diff --git a/model-metadata/CU-RSV_SVIRS.yaml b/model-metadata/CU-RSV_SVIRS.yaml
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+team_name: "Columbia University"
+team_abbr: "CU"
+model_name: "RSV_SVIRS"
+model_abbr: "RSV_SVIRS"
+model_contributors: [
+   {
+    "name": "Yamana Teresa",
+    "affiliation": "Columbia University",
+    "email": "tky2104@cumc.columbia.edu"
+  },
+  {
+   "name": "Pei Sen",
+    "affiliation": "Columbia University",
+    "email": "sp3449@cumc.columbia.edu"
+  }
+]
+license: "cc-by-4.0"
+methods: "Age-structured SVIRS model coupled with Ensemble Adjustment Kalman Filter. Inputs CDC RSV-NET, POLYMOD contact matrix, and seasonal absolute humidity"
+methods_long: "Age-structured state-level SVIRS compartmental model coupled with Ensemble Adjustment Kalman Filter. Model is fit to CDC RSV-NET data.  Each state’s population divided into age categories: <1, 1-4, 5-64, and 65+.  Model transmission rate is modified by seasonal absolute humidity.  Contacts between age groups are informed by the POLYMOD study. 300 ensemble members initialized once per location; the 5 scenarios being from these initializations.  However initial stochasticity is introduced if/when an ensemble member's parameter or state variable value goes out of bounds, in which case that value is reinitialized.  Vaccination and monocolonal antibody is applied as specified by the scenarios.  Additionally, we assume that each intervention provides a 20% protection against infection."
+model_version: "1.0"
+team_funding: "CSTE NU38OT00297"
+data_inputs: "CDC RSV-NET, POLYMOD contact matrix, and seasonal absolute humidity"
+
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