TY - GEN
T1 - A complex systems approach to infectious disease surveillance and response
AU - SHI, Benyun
AU - Xia, Shang
AU - LIU, Jiming
N1 - Copyright:
Copyright 2014 Elsevier B.V., All rights reserved.
PY - 2013
Y1 - 2013
N2 - The transmission of infectious diseases can be affected by various interactive factors at or across different scales, such as environmental factors (e.g., temperature) and physiological factors (e.g., immunity). In view of this, to effectively and efficiently monitor and response to an infectious disease, it would be necessary for us to systematically model these factors and their impacts on disease transmission. In this paper, we propose a complex systems approach to infectious disease surveillance and response that puts a special emphasis on complex systems modeling and policy-level decision making with consideration of multi-scale interactive factors and/or surveillance data of disease prevalence. We demonstrate the implementation of our approach by presenting two real-world studies, one on the air-borne influenza epidemic in Hong Kong and the other on the vector-borne malaria endemic in Yunnan, China.
AB - The transmission of infectious diseases can be affected by various interactive factors at or across different scales, such as environmental factors (e.g., temperature) and physiological factors (e.g., immunity). In view of this, to effectively and efficiently monitor and response to an infectious disease, it would be necessary for us to systematically model these factors and their impacts on disease transmission. In this paper, we propose a complex systems approach to infectious disease surveillance and response that puts a special emphasis on complex systems modeling and policy-level decision making with consideration of multi-scale interactive factors and/or surveillance data of disease prevalence. We demonstrate the implementation of our approach by presenting two real-world studies, one on the air-borne influenza epidemic in Hong Kong and the other on the vector-borne malaria endemic in Yunnan, China.
KW - Complex systems modeling
KW - Data-driven computational intelligence
KW - Policy-level decision making
UR - http://www.scopus.com/inward/record.url?scp=84892927602&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-02753-1_53
DO - 10.1007/978-3-319-02753-1_53
M3 - Conference proceeding
AN - SCOPUS:84892927602
SN - 9783319027524
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 524
EP - 535
BT - Brain and Health Informatics - International Conference, BHI 2013, Proceedings
T2 - International Conference on Brain and Health Informatics, BHI 2013
Y2 - 29 October 2013 through 31 October 2013
ER -
