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On the use of clinical based infection data for pandemic case studies

  • Giuseppe Tradigo
  • , Patrizia Vizza
  • , Gabriel Gabriele
  • , Maria Mazzitelli
  • , Carlo Torti
  • , Mattia Prosperi
  • , Pietro Hiram Guzzi
  • , Pierangelo Veltri
  • eCampus University
  • Magna Græcia University
  • University of Florida

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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Abstract

Epidemiological models are relevant to study and analyze clinical as well as environmental and behavioural data, useful to support health studies. The target is to perform epidemiological analysis producing fast and reliable data access useful to guide prevention and curing processes. This is currently true in pandemic emergency as the current Covid-19 context. Epidemiological models should support in the early identification of pandemic phenomena and in making available data set for studying more accurate drug-based strategy for vaccines or virus containment.In this contribution we present an epidemiology database which integrates different types of clinical data to support research, follow-up and patient monitoring. The idea starts from an hospital databases cooperation integration where virus available data have been integrated to support statistical based studies. Starting from an available database containing 5 years data of infection related viruses (such as HPC, hepatitis) and patient anonymous data, the proposed system provide an integrated data access able to (i) extracting data filtered by means of clinical hypothesis based on patient profiles, environment and drugs and (ii) allowing to build large scale geographical data mappings in order to study correlations among chronic infection diseases and their relations with upcoming pandemic phenomena. Even if the application is in its infancy, the application is relevant with high very important applications.
Original languageEnglish
Title of host publicationProceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2313-2317
ISBN (Electronic)9781728162157
DOIs
Publication statusPublished - 16 Dec 2020
Externally publishedYes
Event2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020 - Virtual, Seoul, South Korea
Duration: 16 Dec 202019 Dec 2020

Publication series

NameProceedings - 2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020

Conference

Conference2020 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2020
Country/TerritorySouth Korea
CityVirtual, Seoul
Period16/12/202019/12/2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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