diff --git a/tutorials/IDD/spatial_SIR/simulation.py b/tutorials/IDD/spatial_SIR/simulation.py
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+"""
+This script contains a calibration of an SIR model to synthetic data.
+"""
+
+__author__      = "Tijs Alleman"
+__copyright__   = "Copyright (c) 2024 by T.W. Alleman, IDD Group, Johns Hopkins Bloomberg School of Public Health. All Rights Reserved."
+
+############################
+## Load required packages ##
+############################
+
+import numpy as np
+import matplotlib.pyplot as plt
+
+######################
+## Initialise model ##
+######################
+
+# A model with two age groups and two spatial patches 'A' (500 inhabitants) and 'B' (5000 inhabitants).
+# Epidemic is seeded in location 'A'. Inhabitants of 'B' never visit 'A'.
+# While 20% of inhabitants of 'A' visits 'B', and has f_v % of their contacts in 'B'.
+
+coordinates = {'age': ['0-25', '25+'],  # 2 age groups
+               'location': ['A', 'B']   # 2 spatial units 'A' and 'B'
+                }
+init_states = {'S': np.array([[100, 400], [1000, 4000]]),   # 
+               'I': np.array([[1, 0], [0, 0]])
+               }
+params = {'beta': 0.025,                                # infectivity (-)
+          'gamma': 5,                                   # duration of infection (d)
+          'f_v': 0.1,                                   # fraction of total contacts on visited patch
+          'N': np.array([[10.7, 7.9],[3.22, 14.0]]),    # contact matrix (BE, Van Hoang, 2020)
+          'M': np.array([[0.8, 0.2], [0, 1]])           # origin-destination mobility matrix
+          }
+
+# initialize model
+from models import spatial_ODE_SIR
+model = spatial_ODE_SIR(states=init_states, parameters=params, coordinates=coordinates)
+
+##########################
+## Simulate & visualise ##
+##########################
+
+# simulate
+out = model.sim(90)
+
+# visualise
+fig,ax=plt.subplots(nrows=2, figsize=(8.3,11.7/2))
+
+ax[0].set_title('Overall')
+ax[0].plot(out['time'], out['S'].sum(dim=['age', 'location']), color='green', alpha=0.8, label='S')
+ax[0].plot(out['time'], out['I'].sum(dim=['age', 'location']), color='red', alpha=0.8, label='I')
+ax[0].plot(out['time'], out['R'].sum(dim=['age', 'location']), color='black', alpha=0.8, label='R')
+ax[0].legend(loc=1, framealpha=1)
+
+ax[1].set_title('Infected')
+ax[1].plot(out['time'], out['I'].sum(dim='age').sel({'location': 'A'}), linestyle = '-', color='red', alpha=0.8, label='location A')
+ax[1].plot(out['time'], out['I'].sum(dim='age').sel({'location': 'B'}), linestyle = '-.', color='red', alpha=0.8, label='location B')
+ax[1].legend(loc=1, framealpha=1)
+
+plt.tight_layout()
+plt.show()
+plt.close()
+
+