diff --git a/tests/fixtures.py b/tests/fixtures.py
index 9d2d75802..c068bd62c 100644
--- a/tests/fixtures.py
+++ b/tests/fixtures.py
@@ -93,7 +93,7 @@ def __init__(
     ModelFixture(os.path.join(MODELS_PATH, "SEIRHD_stockflow.json"), "p_cbeta"),
 ]
 
-optimize_kwargs_SIRstockflow_param = {
+optkwargs_SIRstockflow_param = {
     "qoi": lambda x: obs_nday_average_qoi(x, ["I_state"], 1),
     "risk_bound": 300.0,
     "static_parameter_interventions": param_value_objective(
@@ -106,7 +106,7 @@ def __init__(
     "bounds_interventions": [[0.1], [0.5]],
 }
 
-optimize_kwargs_SIRstockflow_time = {
+optkwargs_SIRstockflow_time = {
     "qoi": lambda x: obs_nday_average_qoi(x, ["I_state"], 1),
     "risk_bound": 300.0,
     "static_parameter_interventions": start_time_objective(
@@ -118,7 +118,7 @@ def __init__(
     "bounds_interventions": [[0.0], [40.0]],
 }
 
-optimize_kwargs_SIRstockflow_time_param = {
+optkwargs_SIRstockflow_time_param = {
     "qoi": lambda x: obs_nday_average_qoi(x, ["I_state"], 1),
     "risk_bound": 300.0,
     "static_parameter_interventions": start_time_param_value_objective(
@@ -129,35 +129,47 @@ def __init__(
     "bounds_interventions": [[0.0, 0.1], [40.0, 0.5]],
 }
 
-optimize_kwargs_SEIRHD_param_maxQoI = {
+# Creating a combined intervention
+intervened_params = ["beta_c", "gamma"]
+static_parameter_interventions1 = param_value_objective(
+    param_name=[intervened_params[0]],
+    start_time=torch.tensor([10.0]),
+)
+static_parameter_interventions2 = start_time_objective(
+    param_name=[intervened_params[1]],
+    param_value=torch.tensor([0.45]),
+)
+# Combine different intervention templates into a list of Callables
+static_parameter_interventions = lambda x: [
+    static_parameter_interventions1(torch.atleast_1d(x[0])),
+    static_parameter_interventions2(torch.atleast_1d(x[1])),
+]
+optkwargs_SEIRHD_paramtimeComb_maxQoI = {
     "qoi": lambda x: obs_max_qoi(x, ["I_state"]),
-    "risk_bound": 300.0,
-    "static_parameter_interventions": param_value_objective(
-        param_name=["beta_c", "gamma"],
-        start_time=[torch.tensor(10.0), torch.tensor(15.0)],
-    ),
-    "objfun": lambda x: np.abs(0.35 - x[0]) + np.abs(0.2 - x[1]),
-    "initial_guess_interventions": [0.2, 0.4],
-    "bounds_interventions": [[0.1, 0.1], [0.5, 0.5]],
+    "risk_bound": 3e5,
+    "static_parameter_interventions": static_parameter_interventions,
+    "objfun": lambda x: np.abs(0.35 - x[0]) - x[1],
+    "initial_guess_interventions": [0.35, 5.0],
+    "bounds_interventions": [[0.1, 1.0], [0.5, 90.0]],
     "fixed_static_parameter_interventions": {10.0: {"hosp": torch.tensor(0.1)}},
 }
 
 OPT_MODELS = [
     ModelFixture(
         os.path.join(MODELS_PATH, "SIR_stockflow.json"),
-        optimize_kwargs=optimize_kwargs_SIRstockflow_param,
+        optimize_kwargs=optkwargs_SIRstockflow_param,
     ),
     ModelFixture(
         os.path.join(MODELS_PATH, "SIR_stockflow.json"),
-        optimize_kwargs=optimize_kwargs_SIRstockflow_time,
+        optimize_kwargs=optkwargs_SIRstockflow_time,
     ),
     ModelFixture(
         os.path.join(MODELS_PATH, "SIR_stockflow.json"),
-        optimize_kwargs=optimize_kwargs_SIRstockflow_time_param,
+        optimize_kwargs=optkwargs_SIRstockflow_time_param,
     ),
     ModelFixture(
         os.path.join(MODELS_PATH, "SEIRHD_NPI_Type1_petrinet.json"),
-        optimize_kwargs=optimize_kwargs_SEIRHD_param_maxQoI,
+        optimize_kwargs=optkwargs_SEIRHD_paramtimeComb_maxQoI,
     ),
 ]