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(2018.6.26)Prof. Haiyan Wang:Combining networks and partial differential equations to improve influenza predictions
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Update time: 2018-06-22
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Academy of Mathematics and Systems Science, CAS
Colloquia & Seminars

Speaker:

Prof. Haiyan Wang, Arizona State University , USA

Inviter:  
Title:
Combining networks and partial differential equations to improve influenza predictions
Time & Venue:
2018.6.26 16:00-17:00 N820
Abstract:
The ever-increasing availability of geospatial data now open the possibility to use spatio-temporal models to more accurately predict patterns of movement and trends in human activities, epidemic spread, environmental changes and many other natural phenomena. In this talk, we present an integrated framework for early detection of epidemic outbreaks based on real-time geo-tagged data in Twitter. We combine network theory, data mining and partial differential equation models to describe/predict patterns of epidemic spread at regional level. In addition, I will discuss a number of mathematical problems including free boundary value problems and bifurcation problems arising from these applications.
 

 

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