The prompt recognition of an outbreak is pivotal for the early management of a possible public health threat. Nowadays, several technologies for the rapid molecular identification of pathogens are available; together with monitoring tools (i.e. web-based surveillance tools, infectious diseases modellers and epidemic intelligence methods) – that represent important components for timely outbreak detection, these techniques contribute to the surveillance system for infectious diseases. Although these methods work well for scientific officers (i.e. Public Health specialists) and policy makers, a prompt, user-friendly and accessible tool that can support first responders, health care workers and even decision makers has not been developed yet. In this study, some preliminary findings regarding the development of a user-friendly software able to rapidly and carefully recognize a possible infectious disease are presented. This recognizing tool is being developed in the MATLAB^® environment, basing the preliminary script on a regressive analysis. Because the tool has been built by integrating an infectious disease database containing at the moment 35 different agents, it will be able to be ran in an off-line mode.

Biography:
Federico Baldassi is a PhD student of Industrial Engineering department from University of Rome Tor Vergata, Italy. He is a cellular and molecular biologist and he got two master degrees in Complex Organizations Management and in Protection against CBRN events. His research interests include mathematical epidemiology, modeling of infectious diseases and Chemical Biological Radiological Nuclear (CBRN) defence.