The Mathematics of Infectious Diseases
SIAM Review
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Inoculation strategies for victims of viruses and the sum-of-squares partition problem
Journal of Computer and System Sciences
A measurement-driven analysis of information propagation in the flickr social network
Proceedings of the 18th international conference on World wide web
Learning influence probabilities in social networks
Proceedings of the third ACM international conference on Web search and data mining
MASS '11 Proceedings of the 2011 IEEE Eighth International Conference on Mobile Ad-Hoc and Sensor Systems
Mobile Data Offloading through Opportunistic Communications and Social Participation
IEEE Transactions on Mobile Computing
Mobile phone based social relationship identification for target vaccination in mobile healthcare
Proceedings of the Third International Workshop on Sensing Applications on Mobile Phones
A community based vaccination strategy over mobile phone records
Proceedings of the Second ACM Workshop on Mobile Systems, Applications, and Services for HealthCare
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This work explores the use of social communications for epidemic disease control. Since the most infectious diseases spread through human contacts, we focus on modeling the diffusion of diseases by analyzing the social relationship among individuals. In other words, we try to capture the interaction pattern among human beings using the social contact information, and investigate its impact on the spread of diseases. Particularly, we investigate the problem of minimizing the expected number of infected persons by treating a small fraction of the population with vaccines. We prove that this problem is NP-hard, and propose an approximate algorithm representing a preventive disease control strategy based on the social patterns. Simulation results confirm the superiority of our strategy over existing ones.