Influence of Underlying Random Walk Types in Population Models on Resulting Social Network Types and Epidemiological Dynamics
Description:
Epidemiologists rely on human interaction networks for determining states and dynamics of disease propagations in populations. However, such networks are empirical snapshots of the past. It will greatly benefit if human interaction networks are statistically predicted and dynamically created while an epidemic is in progress. We develop an application framework for the generation of human interaction networks and running epidemiological processes utilizing research on human mobility patterns and…
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Date:
December 2016
Creator:
Kolgushev, Oleg
Partner:
UNT Libraries