Year: 2016
Type: conference-paper
Abstract: Disease transmission is a complex spatio-temporal process.A great number of approaches have been developed to predict influenza epidemics.Few of them have focused on the temporal dynamics of individual infected locations.Location networks, where locations are nodes and disease flows between them are links, provide a promising approach for such dynamic analyses, but also present challenges.In this study, we employ a deep learning approach to capture the dynamics of disease flows in location networks.We also analyze how the attributes of locations have an impact on the prediction accuracy via a sensitivity analysis.
Authors: Shiran Zhong, Ling Bian
Institution: University at Buffalo, State University of New York
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
OpenAlex ID: W2621641560