Epidemic outbreaks with adaptive prevention on complex networks
Diogo H. Silva, Celia Anteneodo, Silvio C. Ferreira

TL;DR
This study models epidemic spread on complex networks considering adaptive preventive behaviors influenced by local and global epidemic awareness, revealing how perception and network heterogeneity affect outbreak mitigation.
Contribution
It introduces a dual-compartment SIR model with adaptive behavior based on local and global awareness, analyzing their effects through mean-field theory and simulations.
Findings
Local awareness significantly raises epidemic thresholds and delays peaks.
Increasing local perception rate reduces protected individuals but improves mitigation.
Network heterogeneity diminishes the effectiveness of local awareness mechanisms.
Abstract
The adoption of prophylaxis attitudes, such as social isolation and use of face masks, to mitigate epidemic outbreaks strongly depends on the support of the population. In this work, we investigate a susceptible-infected-recovered (SIR) epidemic model, in which the epidemiological perception of the environment can adapt the behavior of susceptible individuals towards preventive behavior. {Two compartments of susceptible individuals are considered, to distinguish those that adopt or not prophylaxis attitudes.} Two rules, depending on local and global epidemic prevalence, for the spread of the epidemic in heterogeneous networks are investigated. We present the results of both heterogeneous mean-field theory and stochastic simulations. The former performs well for the global rule, but misses relevant outcomes of simulations in the local case. In simulations, only local awareness can…
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Taxonomy
TopicsCOVID-19 epidemiological studies · Opinion Dynamics and Social Influence · Complex Network Analysis Techniques
