Analysis of epidemic dynamics: Incorporating PRCC in SIRS model with control strategies and environmental fluctuations

The present article examines the global characteristics of a generalized SIHRS (susceptible-infected-hospitalized-recovered-susceptible) epidemic model. This investigation incorporates the influence of government policies, public responses, and social behavioral reactions. We also analyze how environmental fluctuations and time-dependent control strategies affect the dynamics of disease spread. For deterministic model, these findings indicate that the disease will spread within the population if basic reproduction number exceeds 1. Sensitivity analysis is employed using Latin hypercube sampling method to evaluate the impact of model parameters on disease spread. Subsequently, Kendall’s tau and Spearman’s rank correlation coefficients are computed to gain deeper insights. The findings indicate that early government action during a disease outbreak effectively accelerates the occurrence of a disease-free state. Additionally, a crucial finding of this study is that random fluctuations can help to prevent disease outbreaks, paving the way for effective control techniques to manage disease dynamics. The combination of governmental actions and total number of hospital beds proves to be an effective control strategy in this model. Our results show that implementing these strategies significantly reduces the disease burden.