TY - GEN
T1 - Enhancing syndromic surveillance through autonomie health grids
AU - Arora, Hina
AU - Vinze, Ajay
AU - Santanam, Raghu
AU - Brittenham, Peter
PY - 2005
Y1 - 2005
N2 - The Centers for Disease Control defines syndromic surveillance as, an investigational approach where health department staff, assisted by automated data acquisition and generation of statistical alerts, monitor disease indicators in real-time or near real-time to detect outbreaks of disease earlier than would otherwise be possible with traditional public health methods (CDC, 2004). While syndromic surveillance has traditionally been used in the context of detecting natural outbreaks, it is increasingly being used to develop systems to detect bioterrorism outbreaks. Timely response to a bioterrorism event requires accurate information exchange between clinicians and public health officials. This entails building highly complex surveillance systems that provide access to heterogeneous/distributed medical data, computational resources and collaborative services, for real-time decision making in a highly reliable and secure environment. In this paper we propose enhancing syndromic surveillance through grid and autonomie computing augmentations, and present our approach to a proof of concept modeling and simulation environment.
AB - The Centers for Disease Control defines syndromic surveillance as, an investigational approach where health department staff, assisted by automated data acquisition and generation of statistical alerts, monitor disease indicators in real-time or near real-time to detect outbreaks of disease earlier than would otherwise be possible with traditional public health methods (CDC, 2004). While syndromic surveillance has traditionally been used in the context of detecting natural outbreaks, it is increasingly being used to develop systems to detect bioterrorism outbreaks. Timely response to a bioterrorism event requires accurate information exchange between clinicians and public health officials. This entails building highly complex surveillance systems that provide access to heterogeneous/distributed medical data, computational resources and collaborative services, for real-time decision making in a highly reliable and secure environment. In this paper we propose enhancing syndromic surveillance through grid and autonomie computing augmentations, and present our approach to a proof of concept modeling and simulation environment.
KW - Autonomie computing
KW - Grid computing
KW - Syndromic surveillance
UR - http://www.scopus.com/inward/record.url?scp=84869999949&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84869999949&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:84869999949
SN - 9781604235531
T3 - Association for Information Systems - 11th Americas Conference on Information Systems, AMCIS 2005: A Conference on a Human Scale
SP - 2091
EP - 2096
BT - Association for Information Systems - 11th Americas Conference on Information Systems, AMCIS 2005
T2 - 11th Americas Conference on Information Systems, AMCIS 2005
Y2 - 11 August 2005 through 15 August 2005
ER -