Co-evolution of behavioral attitudes and disease transmission on multilayer simplicial complexes

As global public health emergencies become more frequent, the role of higher-order interactions between individuals and environmental media in disease transmission has attracted significant attention. This study proposes a multilayer higher-order model based on simplicial complexes, incorporating the environmental infection rate from indirect contact to explore the interaction between individual behavioral attitude transitions and disease transmission. The critical threshold for disease transmission is derived using the microscopic Markov chain approach. Numerical results indicate that compared to the Barabási-Albert network, infection density in the Erdős-Rényi network increases more rapidly with the disease transmission rate, reaching saturation at lower transmission rates. When the probabilities of unaware or negative individuals transitioning to positive attitudes increase, the infection density decreases; conversely, the opposite situation increases the infection density. Moreover, a higher environmental infection rate increases the infection density and variations in delays. The introduction of environmental media reduces the influence of network topology on transmission dynamics. To effectively mitigate epidemic spreading, policymakers should prioritize environmental hygiene, particularly through strict cleaning and disinfection measures in public spaces and transportation systems. Additionally, public health campaigns should focus on raising awareness of healthy behaviors and encouraging individuals to adopt proactive preventive measures.