Mathematical modeling of awareness-driven interventions for gender-based violence control in a closed population

Abstract

Gender-based violence (GBV) remains a critical global health issue with profound social, economic, and psychological implications. Despite concerted efforts to address this challenge, traditional intervention approaches often fall short of effectively mitigating its prevalence. In recent years, there has been growing recognition of the potential impact of awareness-based interventions in addressing various social and health crises. This paper introduces a modeling framework to explore the efficacy of awareness-based interventions in influencing the dynamics of the GBV epidemic within a closed population. A detailed sensitivity analysis, utilizing a normalized sensitivity index method, reveals that the violence transfer rate between perpetrators and at-risk individuals, the rate of transfer between violence-affected and violence-non-reconciled individuals, and the recruitment rate of the at-risk population exert the greatest influence on GBV dynamics. Furthermore, simulations have demonstrated that awareness interventions can significantly reduce the number of perpetrators and violence-affected individuals in the population, while increasing the proportion of individuals free from GBV.