diff --git a/model-metadata/OptimAgent-GEMS.yml b/model-metadata/OptimAgent-GEMS.yml
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+team_name: OptimAgent 
+model_name: German Epidemic Micro-Simulation System
+team_abbr: OptimAgent
+model_abbr: GEMS
+model_contributors:
+    - name: Aleksandr Bryzgalov
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: Aleksandr.Bryzgalov@uk-halle.de
+    - name: Beryl Musundi
+      affiliation: Martin-Luther-University, sHalle-Wittenberg
+      email: Beryl.Musundi@uk-halle.de
+    - name: Johannes Ponge
+      affiliation: University of Muenster
+      email: johannes.ponge@wi.uni-muenster.de
+    - name: Janik Suer
+      affiliation: University of Muenster
+      email: janik.suer@uni-muenster.de
+    - name: Tyll Krueger
+      affiliation: Wroclaw University of Science and Technology
+      email: tyll.krueger@googlemail.com
+    - name: Mahreen Kahkashan
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: Mahreen.Kahkashan@uk-halle.de
+    - name: Wolfgang Bock
+      affiliation: Linneaus University
+      email: wolfgang.bock@lnu.se
+    - name: Johannes Horn
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: johannes.horn@uk-halle.de
+    - name: Mirjam Kretzschmar
+      affiliation: Utrecht University
+      email: m.e.e.kretzschmar@umcutrecht.nl
+    - name: Rafael Mikolycjzyk
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: rafael.mikolajczyk@uk-halle.de
+    - name: Alexander Kuhlmann
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: Alexander.Kuhlmann@uk-halle.de
+methods: An agent-based modelling framework tailored for the German population to simulate epidemics.
+data_inputs: RKI 
+team_model_designation: primary
+methods_long: GEMS is an agent-based mathematical modelling framework tailored for the German population. Individuals in the model have attributes such as age and gender and are associated with contact settings that include households, schools, workplaces and municipality. Disease progression is age-dependent and seasonality effects are included. The model is calibrated using reported cases of hospitalizations and used to forecast COVID-19 infections and hospitalizations.
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