title: Inferring epidemic network topology from surveillance data.
abstract: The transmission of infectious diseases can be affected by many or even hidden factors, making it difficult to accurately predict when and where outbreaks may emerge. One approach at the moment is to develop and deploy surveillance systems in an effort to detect outbreaks as timely as possible. This enables policy makers to modify and implement strategies for the control of the transmission. The accumulated surveillance data including temporal, spatial, clinical, and demographic information, can provide valuable information with which to infer the underlying epidemic networks. Such networks can be quite informative and insightful as they characterize how infectious diseases transmit from one location to another. The aim of this work is to develop a computational model that allows inferences to be made regarding epidemic network topology in heterogeneous populations. We apply our model on the surveillance data from the 2009 H1N1 pandemic in Hong Kong. The inferred epidemic network displays significant effect on the propagation of infectious diseases.
authors: Department of Computer Science and Institute of Theoretical and Computational Study, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
authors: Xiang
authors: X
authors: Wan
authors: Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
authors: Jiming
authors: J
authors: Liu
authors: Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
authors: William K
authors: WK
authors: Cheung
authors: Department of Mathematics and Institute of Theoretical and Computational Study, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
authors: Tiejun
authors: T
authors: Tong
mesh_terms: D000328:Adult; D002648:Child; D004196:Disease Outbreaks; D062665:Epidemiological Monitoring; D006723:Hong Kong / Q000453:epidemiology; D006801:Humans; D053118:Influenza A Virus, H1N1 Subtype / Q000502:physiology; D007251:Influenza, Human / Q000453:epidemiology* / Q000635:transmission; D008390:Markov Chains; D015233:Models, Statistical