This paper describes a pilot application of the Epidemic Volatility Index (EVI) to data from the pulmonary clinic of the University Hospital of Thessaly, Greece, for monitoring respiratory infections, COVID-19, and flu cases. EVI, a simple and easily implemented early warning method based on the volatility of newly reported cases, exhibited consistent and stable performance in detecting new waves of epidemics. The study highlights the importance of implementing early warning tools to address the effects of epidemics, including containment of outbreaks, timely intervention strategies, and resource allocation within real-world clinical settings as part of a broader public health strategy.The results presented in the figures demonstrate the association between successive early warnings and the onset of new waves, providing valuable insights for proactive decision-making. A web-based application enabling real-time monitoring and informed decision-making by healthcare professionals, public health officials, and policymakers was developed.This study emphasizes the significant role of early warning methods in managing epidemics and safeguarding public health. Future research may explore extensions and combinations of multiple warning systems for optimal outbreak interventions and application of the methods in the context of personalized medicine.