Data-driven mechanistic framework with stratified immunity and effective transmissibility for COVID-19 scenario projections

Details

• Alternative Title:
  Epidemics
• Personal Author:
  Porebski, Przemyslaw ; Venkatramanan, Srinivasan ; Adiga, Aniruddha ; Klahn, Brian ; Hurt, Benjamin ; Wilson, Mandy L. ; Chen, Jiangzhuo ; Vullikanti, Anil ; Marathe, Madhav ; Lewis, Bryan
• Description:
  Scenario-based modeling frameworks have been widely used to support policy-making at state and federal levels in the United States during the COVID-19 response. While custom-built models can be used to support one-off studies, sustained updates to projections under changing pandemic conditions requires a robust, integrated, and adaptive framework. In this paper, we describe one such framework, UVA-adaptive, that was built to support the CDC-aligned Scenario Modeling Hub (SMH) across multiple rounds, as well as weekly/biweekly projections to Virginia Department of Health (VDH) and US Department of Defense during the COVID-19 response. Building upon an existing metapopulation framework, PatchSim, UVA-adaptive uses a calibration mechanism relying on adjustable effective transmissibility as a basis for scenario definition while also incorporating real-time datasets on case incidence, seroprevalence, variant characteristics, and vaccine uptake. Through the pandemic, our framework evolved by incorporating available data sources and was extended to capture complexities of multiple strains and heterogeneous immunity of the population. Here we present the version of the model that was used for the recent projections for SMH and VDH, describe the calibration and projection framework, and demonstrate that the calibrated transmissibility correlates with the evolution of the pathogen as well as associated societal dynamics.
• Subjects:
  COVID-19 COVID-19 Vaccines Epidemiological Models Forecasting Humans Pandemics SARS-CoV-2 United States Virginia
• Keywords:
  Alzheimer's Disease Alzheimer's Disease Sequencing Project Antiviral Agents Compartmental Model Herpes Simplex Human Papillomavirus Population Immunity Scenario Projections Torque Teno Viruses Transmission Dynamics Variant Characteristics Whole Exome Sequencing Whole Genome Sequencing

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• Source:
  Epidemics. 47:100761
• Pubmed ID:
  38555667
• Pubmed Central ID:
  PMC11205267
• Document Type:
  Journal Article
• Funding:
  NU38OT000297/CC/CDC HHSUnited States/ ; R01 GM109718/GM/NIGMS NIH HHSUnited States/
• Volume:
  47
• Collection(s):
  CDC Public Access
• Main Document Checksum:
  urn:sha-512:0ec7c4078d114a3825bc451e3b1cbd095afc063e2a0d396e8ad4a24757841485c3150bada5928e8dafda067e232d2523716c693159dd151f0d4e01d73a8e10c5
• Download URL:
  https://stacks.cdc.gov/view/cdc/158166/cdc_158166_DS1.pdf
• File Type:
  [PDF - 1.98 MB ]