A Systematic Study of Mathematical Modeling for Sustainable Community-Based Disaster Risk Management

This study aimed to evaluate the application of mathematical modeling in sustainable community-based disaster risk management (CBDRM), paying particular attention to the incorporation of financial risk mitigation mechanisms such as insurance and community-based risk pooling. A structured literature search was conducted in the Scopus and ScienceDirect databases, followed by bibliometric and qualitative analysis of relevant studies in mathematics, economics, and disaster management. During the analysis, 17 peer-reviewed journal articles met the inclusion criteria and were examined based on publication trends, geographical distribution, modeling methods, and the extent to which financial protection mechanisms were incorporated into quantitative frameworks. The findings indicated growing academic interest in recent years and showed considerable methodological diversity, including stochastic optimization, vulnerability indices, agent-based simulations, and econometric models. Despite these advancements, major financial risk mitigation elements, such as premium design, fund management, and payout procedures, remained inadequately incorporated into existing modeling structures and were frequently addressed as separate analytical components. The focus on studies in high-income countries raised concerns about contextual applicability in climate-vulnerable and low-income regions. The review showed the need for more operationally incorporated modeling frameworks that connect quantitative risk assessment with community-level financial resilience strategies to support sustainable CBDRM.