OptimAgent 2024_2025_COVID_1

model-metadata/OptimAgent_GEMS.yml

@@ -0,0 +1,42 @@
+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: [email protected]
+    - name: Beryl Musundi
+      affiliation: Martin-Luther-University,Halle-Wittenberg
+      email: [email protected]
+    - name: Johannes Ponge
+      affiliation: University of Muenster
+      email: [email protected]
+    - name: Janik Suer
+      affiliation: University of Muenster
+      email: [email protected]
+    - name: Tyll Krueger
+      affiliation: Wroclaw University of Science and Technology
+      email: [email protected]
+    - name: Mahreen Kahkashan
+      affiliation:Martin-Luther-University, Halle-Wittenberg
+      email: [email protected]
+    - name: Wolfgang Bock
+      affiliation: Linneaus University
+      email: [email protected]
+    - name: Johannes Horn
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: [email protected]
+    - name: Mirjam Kretzschmar
+      affiliation: Utrecht University
+      email: [email protected]
+    - name: Rafael Mikolycjzyk
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: [email protected]
+    - name: Alexander Kuhlmann
+      affiliation: Martin-Luther-University, Halle-Wittenberg
+      email: [email protected]
+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.