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The study of the spread of diseases in actual populations represents a topic of vital importance. Compartmentales models, assume homogeneity in the interactions of the individuals. Nevertheless, the existing heterogeneities in the complex networks of interaction in real populations, present effects that cannot be understood by compartmentales models. The present paper uses the networks of social interaction (physical proximity) between the students of the Engineering Department of the University de Los Andes, to study the epidemiological vulnerability of thestudents population on each semeste. Additionally, by simulating flu-like diseases on these populations, we propose immunization and control strategies based on attributes that are innate of the networked population. The results of this investigation show that there exist, under this methodology, methods of prevention of diseases more efficient than the ones …