Epidemic Control Based on Fused Body Sensed and Social Network Information

Author

Zhang, Zhaoyang ; Lee, Ken C K ; Wang, Honggang ; Xuan, Dong ; Fang, Hua

Author_Institution

Univ. of Massachusetts Dartmouth, Dartmouth, MA, USA

fYear

2012

fDate

18-21 June 2012

Firstpage

285

Lastpage

290

Abstract

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.

Keywords

body sensor networks; epidemics; health care; medical information systems; EPIC; body sensor network; epidemic condition prediction; epidemic control; fused body sensed network information; health condition; information system; social interaction; social network information; vital signs; Diseases; Educational institutions; Estimation; Prediction algorithms; Predictive models; Smart phones; Social network services; Algorithm; Body Sensor; Critical Network; Epidemic Control; Evaluation; Model; Social Network;

fLanguage

English

Publisher

ieee

Conference_Titel

Distributed Computing Systems Workshops (ICDCSW), 2012 32nd International Conference on

Conference_Location

Macau

ISSN

1545-0678

Print_ISBN

978-1-4673-1423-7

Type

conf

DOI

10.1109/ICDCSW.2012.85

Filename

6258169