Advancing decision support and training to ensure intelligent responses to uncertain pathogen threats.
Throughout the COVID-19 pandemic, leaders have scrambled to combat an evolving threat, equipped with a growing arsenal of countermeasures, and yet hindered by unexpected cascading political, social and health dynamics. Despite decades of planning, we did not and still do not have a robust playbook. Cities, states and countries made idiosyncratic decisions regarding re-opening and closing, face-mask requirements, and vaccination policies that are often met with political and social resistance. Effective and timely responses have been further hampered by fragile supply chains and by limited and uncertain availability of key resources, including PPE, healthcare personnel, ICU beds and ventilators, and low-cost tests. We critically need to develop science and practice that can guide effective decision-making, even when situations change unexpectedly.
Our pilot projects and workshops are grounded in the following three hypotheses:
- Staged alert systems provide a good scientific starting point for developing a robust decision-support framework, applicable across all stages of emergence, containment, mitigation, and endemicity. Such systems can be designed to provide clear guideposts that reduce uncertainty and decision complexity. They typically track a few key indicators that reflect pandemic severity and trigger changes in alert level at thresholds corresponding to states of increasing concern (e.g., Harvard Global Health Institute proposed widely-adopted thresholds based on estimated incidence; France triggered lock downs based on ICU bed utilization by COVID patients; Colorado, Illinois, and New York developed their own systems). More generally, alert systems are used to warn the public of threats, from terrorism, floods and hurricanes, as a means to clarify decision making and encourage adherence to official guidance. If done right, such systems could provide a critical source of predictive intelligence, enabling adaptive responses that can turn the tide of a pandemic threat.
- COVID-19 provides a valuable model system for research and validation. Numerous alert systems have been enacted, but few indicate their theoretical underpinnings. We do not yet know the extent to which they actually guide policy, influence individual behavior, mitigate risks and burdens, or anticipate and ensure needed healthcare supplies.
- Without experienced teams of decision makers, even the best policies will fall short. By developing next generation pandemic exercises, grounded in interdisciplinary science and gaming, we can significantly improve decision making by individuals and organizations.
Pilot Study 3.1 – A prototype decision-support system. As a first step towards engineering decision-support systems for mitigating pathogen threats at any phase of emergence, we will extend the framework we used to build the COVID-19 staged alert system for Austin, Texas into a plug-and-play prototype for designing staged strategies that balance competing public health and socioeconomic goals. The “plug in” components will consist of: (i) an epidemic model that incorporates the impacts of mitigation measures (such as reductions in transmission), the observational process that will be used to trigger alert stages (such as case counts), and key outcome measures (such as hospitalizations or deaths), (ii) a set of policy goals and constraints (such as minimizing mortality or economic costs), and (iii) a policy space (such as an infinite set of possible thresholds for triggering changes in alert levels), and (iv) an optimization algorithm (such as a grid-based search or reinforcement learning).
Pilot Study 3.2 – Small-scale preparedness exercise to advance simulation of unknown unknowns. We will design and run a small-scale planning exercise to evaluate its ability to generate meaningful challenges. Co-PI Escott (City of Austin) and Collaborator Gentry (Texas Department of Public Safety) will help to assemble a team of local and state public health and emergency response officials to participate; Collaborators Polski (US Naval War College) and de Rosa (NATO) will guide the translation of the simulations into an exercise format as well as the execution of the event and CAPTRS will provide logistical support. The outcomes will be evaluated quantitatively, and the human participants will qualitatively evaluate the realism and challenge provided by these techniques. The focus will be to provide a proof-of-concept for the design and implementation of simulation-based exercises and evaluate the proposed methods for synthesizing complex interacting dynamics.