The complexity of biological events
Authors: Rebecca Katz, Ellie Graeden, Justin Kerr
Journal: The Lancet Global Health (2018)

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. This complexity is multiplied when the biological event is deliberate or suspected of being deliberately caused. Over the past 20 years, understanding of biological threats has gradually increased, as have the resources devoted to addressing them. Much of the planning, however, has been for a discrete set of biological agents. Partly in response to specific threats, but also due to the demand to focus thinking and resources, the US Government and others around the world have developed lists of particularly worrisome diseases (such as the Centers for Disease Control and Prevention's category A, B, and C lists).1Centers for Disease Control and Prevention, Bioterrorism agents/disease. https://emergency.cdc.gov/agent/agentlist-category.asp (accessed Oct 26, 2017).Google Scholar, 2National Institutes of Health, National Institute of Allergy and Infectious Diseases, NIAID emerging infectious diseases/pathogens. https://www.niaid.nih.gov/research/emerging-infectious-diseases-pathogens (accessed Oct 26, 2017).Google Scholar On the basis of these lists, a multitude of disease-specific preparedness and response plans have been developed for both naturally occurring and deliberate events, such as the US Department of Homeland Security's guidance on specific response aspects following exposure to anthrax.3US Department of Homeland Security Guidance for protecting responders' health during the first week following a wide-area aerosol anthrax attack. September, 2012https://www.dhs.gov/sites/default/files/publications/Guidance%20for%20Protecting%20Responders%27%20Health%20-%20October%202012_0_0.pdfGoogle Scholar Disease-specific lists are guiding the research and development of medical countermeasures, including the new Coalition for Epidemic Preparedness Innovation, which has developed a shortlist of priority pathogens that emerged from WHO's R&D Blueprint for action to prevent epidemics.4Coalition for Epidemic Preparedness Innovation, Priority diseases. http://cepi.net/resources#Priority-diseases (accessed Oct 26, 2017).Google Scholar, 5WHO, R&D Blueprint. List of Blueprint priority diseases. http://www.who.int/blueprint/priority-diseases (accessed Oct 26, 2017).Google Scholar These plans and disease-specific activities have been invaluable and have dramatically improved global preparedness and response capacity for biological threats. However, extending preparation beyond these lists is important, because new biological outbreaks occur every year, each with their own specific disease characteristics and response requirements. The characteristics of each potential biological event will drive coordination and support requirements for logistics, public health and medical countermeasures, security, investigation, and attribution for an attack. Each event could require as many as 20 different disciplines, spanning activities for prevention, detection, reporting, response, recovery, investigation (if needed), and governance, particularly if an event becomes global in scope. Some of these activities will be similar from one biological event to another, but many will require modification to address the specific parameters of the event. To define and communicate the complexity inherent in the biological threat space to decision makers, we identified 12 major response-relevant dimensions across which biological outbreaks or deliberate release events can be characterised (panel). 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 in the appendix).PanelParameters for biocomplexity model1Origin (natural or intentional)2Type (animal only, human only, or zoonotic disease)3Means of spread (communicable or non-communicable)4Route of transmission (airborne, bloodborne, waterborne, foodborne, or vector-borne)5Diagnostics (point of care and biosafety levels 1, 2, 3, and 4)6Medical countermeasures (antivirals, antibiotics, vaccine, post-exposure prophylaxis, or none)7Outbreak location (accessible to international community or not and whether conditions are non-permissive owing to conflict or other instability)8Affected populations (all, pregnant women, children, elderly, or targeted attack)9Applicable personal protective equipment (respirator, containment suit, mask, gloves, and gown)10Morbidity (graded at five levels from very low to very high)11Response level (local, intermediate, national, regional, or global)12Policy measures in place (national, international, or none) 1Origin (natural or intentional)2Type (animal only, human only, or zoonotic disease)3Means of spread (communicable or non-communicable)4Route of transmission (airborne, bloodborne, waterborne, foodborne, or vector-borne)5Diagnostics (point of care and biosafety levels 1, 2, 3, and 4)6Medical countermeasures (antivirals, antibiotics, vaccine, post-exposure prophylaxis, or none)7Outbreak location (accessible to international community or not and whether conditions are non-permissive owing to conflict or other instability)8Affected populations (all, pregnant women, children, elderly, or targeted attack)9Applicable personal protective equipment (respirator, containment suit, mask, gloves, and gown)10Morbidity (graded at five levels from very low to very high)11Response level (local, intermediate, national, regional, or global)12Policy measures in place (national, international, or none) We inputted the combinatorial results into a static database and created a visualisation tool using interactive graphics based on HTML5 and d3.js and coded in JavaScript. Filters allow the user to visualise subsets of the scenarios that reflect specific characteristics. Disease scenarios are sized on the basis of the number of fatalities estimated by general characteristics. Scenarios are coloured from red to purple to blue, with red indicating scenarios caused by agents that infect only humans to scenarios that cause disease primarily in animals, but can also infect humans. Attributes directly related to planning and response requirements are included in the figures and as the default filters; additional attributes can be analysed using the filters in the interactive web tool. Categorisation does not include whether the agent is viral, bacterial, or a toxin, but instead focuses on the response relevance of those characteristics: whether the agent is communicable, the route of transmission, and the type of medical countermeasure required for prophylaxis or treatment. Modelled scenarios include a bloodborne agent with no available medical countermeasure that results in 11 000 fatalities; a deliberate zoonotic disease event that results in 500 fatalities; and a naturally occurring pandemic of an airborne agent with delayed medical countermeasures that results in 1 100 000 fatalities (appendix) Designed for use by practitioners, decision makers, and educators, the tool and its scenario filtering provide a method to define exercise scenarios, drive discussions, and provide a framework around which to test and evaluate planning and exercise efforts. Additionally, the tool provides 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. We declare no competing interests. This work was partly funded by the Open Philanthropy Project grant to Georgetown University Center for Global Health Science and Security. Download .pdf (1.76 MB) Help with pdf files Supplementary appendix