TY - GEN
T1 - Active Risk Aversion in SIS Epidemics on Networks
AU - Bizyaeva, Anastasia
AU - Arango, Marcela Ordorica
AU - Zhou, Yunxiu
AU - Levin, Simon
AU - Leonard, Naomi Ehrich
N1 - Publisher Copyright: © 2024 AACC.
PY - 2024
Y1 - 2024
N2 - We present and analyze an actively controlled SIS (actSIS) model of interconnected populations to study how risk aversion strategies affect network epidemics. A population using a risk aversion strategy reduces its contact rate with other populations when it perceives an increase in infection risk. The network actSIS model relies on two distinct networks. One is a physical network that defines which populations come into contact with which others, thus how infection spreads. The other is a communication network, such as an online social network, that defines which populations observe the infection level of which others, thus how information spreads. We prove that the system exhibits a transcritical bifurcation where an endemic equilibrium (EE) emerges. For regular graphs, we prove that the endemic infection level is uniform across populations and reduced by the risk aversion strategy, relative to the network SIS endemic level. We show that when communication is sufficiently sparse, this initially stable EE loses stability in a secondary bifurcation. Simulations show that a new stable solution emerges with nonuniform infection levels.
AB - We present and analyze an actively controlled SIS (actSIS) model of interconnected populations to study how risk aversion strategies affect network epidemics. A population using a risk aversion strategy reduces its contact rate with other populations when it perceives an increase in infection risk. The network actSIS model relies on two distinct networks. One is a physical network that defines which populations come into contact with which others, thus how infection spreads. The other is a communication network, such as an online social network, that defines which populations observe the infection level of which others, thus how information spreads. We prove that the system exhibits a transcritical bifurcation where an endemic equilibrium (EE) emerges. For regular graphs, we prove that the endemic infection level is uniform across populations and reduced by the risk aversion strategy, relative to the network SIS endemic level. We show that when communication is sufficiently sparse, this initially stable EE loses stability in a secondary bifurcation. Simulations show that a new stable solution emerges with nonuniform infection levels.
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U2 - 10.23919/ACC60939.2024.10644997
DO - 10.23919/ACC60939.2024.10644997
M3 - Conference contribution
T3 - Proceedings of the American Control Conference
SP - 4428
EP - 4433
BT - 2024 American Control Conference, ACC 2024
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2024 American Control Conference, ACC 2024
Y2 - 10 July 2024 through 12 July 2024
ER -