Using Traffic Data to Inform Transmission Dynamics for COVID-19 in Southern California

Details

• Creators:
  Suen, Sze-chuan ; Dessouky, Maged ; Zhang, Suyanpeng ; Yu, Han ; Nguyen, Anthony
• Corporate Creators:
  METRANS Transportation Center (Calif.) ; Pacific Southwest Region 9 UTC, University of Southern California
• Corporate Contributors:
  United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  • COVID-19
  • Communicable diseases
  • Computer models
  • Traffic flow
  • Origin and destination Compartmental model
• Publication/ Report Number:
  PSR-20-SP95
• Resource Type:
  Tech Report
• Geographical Coverage:
  California;Southern California;United States
• Edition:
  Final report (August 1, 2020-July 29,2021)
• Corporate Publisher:
  METRANS Transportation Center (Calif.)
• Abstract:
  Understanding COVID patterns for disease control means that we need to incorporate population flow in our modeling, as these trends influence disease transmission. We use ADMS traffic data to build a compartmental disease model of COVID-19. We draw on methodology from infectious disease models, traffic data, and facility location models together in a novel way, and to our knowledge, no prior work has leveraged such detailed traffic information over such a large urban area to inform disease control efforts.
• Content Notes:
  Project name: Identifying Priority Testing Locations in Southern California for COVID-19 With Transmission Dynamics and Network Data
• Format:
  PDF
• Funding:
  69A3551747109
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/67531/dot_67531_DS1.pdf
• File Type:
  [PDF - 1.33 MB]
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:1f2a968ec635fa815686e24c6a99605eefc3b8d6a39e5c6eaa10d07f9a7e26f5baae3d0f4a6acd07cb915e814b3ec2e62678e0331c82121d2e29e070328f77fb