Discovering dynamic patterns from infectious disease data using dynamic mode decomposition.

ABSTRACT:

Background

The development and application of quantitative methods to understand disease dynamics and plan interventions is becoming increasingly important in the push toward eradication of human infectious diseases, exemplified by the ongoing effort to stop the spread of poliomyelitis.

Methods

Dynamic mode decomposition (DMD) is a recently developed method focused on discovering coherent spatial-temporal modes in high-dimensional data collected from complex systems with time dynamics. The algorithm has a number of advantages including a rigorous connection to the analysis of nonlinear systems, an equation-free architecture, and the ability to efficiently handle high-dimensional data.

Results

We demonstrate the method on three different infectious disease sets includi

SUBMITTER: Proctor JL 

PROVIDER: S-EPMC4379984 | biostudies-literature | 2015 Mar

REPOSITORIES: biostudies-literature