<｜begin▁of▁sentence｜>### Instruction:
Imagine that we're developing an educational module for a public health initiative that aims to illustrate the strength and resilience of closely-knit communities in preventing the spread of disease. The Petersen graph will serve as the basis for our simulation, representing a highly interconnected social network. We want to showcase how different subgroups within the community are interlinked, which can be analogous to the k-component structure in graph theory.

Could you guide us through the process of using NetworkX to analyze the intricate k-component structure of the Petersen graph? By examining such a structure, we intend to provide a visual demonstration of the community's robustness in our health education program, emphasizing the importance of maintaining strong social connections for effective disease prevention. How would this k-component structure manifest in the Petersen graph, considering its reputation for remarkable connectivity and resilience?
### Response:
import networkx as nx

# Create a graph
G = nx.petersen_graph()

# Compute the k-component structure
k_components = nx.k_components(G)

print(k_components)
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