Simulating bioterrorism through epidemiology approximation

Bioterrorism represents a significant threat to society. The lack of successful attacks that have resulted in true epidemics have created a need for data that can be generated from existing known factors. We have taken the popular susceptible-infected-recovery model and created a hybridized model that balances the simplicity of the original with an approximation of what more complex agent-based models already offer, with an emphasis on the exploration of large search spaces. Our experiments focus on more unconventional methods of intervention in the event of an epidemic, the results of which suggest a much more basic approach can be taken beyond the thoroughly explored realm of inoculation strategies.