Active and inactive quarantine in epidemic spreading on adaptive activity-driven networks.
Phys Rev E
; 102(2-1): 020301, 2020 Aug.
Article
in English
| MEDLINE | ID: covidwho-798825
ABSTRACT
We consider an epidemic process on adaptive activity-driven temporal networks, with adaptive behavior modeled as a change in activity and attractiveness due to infection. By using a mean-field approach, we derive an analytical estimate of the epidemic threshold for susceptible-infected-susceptible (SIS) and susceptible-infected-recovered (SIR) epidemic models for a general adaptive strategy, which strongly depends on the correlations between activity and attractiveness in the susceptible and infected states. We focus on strong social distancing, implementing two types of quarantine inspired by recent real case studies an active quarantine, in which the population compensates the loss of links rewiring the ineffective connections towards nonquarantining nodes, and an inactive quarantine, in which the links with quarantined nodes are not rewired. Both strategies feature the same epidemic threshold but they strongly differ in the dynamics of the active phase. We show that the active quarantine is extremely less effective in reducing the impact of the epidemic in the active phase compared to the inactive one and that in the SIR model a late adoption of measures requires inactive quarantine to reach containment.
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Collection:
International databases
Database:
MEDLINE
Language:
English
Journal:
Phys Rev E
Year:
2020
Document Type:
Article
Affiliation country:
PhysRevE.102.020301
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