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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.
Baldassi, Federico; Cenciarelli, Orlando; Malizia, Andrea; Gaudio, Pasquale.
  • Baldassi F; Department of Industrial Engineering, University of Rome "Tor Vergata", Italy. Electronic address: federico.baldassi@students.uniroma2.eu.
  • Cenciarelli O; International CBRNe Master Courses, University of Rome "Tor Vergata", Italy.
  • Malizia A; Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Italy.
  • Gaudio P; Department of Industrial Engineering, University of Rome "Tor Vergata", Italy.
J Infect Public Health ; 14(1): 123-130, 2021 Jan.
Artículo en Inglés | MEDLINE | ID: covidwho-1065353
ABSTRACT

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.
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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Vigilancia de la Población / Bases de Datos Factuales / SARS-CoV-2 / COVID-19 Tipo de estudio: Estudio experimental / Estudio observacional / Estudio pronóstico Límite: Humanos Idioma: Inglés Revista: J Infect Public Health Asunto de la revista: Enfermedades Transmisibles / Salud Pública Año: 2021 Tipo del documento: Artículo

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Texto completo: Disponible Colección: Bases de datos internacionales Base de datos: MEDLINE Asunto principal: Vigilancia de la Población / Bases de Datos Factuales / SARS-CoV-2 / COVID-19 Tipo de estudio: Estudio experimental / Estudio observacional / Estudio pronóstico Límite: Humanos Idioma: Inglés Revista: J Infect Public Health Asunto de la revista: Enfermedades Transmisibles / Salud Pública Año: 2021 Tipo del documento: Artículo