Assessing infectious disease simulation in combat zones through capacity, vulnerability, and risk framework

Introduction. Infectious disease modelling is crucial in managing disease spread, particularly in conflict zones where health systems and infrastructure are severely compromised. However, applying these models in unstable environments, such as during the ongoing Russian invasion invasion in Ukraine, presents unique challenges that require adapted approaches. Purpose. This study aims to evaluate the effectiveness of infectious disease simulation models in conflict zones using the Capacity, Vulnerability, and Risk Assessment (CVRA) framework, specifically focusing on the impact of the russian invasion in Ukraine. Materials and Methods. The CVRA framework assessed the capabilities, vulnerabilities, and risks of using infectious disease models in conflict settings. The framework's three components were used to evaluate the resources, susceptibility factors comprehensively, and threats affecting the success of infectious disease simulations in combat-affected areas. Results. The results highlight the strengths and limitations of using disease models during conflict. Ukraine's digital infrastructure and international collaboration provide a basis for disease simulation implementation. However, significant challenges remain due to healthcare disruptions, data quality issues, logistical barriers, and population vulnerabilities resulting from mass displacement and other factors. The CVRA framework provided a structured approach to understanding these factors and optimizing intervention strategies. Conclusions. This study demonstrates the potential for applying infectious disease models in conflict settings but emphasizes the need for substantial adaptation to address the challenges specific to such environments. The CVRA framework is valuable for systematically assessing and enhancing public health interventions in combat zones. The study's findings provide insights that can be transferred to other conflict-affected areas, although limitations in data availability and ethical concerns must be addressed in future work.