NDLI: Inferring Epidemic Network Topology from Surveillance Data

Content Provider	PubMed Central
Author	Wan, Xiang Liu, Jiming Cheung, William K. Tong, Tiejun
Editor	Vespignani, Alessandro
Copyright Year	2014
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.
Related Links	http://dx.doi.org/10.1371/journal.pone.0100661
Starting Page	100661
File Format	PDF
ISSN	19326203
e-ISSN	19326203
Journal	PLoS ONE
Issue Number	6
Volume Number	9
Language	English
Publisher	Public Library of Science
Publisher Date	2014-06-01
Access Restriction	Open
Rights Holder	Public Library of Science
Subject Keyword	Biochemistry, Genetics and Molecular Biology(all) Agricultural and Biological Sciences(all) Medicine(all) Research in Higher Education
Content Type	Text
Resource Type	Article
Subject	Multidisciplinary

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Inferring Social Network Structure from Bacterial Sequence Data

Inferring General Relations between Network Characteristics from Specific Network Ensembles

Inferring a Transcriptional Regulatory Network from Gene Expression Data Using Nonlinear Manifold Embedding

Inferring Phylogenies from RAD Sequence Data

Directed Partial Correlation: Inferring Large-Scale Gene Regulatory Network through Induced Topology Disruptions

Inferring Animal Densities from Tracking Data Using Markov Chains

Inferring Network Connectivity by Delayed Feedback Control

Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

Inferring patterns of influenza transmission in swine from multiple streams of surveillance data

Inferring Epidemic Network Topology from Surveillance Data

Similar Documents

Inferring Social Network Structure from Bacterial Sequence Data

Inferring General Relations between Network Characteristics from Specific Network Ensembles

Inferring a Transcriptional Regulatory Network from Gene Expression Data Using Nonlinear Manifold Embedding

Inferring Phylogenies from RAD Sequence Data

Directed Partial Correlation: Inferring Large-Scale Gene Regulatory Network through Induced Topology Disruptions

Inferring Animal Densities from Tracking Data Using Markov Chains

Inferring Network Connectivity by Delayed Feedback Control

Inferring Regulatory Networks from Expression Data Using Tree-Based Methods

Inferring patterns of influenza transmission in swine from multiple streams of surveillance data

Inferring Epidemic Network Topology from Surveillance Data