Epidemic Control Based on Fused Body Sensed and Social Network Information

Epidemic control becomes more difficult and challenging than ever due to increased population density and close social interactions. In this paper, we introduce a new information system named EPIC to predict epidemic conditions based on the continually collected vital signs of individuals from body sensor networks in a community and their social network. The core of EPIC is a critical network that models health conditions and social interactions of individuals. Facilitated by critical network, our prediction algorithms can cost-effectively determine quarantine strategies. The effectiveness of EPIC is evaluated through simulation.