NIH_UIUC-RIFTcov.yaml

team_name: "NIH-UIUC"
team_abbr: "NIH_UIUC"
model_name: "Reflecting Inequity in Future Time for SARS-CoV-2"
model_abbr: "RIFTcov"
model_contributors: [
  {
    "name": "Sophie Larsen",
    "affiliation": "Program in Ecology, Evolution, and Conservation Biology, University of Illinois at Urbana-Champaign, Urbana, IL, USA",
    "email": "sll4@illinois.edu"
  },
  {
   "name": "Samantha Bents",
   "affiliation": "Fogarty International Center, National Institutes of Health, Bethesda, MD, USA"
   "email": "samantha.bents@nih.gov"
  },
  {
    "name": "Cécile Viboud",
    "affiliation": "Fogarty International Center, National Institutes of Health, Bethesda, MD, USA",
    "email": "viboudc@mail.nih.gov"
  }
]
license: "cc-by-4.0"
methods: "This model is an adapted version of the ODE system published in Larsen et al. (Science Advances, 2023), replacing socioeconomic stratification with race/ethnicity structure and an explicitly NPI-compliant class."
methods_long: "This compartmental SEIR model tracks individuals through two levels of immunity (fully naive, previously infected/vaccinated). Daily contacts, case reporting rate, npi compliance, vaccination, and infection fatality rate are all stratified by race/ethnicity. The model is calibrated to cases and deaths using maximum likelihood estimation. During the projection period, uncertainty is incorporated through Latin hypercube sampling on profiled parameters (NPI compliance/duration, reporting rate and IFR) and on a range of possible changes in NPI compliance in the projection period relative to the calibration period."
model_version: "1.0"
citation: "Larsen, S, Shin I, Joseph J, West H, Anorga R, Mena G, Mahmud A, Martinez P. Quantifying the impact of SARS-CoV-2 temporal vaccination trends and disparities on disease control. Science Advances. 2023 Aug. doi: 10.1126/sciadv.adh9920."