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Data Science

How Data and Simulation Can Optimize Human Resiliency

How can we use public health data forecasting and simulation to optimize human resiliency in the wake of national emergencies and disasters? Bryan Lewis, research associate professor for the Biocomplexity Institute and Initiative, recently tackled this topic at the National Academies of Sciences, Engineering, and Medicine (NASEM) “Frontiers of Big Data, Modeling, and Simulation in Urban Sustainability” workshop in Washington, D.C.

The workshop brought together an interdisciplinary network of practitioners, business leaders, academics, and policymakers using data for urban sustainability to identify areas where cities can partner with the scientific community to address challenges related to air and water quality, transportation and physical infrastructure, and sustainable inclusive communities.

Lewis was among about a dozen experts speaking on advances in data, modeling, and simulation. His presentation, “Public Health and Simulation for Supporting Urban Sustainability,” specifically addressed his team’s state-of-the-art work in the public health arena. Lewis discussed how simulation of emergencies and disasters such as disease outbreaks or catastrophic events can be used to inform and develop response plans and public policy to optimize preparedness and lives saved.

Through computational techniques such as disease forecasting, synthetic representations of urban populations, and pandemic simulations, researchers can actually mimic how large numbers of people would respond to emergencies. The resulting data helps researchers and policymakers explore and develop large-scale plans for health, power, communication, transportation, and other critical functions.

Lewis acknowledged that while computer simulations are very useful for public health policy and have huge potential for informing urban sustainability, we still have a long way to go when it comes to finding ways to incorporate them at the local and state levels. “The city is such a complicated organism, if we can get these massively interdependent systems represented and captured, doing this in the simulation platform makes a lot of sense. I think we can start solving a lot of these problems, but the ‘how’ is still to be worked out. We are increasingly able to gather the data and make representations in a computational framework. Now, the question is – how do we translate that into governance and operations?”

Answering that question of ‘how’ is becoming more possible through myriad technological advancements, such as model-guided machine learning and virtual reality that can extend the use of simulation, improve cost efficiency, and make otherwise complex data more accessible and understandable to a broader range of people. Further, Lewis stated that because of technological advancements, we’re now at a place where we must rethink how to structure the governance and management of our societies to enable useful data and intelligence to emerge more organically. 

The National Academies of Sciences, Engineering, and Medicine are private, nonprofit institutions that provide expert advice on some of the most pressing challenges facing the nation and the world. Their work helps shape sound policies, inform public opinion, and advance the pursuit of science, engineering, and medicine. The “Frontiers of Big Data, Modeling, and Simulation in Urban Sustainability” workshop was organized by the National Academies’ Mathematical Sciences and Analytics, Energy and Environmental Systems, and Computer Science and Telecommunications Boards. 

View Lewis’ full presentation (starting at 1:11) and the entire event webcast here: