Talk at Complex Networks 2020 International Conference

1. Introduction: Risk map generation Consensus in networks Results and Conclusions
Using Distributed Risk Maps by Consensus as a
Complement to Contact Tracing Apps
M. Rebollo1,2, R.M. Benito2, J.C. Losada2, J. Galeano2
1VRAIN
Universitat Polit`ecnica de Val`encia
2GSC
Universidad Politecnica de Madrid
Complex Networks, Madrid 2020
c b a
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

2. Introduction: Risk map generation Consensus in networks Results and Conclusions
Problem
mixed feeling about sharing
data and trust
low adoption index
proposal: use close contact
network
What’s our goal?
Create a distributed map to alert people about the risk to get
infected by COVID
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

3. Introduction: Risk map generation Consensus in networks Results and Conclusions
Consensus process in networks
process to share informaci´on on
a network
xi (t + 1) =
xi (t) + ε j∈Ni
[xj(t) − xi (t)]
x(t + 1) = (I − εL)
P
x(t)
with L = DAG
− AG
information from direct
neighbors only
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

4. Introduction: Risk map generation Consensus in networks Results and Conclusions
Risk map generation by consensus
R = (0.0, 0.0, 0.0, 110.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0)
R =
(9.9, 10.1, 9.9, 9.9, 12.2, 11.3, 50.3, 55.6, 53.1, 15.4, 21.8, 9.9, 10.9, 10.1)
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

5. Introduction: Risk map generation Consensus in networks Results and Conclusions
Pilot project in La Gomera
simulation in La
Gomera island
3,000 participants
21,500 inhabitants
SEIR model for
propagation
two infection
steps/day
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

6. Introduction: Risk map generation Consensus in networks Results and Conclusions
Risk map obtained
Calculated risk map Actual risk map
(consensus) (complete)
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

7. Introduction: Risk map generation Consensus in networks Results and Conclusions
Effect in contagion
people do no enter in risky areas
people from risky areas do not go out
Effect
delay in propagation of infection
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

8. Introduction: Risk map generation Consensus in networks Results and Conclusions
RadarCovid Tracing app
20% 40% 60% 80%
High number of users (> 40%) to reduce the infections
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps

9. Introduction: Risk map generation Consensus in networks Results and Conclusions
Combined results
tracing + risk map
evaluation
lower bound
reducen to 20%
infected number
smoothed and
delayed
Conclusion
risk map as a complement to tracing apps
no threats to citizen’s privacy
@mrebollo VRAIN-GSC
Using Distributed Risk Maps by Consensus as a Complement to Contact Tracing Apps