<｜begin▁of▁sentence｜>### Instruction:
In the intricate web of social connections within a correctional facility, assume we have documented interactions that can be described as a series of connections: an individual (1) has connections to individuals (2) and (3), and both (2) and (3) are connected to one another. Additionally, individual (3) has a connection to (4), who in turn has connections to individual (5). If our goal is to prevent communication between individual (1) and individual (5) due to concerns about potential collusion, we are faced with the complex task of understanding the minimum number of individuals that would need to be strategically reassigned to different sections of the facility to disrupt this particular communication channel. How would we determine the fewest number of individuals to reassign in order to sever the link between individuals (1) and (5), while maintaining the broader social structure of the facility? This scenario is captured in the interactions graph provided.
### Response:
import networkx as nx
from networkx.algorithms.connectivity import local_node_connectivity

# Create a graph
G = nx.Graph()
G.add_edges_from([(1, 2), (1, 3), (2, 3), (3, 4), (4, 5)])

# Calculate local node connectivity between nodes 1 and 5
connectivity = local_node_connectivity(G, 1, 5)

print('Local node connectivity between nodes 1 and 5:', connectivity)
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