diff --git a/caimira/apps/calculator/report_generator.py b/caimira/apps/calculator/report_generator.py
index f171fe01..8f30876c 100644
--- a/caimira/apps/calculator/report_generator.py
+++ b/caimira/apps/calculator/report_generator.py
@@ -274,9 +274,9 @@ def manufacture_alternative_scenarios(form: FormData) -> typing.Dict[str, mc.Exp
     return scenarios
 
 
-def scenario_statistics(mc_model: mc.ExposureModel, sample_times: typing.List[float], probabilistic_exposure: bool):
+def scenario_statistics(mc_model: mc.ExposureModel, sample_times: typing.List[float], compute_prob_exposure: bool):
     model = mc_model.build_model(size=_DEFAULT_MC_SAMPLE_SIZE)
-    if (probabilistic_exposure):
+    if (compute_prob_exposure):
         # It means we have data to calculate the total_probability_rule
         prob_probabilistic_exposure = np.array(model.total_probability_rule()).mean()
     else:
@@ -312,16 +312,16 @@ def comparison_report(
         statistics = {}
     
     if (form.short_range_option == "short_range_yes" and form.exposure_option == "p_probabilistic_exposure"):
-        probabilistic_exposure = True
+        compute_prob_exposure = True
     else:
-        probabilistic_exposure = False
+        compute_prob_exposure = False
 
     with executor_factory() as executor:
         results = executor.map(
             scenario_statistics,
             scenarios.values(),
             [sample_times] * len(scenarios),
-            [probabilistic_exposure] * len(scenarios),
+            [compute_prob_exposure] * len(scenarios),
             timeout=60,
         )
 
diff --git a/caimira/models.py b/caimira/models.py
index 913487e9..92589a22 100644
--- a/caimira/models.py
+++ b/caimira/models.py
@@ -1475,7 +1475,7 @@ class ExposureModel:
             # The influence of a higher number of simultainious infected people (> 4 - 5) yields an almost negligible contirbution to the total probability. 
             # To be on the safe side, a hard coded limit with a safety margin of 2x was set.
             # Therefore we decided a hard limit of 10 infected people.
-            for num_infected in range(1, max_num_infected):
+            for num_infected in range(1, max_num_infected + 1):
                 exposure_model = nested_replace(
                     self, {'concentration_model.infected.number': num_infected}
                 )
diff --git a/caimira/tests/test_full_algorithm.py b/caimira/tests/test_full_algorithm.py
index 0ef12fda..aea4151c 100644
--- a/caimira/tests/test_full_algorithm.py
+++ b/caimira/tests/test_full_algorithm.py
@@ -785,6 +785,7 @@ def test_concentration_with_shortrange(expo_sr_model,simple_expo_sr_model,time):
         )
 
 
+@retry(tries=10)
 def test_exposure_with_shortrange(expo_sr_model,simple_expo_sr_model):
     npt.assert_allclose(
         expo_sr_model.build_model(SAMPLE_SIZE).deposited_exposure().mean(),