Epidemic propagation dynamic on the higher-order multilayer network

Multilayer networks provide a new perspective for studying the dynamics of epidemic spread. Based on the Susceptible-Asymptomatic infected-Reported infected-Unreported infected-Quarantine-Recovered ( S A I U Q R ) compartmental model for epidemic transmission on higher-order networks, this paper constructs a three-layer multiplex network model that couples information-driven awareness diffusion and epidemic transmission. We have utilized the Microscopic Markov Chain Approach (MMCA) to calculate the epidemic threshold under the influence of higher-order structures and explored the impact of model parameters on the proportion of infected individuals, aware individuals and the epidemic threshold. Furthermore, we fit the actual COVID-19 data from four states in India to our model, validating the effectiveness of the model in practical applications, and provide epidemic prevention measures recommendations for each state based on the fitted parameter values.