overlap) were primarily influenced by memory and scent decay rate parameters, demonstrating that home-ranging is ultimately a balance between an animals inherent exploratory tendency and its desire to avoid conspecifics. Model application to a population of feral cats demonstrated that general space use patterns could be approximated through simulation, and replication of finer-scale space use patterns is plausible with further model development. Our modelling framework provides a foundation for sophisticated theoretical models of space use in interacting animals.

ecology↗