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

• Main Authors: Federico Baldassi (Author), Orlando Cenciarelli (Author), Andrea Malizia (Author), Pasquale Gaudio (Author)
• Format: Book
• Published: Elsevier, 2021-01-01T00:00:00Z.
• Subjects: article
• Online Access: Connect to this object online.
• Notes: 1876-0341; 10.1016/j.jiph.2020.11.014
• Keywords: Novel coronavirus; COVID-19; SARS-CoV-2; Infectious Diseases Seeker (IDS); Epidemiology; Infectious and parasitic diseases; RC109-216; Public aspects of medicine; RA1-1270
• Source: Journal of Infection and Public Health, Vol 14, Iss 1, Pp 123-130 (2021)

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.