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This NSF Expedition in Computing is a multi-institution partnership aimed at advancing the computational foundations, engineering principles, and technologies of computational epidemiology at an unprecedented scale.

By fostering collaborations between researchers of complementary expertise among our member institutions and beyond, we have taken on challenges we couldn't have done alone. Most notably, our team has been able to tackle unique challenges posed by the COVID-19 pandemic. We highlight some of the challenges and the resulting scientific breakthroughs and social and policy impact of our work here.

Challenge 1: Understand the effects of lockdown strategies on the spread of SARS-CoV-2
   

Solution: For every hour, our mobility-based epidemiological model predicts who got infected where. We fit the model to past reported COVID-19 cases and deaths to get accurate predictions, and then applied our model to analyze reopening, disparities, superspreaders, and more. We show higher infection risks to lower-income and minority census block groups.

Computational advances: Real-time data-driven epidemic modeling

Mobility network models of COVID-19 explain inequities and inform reopening (Chang 2020)

Social and Policy impacts: This work was referenced in two Supreme Court decisions and multiple national-level public health policies.

 
Challenge 2: Develop resource allocation and distribution systems that promote accessibility and equity
   

Solution: We capture accessibility and equity in a combinatorial problem, allowing us to develop efficient algorithms with theoretical guarantees on both of these aspects. This work has led to the optimization of public health resource utilization, including emergency field hospitals; vaccine distribution and allocation; contact tracing; and quarantine and testing.

Computational advances: Real-time stochastic optimization in an uncertain environment

Data-driven Real-time Strategic Placement of Mobile Distribution Sites (Mehrab 2022)

Social and Policy impacts: The state of Virginia has relied on our models to inform public health policy decisions, from March 2020 to present. A Spring 2022 report from the VDH Central Office to the VA General Assembly articulated the impact of our work.

Medical Resource Demand Dashboard

 
Challenge 3: Provide long-term state-level US COVID-19 forecasts to public health officials, decision makers, and the general public
   

Solution: Provided forecasts of COVID-19 trajectories for various scenarios under different assumptions, such as: scale of wave, impact of variants with up-to-date data and epidemiological understanding, vaccination of children, and others.

Computational advances: Data-driven, national-scale, high-performance computing agent models

ACM Gorden Bell Finalist - Specialist Prize for HPC-based COVID-19 Research: Scalable Epidemiological Workflows to Support COVID-19 Planning and Response (Machi 2021)

DeepCOVID: Deep Learning-driven Framework for Explainable Real-time COVID-19 Forecasting (Rodriguez 2021)

Social and Policy impacts: This work was referenced in two Supreme Court decisions and multiple national-level public health policies, and the results were presented to the COVID-19 task force, the head of the CDC, and the White House coronavirus response coordinator, Dr. Jha, and his team.

CDC Morbidity and Mortality Weekly Report May 14, 2021

UVA Provost’s Office Award for Collaborative Excellence in Public Service

 

 

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Find our two fascinating    podcasts on Spotify!

Science Before the Storm: When we speak of the next pandemic, it's no longer a question of "if" but "when". Join us as we talk to the scientists in the NSF research community readying us for the next pandemic.

 

COVID Chasers: A special podcast series from researchers at the Biocomplexity Institute (NSSAC Division), University of Virginia on supporting COVID-19 response in the US over the past year.

 

 

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US and UK launch research prize for ‘privacy enhancing technology’

UVA NSSAC GITHUB

     

Virginia Tech researchers garner two major awards in COVID-19 forecasting challenges

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➢ PRAKASH LAB PAGE

     

Georgia Tech research team wins two COVID-19 challenges in one week

PRAKASH LAB'S COVID PAGE