arrival likelihood

Risk is divided into two categories: likelihood of an event occurring and the consequence once the event has occurred. In biosecurity, the likelihood of an event (i.e. a species invading Australia) can be further divided into the likelihood of arrival, establishment and spread with entry (arrival) and establishment being the two key components. CRC10001 has been using artificial neural networks (i.e. Self Organising Maps – SOMs) to estimate likelihood of establishment. However, this only addresses only one half of the entry/establishment likelihood equation.

The second half is the likelihood of entry and in an increasingly connected world, trade and trade paths are increasing exponentially. Ships that arrive into Australia may have visited multiple ports before arriving. These complex pathways present opportunities for pests and pathogens to arrive at Australia from indirect routes. For example, the Khapra beetle incursion in Western Australia in which this beetle was found in the personal effects of a family emigrating from Scotland. These personal effects had become contaminated when transferred into a shipping container that had originated in Pakistan. This highlights the fact that simply monitoring those pathways that directly link Australia to countries in which a pest or disease is found may not significantly reduce the likelihood of an incident.

Research outcomes:

Models developed in this project, which enable the analysis of complex shipping networks, provide a significant step forward in the risk profiling of incoming ships to Australian ports. These models enable the identification of pathways of greatest threat from invasive species as well as those Australian ports most likely to receive these invasive species.

Research implications:

These models could be incorporated into the current inspection protocols and enable further refinement and prioritisations for these procedures.

Acknowledgements:

Simon Barry, Peter Caley, Paul De Barro, Tom Harwood, Greg Hood, Rieks Van Klinken, Denys Yemshanov.