Christopher L. Barrett

About

Christopher L. Barrett is the inaugural Distinguished Professor in Biocomplexity, Executive Director of the Biocomplexity Institute, and Professor in the Department of Computer Science at the University of Virginia. He is an interdisciplinary computational scientist who has published more than 100 research articles exploring all aspects of large multi-scale interaction systems. During the past 35 years, Barrett has conceived, founded, and led large interdisciplinary complex systems research projects and organizations, established national and international technology programs, and co-founded organizations for federal agencies such as the Department of Defense, the Department of Energy, and the Department of Homeland Security. His research interests include large multi-scale, high-performance modeling and simulation systems grounded in computational and information sciences spanning mathematical, biological, psychological, and social sciences, as well as dynamical networks, intelligent systems, and translational research-to-application analytics and machine intelligence.

Research topics

• Political Science
• Computer Science
• Medicine
• Virology
• Pathology
• History
• Nursing
• Data science
• Law

Selected publications

• Commentary on Ferguson, et al., “Impact of Non-pharmaceutical Interventions (NPIs) to Reduce COVID-19 Mortality and Healthcare Demand”

  Bulletin of Mathematical Biology · 2020 · 945 citations

  Senior authorCorresponding

  A recent manuscript (Ferguson et al. in Impact of non-pharmaceutical interventions (NPIs) to reduce COVID-19 mortality and healthcare demand, Imperial College COVID-19 Response Team, London, 2020. https://www.imperial.ac.uk/media/imperial-college/medicine/sph/ide/gida-fellowships/Imperial-College-COVID19-NPI-modelling-16-03-2020.pdf) from Imperial College modelers examining ways to mitigate and control the spread of COVID-19 has attracted much attention. In this paper, we will discuss a coarse t…

  DOI

• Prioritizing allocation of COVID-19 vaccines based on social contacts increases vaccination effectiveness

  medRxiv (Cold Spring Harbor Laboratory) · 2021 · 70 citations

  We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Even optimistic estimates suggest that most countries will likely take 6 to 24 months to vaccinate their citizens. These time estimates and the emergence of new viral strains urge us to find quick and effective ways to allocate the vaccines and contain the pandemic. While current approaches use combinations of age-based and occupation-based prioritizations, our s…

  DOI

• Heterogeneous adaptive behavioral responses may increase epidemic burden

  Scientific Reports · 2022-07-04 · 23 citations

  articleOpen access

  Non-pharmaceutical interventions (NPIs) constitute the front-line responses against epidemics. Yet, the interdependence of control measures and individual microeconomics, beliefs, perceptions and health incentives, is not well understood. Epidemics constitute complex adaptive systems where individual behavioral decisions drive and are driven by, among other things, the risk of infection. To study the impact of heterogeneous behavioral responses on the epidemic burden, we formulate a two risk-gro…

  PublisherOA PDFDOI

• Data-driven scalable pipeline using national agent-based models for real-time pandemic response and decision support

  The International Journal of High Performance Computing Applications · 2022-10-20 · 20 citations

  articleOpen access

  This paper describes an integrated, data-driven operational pipeline based on national agent-based models to support federal and state-level pandemic planning and response. The pipeline consists of ( i) an automatic semantic-aware scheduling method that coordinates jobs across two separate high performance computing systems; ( ii) a data pipeline to collect, integrate and organize national and county-level disaggregated data for initialization and post-simulation analysis; ( iii) a digital twin…

  PublisherOA PDFDOI

• Effective Social Network-Based Allocation of COVID-19 Vaccines

  Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining · 2022-08-12 · 19 citations

  articleOpen access

  We study allocation of COVID-19 vaccines to individuals based on the structural properties of their underlying social contact network. Using a realistic representation of a social contact network for the Commonwealth of Virginia, we study how a limited number of vaccine doses can be strategically distributed to individuals to reduce the overall burden of the pandemic. We show that allocation of vaccines based on individuals' degree (number of social contacts) and total social proximity time is s…

  PublisherDOI

Frequent coauthors

• Madhav Marathe

  100 shared

• Bryan Lewis

  Biocom

  47 shared

• Stephen Eubank

  University of Virginia

  39 shared

• Henning Mortveit

  University of Virginia

  38 shared

• Christian M. Reidys

  38 shared

• Srinivasan Venkatramanan

  Biocom

  35 shared

• Fenix W. D. Huang

  35 shared

• Achla Marathe

  32 shared

Awards & honors

• 2012–2013 Jubilee Professorship in Computer Science and Engi…
• Distinguished International Professor at the Royal Institute…
• Distinguished Achievement Award, Los Alamos National Laborat…
• Meritorious Service Medal (U.S. Navy) for research and devel…
• Virginia Academy of Science, Engineering, and Medicine 2021…

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