Abstract for: A Dynamic Model of Workforce Management During Seasonal Epidemics

Seasonal epidemics pose a recurring threat to organizational stability by reducing workforce availability and disrupting operational continuity. This study presents a dynamic modeling framework that adapts the classical Susceptible-Infected-Recovered (SIR) model to organizational settings, allowing for the evaluation of managerial policies under varying levels of infectivity, disease severity, and sick leave culture. Simulation experiments demonstrate that proactive leave policies—particularly those targeting mildly infected employees who continue to work—can significantly reduce infection spread and cumulative workday losses. However, the effectiveness of such interventions is highly dependent on epidemic characteristics and cultural attitudes toward presenteeism. The findings underscore a critical trade-off between capacity reductions due to absenteeism and increased transmission risk from infected attendance, highlighting the importance of adaptive, data-driven workforce management strategies. By offering a decision-support tool for simulating diverse epidemic scenarios, this study equips organizations with actionable insights to safeguard employee health, maintain operational continuity, and enhance resilience against seasonal epidemic threats.