<｜begin▁of▁sentence｜>### Instruction:
Imagine we are mapping the transmission pathways of a recent outbreak within a population, and to better understand the progression of the infection, we've constructed a graphical model. This model is composed of nodes representing individuals and directed edges indicating the direction of disease transmission. The current dataset, tracking the primary cases, includes the following transmission events: Patient 1 to Patient 2, Patient 1 to Patient 3, and Patient 3 to Patient 2. To ensure rigorous analysis and appropriate intervention strategies, it's essential to confirm that this spread pattern, when represented in our epidemiologic modeling software, does not form any cyclic pathways, which would be inconsistent with the nature of this infectious disease. Could our model, which takes the form of a directed graph as per the recorded transmission events, be validated as a directed acyclic graph using NetworkX tools? This confirmation is crucial because it supports the temporal sequence of transmissions and the hypothesis that each infection is derived from a single preceding case.
### Response:
import networkx as nx

# Create a directed graph
G = nx.DiGraph()

# Add edges
G.add_edge(1, 2)
G.add_edge(1, 3)
G.add_edge(3, 2)

# Check if the graph is a directed acyclic graph (DAG)
is_dag = nx.is_directed_acyclic_graph(G)

print('Is the graph a DAG?', is_dag)
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