Characterizing Biological Events
Defining and communicating the complexity of biological threats
The preparation for and response to biological events is complicated by the fact that variation between the events — from type of transmission to the types of medical countermeasures available to how quickly origin can be determined — can dramatically alter the requirements for planning and the resources necessary for an effective response.
To define and communicate the complexity inherent in the biological threat space, we have identified 12 major response-relevant dimensions across which biological outbreaks or deliberate release events can be characterized. These include:
- Origin (natural or intentional)
- Type (animal only, human only, or zoonotic disease)
- Means of spread (communicable or non-communicable)
- Route of transmission (airborne, bloodborne, waterborne, foodborne, or vector-borne)
- Diagnostics (point of care and biosafety levels 1, 2, 3, and 4)
- Medical countermeasures (antivirals, antibiotics, vaccine, post-exposure prophylaxis, or none)
- Outbreak location (accessible to international community or not and whether conditions are non-permissive owing to conflict or other instability)
- Affected populations (all, pregnant women, children, elderly, or targeted attack)
- Applicable personal protective equipment (respirator, containment suit, mask, gloves, and gown)
- Morbidity (graded at five levels from very low to very high)
- Response level (local, intermediate, national, regional, or global)
- Policy measures in place (national, international, or none)
We generated a complete set of combinatorial scenarios using these characteristics with a randomisation script. The randomised combinatorial yielded 34 million potential event scenarios. We then applied a system-level review of the scenarios to exclude those that were not biologically rational or plausible. For example, targeted attacks were eliminated for a natural outbreak and a non-communicable means of spread was eliminated for vector-borne diseases. With the non-rational combinations excluded based on a parameter-by-parameter comparison, we were left with approximately 22 million combinations (further details on the methodology can be found here).
We inputted the combinatorial results into a static database and created a visualization tool using interactive graphics. This tool and the scenarios provide a method to define exercise scenarios and drive discussions for practitioners, decision-makers, and educators. It is also significant in that it provides a framework around which to test and evaluate planning and exercise efforts. The tool also offers a method to assess the response characteristics of biological outbreaks and support stakeholders in developing a better understanding of the challenge of effectively planning for and responding to biological outbreaks, regardless of origin.
Acknowledgements: This work was partly funded by the Open Philanthropy Project grant to Georgetown University Center for Global Health Science and Security.