Evaluating a novel predictive tool for respiratory infection outbreaks in real life.

<bold>Introduction:</bold> Respiratory infections are a prevalent cause for individuals seeking medical guidance, remaining a public health threat, emphasizing the role of warning tools in managing health threats. <bold>Aims and objectives:</bold> Estimating Epidemic Volatility Index(EVI) as an early warning tool in real life. <bold>Methods:</bold> The study, ongoing since October 16th, includes adults presenting in our hospital with respiratory infection symptoms from whom nasal specimens are collected. We documented infections necessitating hospitalization and assessed the proportion attributed to specific viruses. EVI issues early warnings(red dots) on its online platform, illustrating in real time the correlation between successive red dots and the onset of new waves[1]. <bold>Results:</bold> Among 948 adults tested, positive tests were: 23.52 % Flu-A, 0.11% Flu-B, 18.46 % SARS-CoV-2, 2.43% RSV, 0.74% Adenovirus. 54.75% of total yielded negative test. Hospital admissions were 159(16.77%). Among them, 23.27% for Flu-A, 13.21% for SARS-CoV-2, 3.77% for RSV, 0.63% for Adenovirus. We observed a predominance of diagnosed cases (59.7%) over undiagnosed ones (40.3%) the Flu-A outbreak period(Fig 3). Synthesizing EVI’s figures and our results, we illustrate that the model issued a warning 14 days prior to the abrupt increase in Flu-A and SARS-CoV-2 positive cases, indicating the onset of new wave(Fig. 1,2). <bold>Conclusions:</bold> EVI’s timely alerts could aid healthcare systems in preparing for surges ensuring resources and staff availability. Overall, these tools enable rapid response, resource allocation, and international collaboration minimizing health crises impact. 1. Meletis et al, Infect. Public Health 2024 2. Papagiannis et al, Diseases 2023