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Temporal network structure of human contact patterns and its implication for disease dynamics and control Petter Holme, Umeå University with Luis EC Rocha, Sungmin Lee, Fredrik Liljeros. Network theory 101. Network theory 101. Network theory 101. Network theory 101. Temporal effects.

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Temporal network structure of human contact patterns and its implication for disease dynamics and controlPetter Holme, Umeå Universitywith Luis EC Rocha, Sungmin Lee, Fredrik Liljeros


Network theory 101
Network theory 101 implication for disease dynamics and control


Network theory 1011
Network theory 101 implication for disease dynamics and control


Network theory 1012
Network theory 101 implication for disease dynamics and control


Network theory 1013
Network theory 101 implication for disease dynamics and control


Temporal effects
Temporal effects implication for disease dynamics and control


Temporal effects1
Temporal effects implication for disease dynamics and control


What we are interested in
What we are interested in implication for disease dynamics and control

  • What kind of relevant temporal /topological structures are there? Why?

  • How does temporal structures in empirical networks affect disease spreading?

  • Can we exploit these structures to slow down disease spreading?


Our datasets
Our datasets implication for disease dynamics and control

  • E-mail: 3,188 nodes, 309,125 contacts over 83 days

  • Internet dating: 29,341 nodes, 536,276 contacts over 512 d

  • Hospital: 295,107 nodes, 64,625,283 contacts over 8,521 d

  • Prostitution: 16,730 nodes, 50,632 contacts over 2,232 d


Worst case scenario vs null model
Worst case scenario implication for disease dynamics and controlvs. null-model


Threshold in transmission probability implication for disease dynamics and control


Threshold in disease dynamics implication for disease dynamics and control


Two stage HIV model implication for disease dynamics and control


A society-wide context implication for disease dynamics and control


Half time summary implication for disease dynamics and control

  • Temporal correlations speed up the outbreaks on a short time scale & slows it down on a longer time scale

  • Temporal effects create distinct and comparatively high epidemic thresholds

  • HIV can not spread in the prostitution data alone and probably does not serve as a reservoir of HIV in a society-wide perspective


Temporal vaccination strategies implication for disease dynamics and control

Simulation setup


Temporal vaccination strategies implication for disease dynamics and control

Simulation setup


Temporal vaccination strategies implication for disease dynamics and control

Strategy “Recent”


Temporal vaccination strategies implication for disease dynamics and control

Strategy “Weight”


Relative efficiency, worst case implication for disease dynamics and control


Relative efficiency, SIR model implication for disease dynamics and control


Explanatory model implication for disease dynamics and control


Summary implication for disease dynamics and control

  • Temporal correlations do affect disease spreading and can be exploited in targeted vaccination

  • The best vaccination strategy depends on the type of temporal structure

  • Until more structural information is available, we recommend the strategy Recent


Thank implication for disease dynamics and control

You!

March 28 – April 20

nordita.org/network2011

deadline March 10

http://www.tp.umu.se/~holme/


SI model, implication for disease dynamics and controlvsρ = 1


Parameter dependence, relative efficiency implication for disease dynamics and control


Outbreak diversity implication for disease dynamics and control


Contact sequence implication for disease dynamics and controlvs other types of models


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