Analytics for COVID-19 Decision Making

State-level Modeling Results >>

County-level Modeling Results >>

School-level Modeling Results >>

While current models of the COVID-19 pandemic have helped North Carolina decision-makers in the planning process, they are not detailed enough to factor in the interactions between people, resources and policies in their local communities. Our multidisciplinary team is developing an integrated simulation model that captures both the COVID-19 spread at the census tract level and the resulting load on North Carolina healthcare systems. This model will give the decision-makers a tool to make accurate high-priority policy and operational decisions at the local and state levels over the next several years.

Our Papers

Association of Simulated COVID-19 Vaccination and Nonpharmaceutical Interventions With Infections, Hospitalizations, and Mortality

ABSTRACT: Vaccination against SARS-CoV-2 has the potential to significantly reduce transmission and COVID-19 morbidity and mortality. But, the relative importance of vaccination strategies and nonpharmaceutical interventions (NPIs) is not well understood. The objective of this study was to assess the association of simulated COVID-19 vaccine efficacy and coverage scenarios with and without NPIs with infections, hospitalizations, and deaths. MORE >>

High-Quality Masks Reduce COVID-19 Infections and Deaths in the US

ABSTRACT: To evaluate the effectiveness of widespread adoption of masks or face coverings to reduce community transmission of the SARS-CoV-2 virus that causes COVID-19. MORE >>

COVID-19 Simulation Integrated Model: Omicron Modeling Call

COVID-19 Omicron Model – short version

PDF: This is a presentation that was given to the CDC on 12/16/2021 concerning the results of the group’s omicron model.

COVID Modeling Teams’ Statement

Multiple academic teams were selected by the Council of State and Territorial Epidemiologists
and the CDC to support decision-making in health jurisdictions.

Download the joint statement on the Omicron variant.

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Meet our Multidisciplinary Team

  • Julie Swann, Ph.D. | A. Doug Allison Distinguished Professor and Department Head 1 | Affiliate 3 | Industrial & Systems Engineering | jlswann@ncsu.edu
  • Paul Delamater, Ph.D. | assistant professor, Dept. of Geography 2 | pld@email.unc.edu
  • Kristen Hassmiller Lich, Ph.D. | associate professor, Dept. of Health Policy and Management, Gillings School of Global Public Health 2 | klich@unc.edu
  • Mark Holmes, Ph.D. | professor, Dept. of Health Policy and Management, Gillings School of Global Public Health 2 | mark_holmes@unc.edu
  • Julie Ivy, Ph.D. | professor, Fitts Faculty Fellow of Health Systems Engineering, Dept. of Industrial & Systems Engineering 1 | jsivy@ncsu.edu
  • Karl Johnson | Ph.D. candidate, Dept. of Health Policy and Management, Gillings School of Global Public Health 2 | karl12@live.unc.edu
  • Pinar Keskinocak, Ph.D. | William W. George Chair and Professor, Dept. of Industrial and Systems Engineering 3 | pinar@isye.gatech.edu
  • Maria Mayorga, Ph.D. | professor, Dept. of Industrial & Systems Engineering 1 | memayorg@ncsu.edu
  • Jessica Mele | Ph.D. candidate, Dept. of Operations Research 1 | jmele@ncsu.edu
  • Buse Oruc Aglar | Ph.D. candidate, H. Milton Stewart School of Industrial and Systems Engineering 3 | beo.aglar@gatech.edu
  • Mehul Patel, Ph.D. | assistant professor, Dept. of Emergency Medicine 2 | mehul_patel@med.unc.edu
  • Erik Rosenstrom | Ph.D. candidate, Dept. of Operations Research 1 | erosens@ncsu.edu
  • Raymond Smith, Ph.D. | assistant professor, Dept. of Engineering at East Carolina University | smithraym17@ecu.edu
  • Akane Fujimoto Wakabayashi | Ph.D. candidate, H. Milton Stewart School of Industrial and Systems Engineering 3 | afujimoto@gatech.edu
  • April Zhuoting Yu | Ph.D. candidate, H. Milton Stewart School of Industrial and Systems Engineering 3 | zhuoting@gatech.edu

1 North Carolina State University (NCSU)

2 University of North Carolina at Chapel Hill (UNC-CH)

3 Georgia Institute of Technology (GT)

Funding Sources

  • CDC: “Integrated Systems Model to Inform State and Local Planning for the COVID-19 Pandemic”. Council of State and Territorial Epidemiologists (CSTE), Prime: Centers for Disease Control & Prevention. (10/2020-6/2021) PI: Swann.
  • NC TaCS: “Integrated Systems Model to Inform State and Local Planning for the COVID-19 Pandemic”. UNC-Chapel Hill / NC State Translational Research Grant (NC TraCS) and ORI NCSU.  (8/2020-7/2021). PI: Mayorga

Additional Resources