Co-spreading dynamics of smoking behavior and awareness on social contact networks

TL;DR

This paper models how smoking behavior and awareness co-spread through social networks, revealing how social influence and network structure affect smoking prevalence and intervention effectiveness.

Contribution

It introduces a coupled contagion model for smoking and awareness, integrating social influence, behavioral change, and network structure, which advances understanding of intervention strategies.

Findings

Awareness can significantly reduce smoking prevalence.

Network heterogeneity influences intervention success.

Structured contact patterns affect awareness spread and smoking dynamics.

Abstract

Smoking behavior and awareness co-spread through social interactions, giving rise to coupled contagion processes on social contact networks. In addition to initiation and cessation, awareness of the harmful effects of smoking plays an important role in shaping individual behavior and population-level outcomes. In this work, we develop a mathematical model to study the coupled dynamics of smoking behavior, quitting, and awareness in a population. A deterministic framework based on ordinary differential equations is first formulated to capture the interplay between social influence and awareness-driven behavioral change. Analysis of the model reveals the existence of smoking-free and smoking-endemic steady states, and identifies conditions under which awareness can reduce or suppress the persistence of smoking. Since social interactions are often localized rather than well mixed, the mean-field description is then extended to a network-based model that incorporates structured contact patterns. Numerical simulations performed on empirical social networks indicate that contact heterogeneity and localized awareness spreading can influence the effectiveness of interventions. Our findings underscore the importance of population structure when devising awareness-based intervention strategies for smoking cessation.