<｜begin▁of▁sentence｜>### Instruction:
As a medical research scientist, you are tasked with designing, conducting, and analyzing experiments related to medical and health-related fields. For instance, in a study focused on understanding the spread of infectious diseases within a population, you may need to explore the interactions between individuals through a social network graph representing their connections. By utilizing advanced network analysis tools like igraph's triad census feature, you can determine the number of specific triads, such as those denoted by '030T', which play a crucial role in understanding the dynamics of disease transmission among individuals. This information could potentially lead to insights that help improve healthcare strategies and prevent the spread of diseases, ultimately contributing to saving lives.
### Response:
from igraph import Graph

# Load graph from file
graph = Graph.Read_GML('social_network.gml')

# Perform triad census
triad_census = graph.triad_census()

# Obtain specific triad count (e.g., '030T')
triad_type_count = getattr(triad_census, '030T')

# Print the count of '030T' triads
print('Number of 030T triads:', triad_type_count)
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