risk assessment from past temporal contacts...eugenio valdano vittoria colizza. backup asdfasdf....
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Risk Assessment from Past Temporal ContactsModelling Disease Spreading with Message Passing
Andreas Koher, Hartmut Lentz, Philipp Hövel
SIR – Type Outbreaks
SIR – Type Outbreaks
Temporal Contact Networkcatle trade in Germany 2010 – 2011 weighted, directed, daily resolution
Temporal Contact Networkcatle trade in Germany 2010 – 2011 weighted, directed, daily resolution
SIR – Model
Infection:
Recovery:
Temporal Contact Networkcatle trade in Germany 2010 – 2011 weighted, directed, daily resolution
SIR – Model
Goal1. Find a dynamical model
2. Linearize around disease free state2. Apply spectral properties to risk assessment
Infection:
Recovery:
asdfasdfModelling Disease Spreading
Example 1
A B
Two connected nodes
Undirected, unweighted, static
Example 1
A B
Two connected nodes
Undirected, unweighted, static
SI – Model
Discrete node state: Uniform transmission prob.Node A is infected with prob. 0.5 Node B is susceptible
α
S , I
Example 1: Monte – Carlo Simulation
A B
Example 1: Monte – Carlo Simulation
A B
Example 1: Quenched Mean Field
: Prob. b is susceptible
: Prob. b is infected
: Prob. b is recovered
: transmission prob.
: recovery prob.
Example 1: Quenched Mean Field
: Prob. b is susceptible
: Prob. b is infected
: Prob. b is recovered
: transmission prob.
: recovery prob.
Example 1: Quenched Mean Field
: Prob. b is susceptible
: Prob. b is infected
: Prob. b is recovered
: transmission prob.
: recovery prob.
Example 1: Quenched Mean Field
: Prob. b is susceptible
: Prob. b is infected
: Prob. b is recovered
: transmission prob.
: recovery prob.
Example 1: Quenched Mean Field
A B
Example 1: Quenched Mean Field
A B
Message Passing
...
Inferring the origin of an epidemic with a dynamic message-passing algorithmA. Y. Lokhov, M. Mézard, H. Ohta, and L. ZdeborováPhys. Rev. E 90.1, 012801 (2014)
Message passing approach for general epidemic modelsB. Karrer and M. E. J. NewmanPhys. Rev. E 80, 016101 (2010)
A B
C
Message Passing
...
Inferring the origin of an epidemic with a dynamic message-passing algorithmA. Y. Lokhov, M. Mézard, H. Ohta, and L. ZdeborováPhys. Rev. E 90.1, 012801 (2014)
Message passing approach for general epidemic modelsB. Karrer and M. E. J. NewmanPhys. Rev. E 80, 016101 (2010)
Features
1. Edge-based dynamics
2. Accounts for dynamical
correlations - echo chamber
effect
3. Exact on tree–topologies
A B
C
Message Passing
Key idea
„If B infects A, then B has been previously infected by
some neighbor “
...
Inferring the origin of an epidemic with a dynamic message-passing algorithmA. Y. Lokhov, M. Mézard, H. Ohta, and L. ZdeborováPhys. Rev. E 90.1, 012801 (2014)
Message passing approach for general epidemic modelsB. Karrer and M. E. J. NewmanPhys. Rev. E 80, 016101 (2010)
Features
1. Edge-based dynamics
2. Accounts for dynamical
correlations - echo chamber
effect
3. Exact on tree–topologies
A B
C
C≠A
Quenched Mean Field
Quenched Mean Field Message Passing
: b is susceptible given a is susceptible
: b is infected given a is susceptible
: No disease transmission from b to a
Example 1: Message Passing
A B
Example 1: Message Passing
A B
asdfasdfSpectral methods for risk estimation
Low prevalence limit
Linearisation around
disease free solution:
Low prevalence limit
Linearisation around
disease free solution:
A B
C
Low prevalence limit
Linearisation around
disease free solution:
Vectorisation with non-backtracking matrix:
Low prevalence limit
Linearisation around
disease free solution:
Propagator matrix
Vectorisation with non-backtracking matrix:
Spectral Condition for Global Oubreaks
Propagator matrix
Spectral Condition for Global Oubreaks
Propagator matrix
Global Outbreak Condition
: Non-Backtracking Matrix
Spectral Condition for Global Oubreaks
Propagator matrix
Global Outbreak Condition
: Non-Backtracking Matrix
Previous Result
: Adjacency Matrix
Valdano et al. Phys. Rev. X 5, 021005 (2015)
Example 2
α
Temporal Tree - Network
Construction Priciple:
1. Static backbone: undirected, unweighted tree2. One undirected edge → two directed edges3. Edges appears with a fixed prob. per time step
SIR – Model
Discrete node state: Uniform transmission prob.Uniform recovery prob.One initially infected node: Center
S , I , Rα
Tree Network: Quenched Mean FieldAverage Number of Infected and Recovered
Tree Network: Quenched Mean FieldAverage Number of Infected and Recovered
Tree Network: Monte - Carlo SimulationAverage Number of Infected and Recovered
Tree Network: Message PassingAverage Number of Infected and Recovered
Tree Network: Message PassingAverage Number of Infected and Recovered
SIR – Type OutbreaksTemporal Contact Network
catle trade in Germany 2010 – 2011 weighted, directed, daily resolution
SIR – Type OutbreaksTemporal Contact Network
catle trade in Germany 2010 – 2011 weighted, directed, daily resolution
SIR – Type OutbreaksTemporal Contact Network
catle trade in Germany 2010 – 2011 weighted, directed, daily resolution
Outbreak Condition
Critical transmission prob. for a
given recovery prob. Cattle trade in Germany from 2010 to 2011
Outbreak Condition
Critical transmission prob. for a
given recovery prob. Cattle trade in Germany from 2010 to 2011
Summary
Message Passing for epidemic modelling
Epidemic threshold based on the non-backtracking matrix
Summary
Message Passing for epidemic modelling
Epidemic threshold based on the non-backtracking matrix
Thank you… and
Philipp Hövel
Hartmut Lorenz
Eugenio Valdano
Vittoria Colizza
asdfasdfBackup
Comparison
Global Outbreak Condition
Critical transmission prob. for a given recovery prob.
0 0 0 0,01 0,01 0,01 0,01 0,01 0,02 0,02
Quenched Mean Field
Message Passing
Cattle trade in Germany from 2010 to 2011
Example 2
α
Temporal Tree - Network
Construction Priciple:
1. Static backbone: undirected, unweighted tree2. One undirected edge → two directed edges3. Edges appears with a fixed prob. per time step
SIR – Model
Discrete node state: Uniform transmission prob.Uniform recovery prob.One initially infected node: Center
S , I , Rα
β
Example 2: Monte - Carlo Simulation
Example 2: Quenched Mean Field
Example 2: Message Passing
Example 2: Message Passing (QMF)
Example 3
α
Complex temporal network
Hypertext Conference 2009 (Sociopaterns.org)Nodes:
SIR – Model
Discrete node state: Uniform transmission prob.Uniform recovery prob.One initially infected node
S , I , Rα
β
Example 3: Monte - Carlo Simulation
Example 3: Quenched Mean Field
Example 3: Quenched Mean Field