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SUMMARY:CNN Seminar - Epidemics over Mobile Phone Networks -  Dr Katayoun 
 Farrahi\, Goldsmiths\, University of London
DTSTART:20150310T163000Z
DTEND:20150310T173000Z
UID:TALK58299@talks.cam.ac.uk
CONTACT:Petra Vertes
DESCRIPTION:Human interactions sensed ubiquitously by mobile phones can im
 prove a significant number of public health problems\, particularly helpin
 g to track the spread of disease. In this talk\, we evaluate multiple aven
 ues for the integration of high-resolution face to face Bluetooth-sensed i
 nteraction networks into epidemic models. Our goal is to evaluate the capa
 city of the different avenues of integration to track the spread of season
 al influenza on a real-world community of 72 individuals over a period of 
 17 weeks. The dataset considered contains real-time tracking of individual
  flu symptoms over the whole observation period\, providing a concrete ind
 ividualized source for evaluation. We present two different studies on thi
 s dataset. The first considers the standard SIR model simulated over real 
 network dynamics with the overall goal of predicting the real infections o
 ver time. We obtain an error of less than 2 infected people on average whe
 n predicting the total number of individuals affected by the flu and a pre
 cision of approximately 30% when predicting exactly which individual will 
 become infected at a given time. Our results indicate that high-resolution
  mobile phone data can increase the predictive power of even the simplest 
 of epidemic models. The second study proposes a dual model for contact tra
 cing\, where an infection is spreading in the physical interpersonal netwo
 rk\, which we assume can never be fully recovered\, and contact tracing is
  occurring in a communication network which acts as a proxy for the first.
  Our results suggest that contact tracing via mobile phone communication m
 ay be a viable option for controlling contagious outbreaks.\n
LOCATION:Keynes Hall in King's College
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