Print PageIncreasing sophistication of population viability analysis has broadened our capacity to model population change while accounting for system complexity and uncertainty. Many emergent properties of population dynamics, such as the transmission and spread of disease, are however, still poorly coupled to demographic processes. We combined an individual-based demographic (Vortex) and epidemiological (Outbreak) model using a novel command-centre module (Meta-Model Manager) to predict the progression of bovine tuberculosis in introduced swamp buffalo in northern Australia.
Results/Conclusions
Disease patterns matched expectations derived from a previous broad-scale disease monitoring and culling programme. We also assessed the capacity to detect disease based on incrementing sentinel culling rates. We showed that even high monitoring effort (1000 culled sentinels) has a low (< 10 %) probability of detecting the disease, and current sampling is inadequate. Testing proportional and stepped culling rates revealed that up to 50 % of animals must be killed each year to reduce disease prevalence to near-eradication levels. Sensitivity analysis indicated that prevalence depended mainly on population demography (e.g., female age at primiparity) and the additional mortality induced by disease, with only minor contributions from epidemiological characteristics such as probability of transmission and encounter rate. This is a useful finding because the disease parameters are the least well-known. This case study shows that coupled multi-species demographic, epidemiological and other ecosystem-process models using command-centre modules provide immense potential to predict complex system dynamics under global change.
