Effective Epidemic Control and Source Tracing Through Mobile Social Sensing over WBANs

UMMS Affiliation

Department of Quantitative Health Sciences



Document Type



Bioinformatics | Communication Technology and New Media | Digital Communications and Networking | Health Communication | Health Information Technology | Public Health | Systems and Communications | Theory and Algorithms


Accurate and real-time tracing of epidemic sources is critical for epidemic origin analyses and control when outbreaks of epidemic diseases occur. Such tracing requires the simultaneous availability of information about social interactions among people as well as their body vital signs. Existing epidemic control methods are limited due to their inability to collect the above two types of information at the same time. In this paper, for the first time, we propose integrating wireless body area networks (WBANs) for body vital signs collection with mobile phones for social interaction sensing to achieve the desired epidemic source tracing. In particular, we design a mobile phone capability driven hierarchical social interaction detection framework integrated with WBANs. With this framework, we further propose a set of epidemic source tracing and control algorithms including genetic algorithm based search and dominating set identification algorithms to effectively identify epidemic sources and inhibit epidemic spread. We have also conducted extensive simulations, analyses, and case studies based on real data sets, which demonstrate the accuracy and effectiveness of our proposed solutions.


Citation: Zhang Z, Wang, H., Lin, X. Fang, H., Xuan, D. Effective Epidemic Control and Source Tracing Through Mobile Social Sensing over WBANs. Proc. IEEE INFOCOM, 2013, pp. 300-304. DOI 10.1109/INFCOM.2013.6566783. Link to article on publisher's site


Epidemic modeling, cost-effective epidemic control, wireless body area networks (WBAN), social networks, critical networks