Surveillance and Management Optimisation: Maximising Efficiency
Scenario-based approaches allow decision-makers to simulate alternative surveillance and control strategies, optimising resource use and response effectiveness.
Improving Visibility
Surveillance priorities shift throughout an outbreak, requiring adaptable strategies to meet evolving needs.
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The Challenge of Sparse Observation
Surveillance is the generation of ground truth observations of pests and diseases, providing the essential data needed to inform decision-making and power predictive models. However, pest and disease outbreaks are dynamic and spatially heterogeneous, making comprehensive monitoring challenging.
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Surveillance Objectives Change Over Time
There are multiple surveillance objectives at different stages of an outbreak, from early detection to delimiting spread and ultimately confirming eradication. Each stage presents distinct challenges, requiring surveillance strategies that balance sensitivity, specificity, and operational constraints to ensure timely and accurate assessments.
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Optimising the Strategy
Our optimisation techniques account for the underlying uncertainty and complexity to ensure that surveillance efforts are both efficient and effective. By integrating epidemiological modelling, spatial analytics, and mathematical optimisation, we design adaptive surveillance strategies that maximise information gain while optimising resource allocation. This enables targeted deployment of detection methods, balancing cost, scale, and accuracy to deliver the most actionable insights at each stage of an outbreak.
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Towards Data Abundance
We continually identify opportunities where our cutting edge approaches to ML and remote sensing can unlock a step change in data generation, disrupting the limitations of established surveillance approaches.
Optimising Containment and Control
Harnessing predictive insights and scenario-based modelling, we empower stakeholders to design containment and control strategies that are both timely and effective.
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Exponential benefits
In exponential crises such as epidemics and pest outbreaks, the early implementation of effective control measures can lead to disproportionately large long-term benefits. However, stakeholders often lack the necessary visibility and predictive insights to design containment and control strategies that are both timely and effective.
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Exploring different futures
Our predictive models serve as powerful decision-support tools, enabling users to explore, simulate, and compare various control strategies under different conditions. By testing alternative scenarios, stakeholders can assess the potential outcomes of intervention strategies before committing resources.
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Better Tools, Better Decisions
Armed with these insights, decision-makers can evaluate trade-offs, assess uncertainties, and optimise their response strategies. This proactive approach leads to more informed, data-driven decisions that maximise the effectiveness of containment and control efforts while minimising unnecessary costs and risks.