Infectious Diseases Seeker (IDS): An Innovative Tool for Prompt Identification of Infectious Diseases during Outbreaks.

BACKGROUND: Several technologies for rapid molecular identification of pathogens are currently available; jointly with monitoring tools (i.e., web-based surveillance tools, infectious diseases modelers, and epidemic intelligence methods), 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 competences 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. METHODS: This paper presents the work performed to implement and test an innovative tool for prompt identification of infectious diseases during outbreaks, called Infectious Diseases Seeker (IDS). IDS is a standalone software that runs on the most common operative systems. It has been built by integrating a database containing an interim set of 60 different disease causative agents and COVID-19 data and is able to work in an off-line mode without requiring a network connection. RESULTS: IDS has been applied in a real and complex scenario in terms of concomitant infectious diseases (yellow fever, COVID-19, and Lassa fever), as can be in the second part of 2020 in Nigeria. The outcomes have allowed inferring that yellow fever (YF), and not Lassa fever, was affecting the area under investigation. CONCLUSIONS: Our result suggests that a tool like IDS could be valuable for the quick and easy identification and discrimination of infectious disease outbreaks even when concurrent outbreaks occur, like for the case study of YF and COVID-19 pandemic in Nigeria.

Testing the identification effectiveness of an unknown outbreak of the Infectious Diseases Seeker (IDS) using and comparing the novel coronavirus disease (COVID-19) outbreak with the past SARS and MERS epidemics.

BACKGROUND: The aim of this research is to assess the predictive accuracy of the Infectious Diseases Seeker (IDS) - an innovative tool for prompt identification of the causative agent of infectious diseases during outbreaks - when field epidemiological data collected from a novel outbreak of unknown origin are analysed by the tool. For this reason, it has been taken into account the novel coronavirus disease (COVID-19) outbreak, which began in China at the end of December 2019, has rapidly spread around the globe, and it has led to a public health emergency of international concern (PHEIC), declared to the 30th of January 2020 by the World Health Organization (WHO). METHODS: The IDS takes advantage of an off-line database, built before the COVID-19 pandemic, which represents a pivotal characteristic for working without an internet connection. The software has been tested using the epidemiological data available in different and progressive stages of the COVID-19 outbreak. As a comparison, the results of the tests performed using the epidemiological data from the Severe Acute Respiratory Syndrome coronavirus (SARS-CoV) epidemic in 2002 and Middle East Respiratory Syndrome coronavirus (MERS-CoV) epidemic in 2012, are shown. RESULTS: The overall outcomes provided by the software are comforting, as a matter of the fact that IDS has identified with a good accuracy the SARS and MERS epidemics (over 90%), while, as expected, it has not provided erroneous and equivocal readings after the elaboration COVID-19 epidemic data. CONCLUSIONS: Even though IDS has not recognized the COVID-19 epidemic, it has not given to the end user a false result and wrong interpretation, as expected by the developers. For this reason, IDS reveals itself as useful software to identify a possible epidemic or outbreak. Thus, the intention of developers is to plan, once the software will be released, dedicated updates and upgrades of the database (e.g., SARS-CoV-2) in order to keep this tool increasingly useful and applicable to reality.