Infectious diseases seeker (IDS): an innovative tool for prompt identification of infectious diseases during outbreaks

The rapid detection of an ongoing outbreak – and the identification of the causative pathogen – is pivotal for the early recognition of public health threats. Emergence and re-emergence of infectious diseases is linked to several determinants, both human factors – such as population density, travel, and trade – and ecological factors – like climate change and agricultural practices. Several technologies are available for the rapid molecular identification of pathogens (e.g. RT-Real Time PCR), and together with on line monitoring tools of infectious disease activity and behaviour, they contribute to the surveillance system for infectious diseases. Web-based surveillance tools, infectious diseases modelling and epidemic intelligence methods represent crucial components for timely outbreak detection and rapid risk assessment. They represent important components for timely outbreak detection and identification of the involved pathogen. The application of these approaches is usually feasible and effective when performed by healthcare professionals with specific expertise and skills and when data and resources are easily accessible. Contrariwise, in the field situation where healthcare workers or first responders from heterogeneous competencies can be asked to investigate an outbreak of unknown origin, a simple and suitable tool for rapid agent identification and appropriate outbreak management is highly needed. Most especially when time is limited, available data are incomplete, and accessible infrastructure and resources are inadequate. The use of a prompt, user-friendly, and accessible tool able to rapidly recognize an infectious disease outbreak and with high sensitivity and precision may be a game-changer to support emergency response and public health investigations. The aim of this project is to integrate the current prevention and control system with a prediction tool for infectious disease, based on regressive analysis, to supports decision makers, health care workers and first responders to quickly and properly recognise an outbreak. The development of this infectious disease regressive prediction tool has been made in MATLAB® environment. It works with an offline database built with specific epidemiological parameters of a set of infectious diseases of high consequences. The tool is a standalone software called Infectious Diseases Seeker (IDS). The final perspective about this software regards the developing of that tool as useful and userfriendly predictive tool appropriate for first responders, health care workers and public health decision makers to help them in predicting, assessing and contrasting outbreaks.