diff --git a/model.py b/model.py
index b54852fcf1285a27418776783f0422661997cb09..80ba27694b93f1ef3d3905eb79abc363b9274bad 100644
--- a/model.py
+++ b/model.py
@@ -7,10 +7,10 @@ import networkx as nx
 from agents import Bot, Police, Normal
 
 #Definition von Spreading-rates
-    #rate_PoliceToImmune = 0.5
-    #rate_BotToNormal = 0.2
-    #rate_MisToNormal = ??
-    #rate_NormalSelf = ??
+rate_PoliceToImmune = 0.5
+rate_BotToMis = 0.2
+rate_MisToNormal = 0.1
+rate_NormalSelf = 0.01
 
 class FakeModel(mesa.Model):
     """
@@ -80,12 +80,20 @@ class FakeModel(mesa.Model):
         #Änderungen des Steps
         for person in self.schedule.agents:
             #Ãœbergang: Normal zu misinformiert
-            if person.id in self.NeigBot and person.state == "normal" and random.random() <= 0.2:
+            if person.id in self.NeigBot and person.state == "normal" and random.random() <= rate_BotToMis:
                 person.state = "normal_mis"
                 NorToMis.append(person.id)
             #Ãœbergang: Immunisierung von Normalen
-            if person.id in self.NeigPolice and person.state in ["normal","normal_mis"] and random.random() <= 0.5:
+            if person.id in self.NeigPolice and person.state in ["normal","normal_mis"] and random.random() <= rate_PoliceToImmune:
                 person.state = "immune"
                 MisToNor.append(person.id)
+            #Ãœbergang: Misinformiert zu Normalen
+            if person.id in self.NeigMis and person.state == "normal" and random.random() <= rate_MisToNormal:
+                person.state = "normal_mis"
+                NorToMis.append(person.id)
+            #Ãœbergang: Normal zu Mis in Feed
+            if person.state == "normal" and random.random() <= rate_NormalSelf:
+                person.state = "normal_mis"
+                NorToMis.append(person.id)
 
         print("Zu mis: ", NorToMis, " Zu Imm: ", MisToNor, "\n")
\ No newline at end of file
diff --git a/run.py b/run.py
index 906efd5d5692b413311cc6f53d98a402047d61f7..5734ebaf7e6679c5992c2ec2c08715c6923eaa1c 100644
--- a/run.py
+++ b/run.py
@@ -7,7 +7,7 @@ from matplotlib.colors import LinearSegmentedColormap
 from model import FakeModel
 
 #Initialisierung
-FirstIteration = FakeModel(N=1000, police=23, bots=90, misinformed=1, ANDeg=60, directed=False)
+FirstIteration = FakeModel(N=50, police=4, bots=6, misinformed=3, ANDeg=7, directed=False)
 
 # Beispielzustände für jeden Agenten/ Visualisierungsparameter
 states = {"police": "blue", "bot": "red", "normal": "grey", "normal_mis": "orange", "immune":"green"}