Roadmap for development of disease control strategies for bTB

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Mathematical models

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Mathematical models

Research Question

What are we trying to achieve and why? What is the problem we are trying to solve?

Develop mathematical models to simulate the local TB epidemic, to better understand risk factors, longitudinal disease trends and predictions.
Can models be developed to test and cost various interventions?

What are the scientific and technological challenges (knowledge gaps needing to be addressed)?

To investigate risk factors that models are sensitive to.
To investigate cattle-only, wildlife-only, and integrated epi-systems.
To understand the distribution of TB cases by herd – often over-dispersed in surveillance data.
To understand the connectivity of cattle herds and the animal networks over which TB spreads.
To estimate the relative role of cattle movements and local wildlife in spillover/spillback events.
To model the implementation of various interventions
To model the cost-benefit of various interventions.
Accessing national databases of animal-level identification, pedigree, test history and movement data.
Integrating such data with geographical information in compliance with GDPR.
Access to data specialists: data analytics, network analysts, veterinary epidemiology, quantitative genetics etc.
Challenge to obtain accurate parameter estimates from experimental models or field data.

What approaches could/should be taken to address the research question?

Different models required for different analyses, to investigate different questions; for example, agent-based models may be used to simulate transmission of virtual epidemics from estimated variable parameters.
Depending on the reliability of input variables, models are potentially a very powerful means to investigate aspects of TB epidemiology and control intervention options/costs.