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Author (up) Nada Matta; Paul Henri Richard; Alain Hugerot; Theo Lebert pdf  isbn
  Title Experience Feedback Capitalization of Covid-19 Management in Troyes city Type Conference Article
  Year 2022 Publication ISCRAM 2022 Conference Proceedings – 19th International Conference on Information Systems for Crisis Response and Management Abbreviated Journal Iscram 2022  
  Volume Issue Pages 311-319  
  Keywords Experience feedback; MASK method; COVID19 crisis Management; actors’ relations formalization  
  Abstract All countries have to face the COVID’19 pandemic and its heavy consequences. This sanitary crisis differs from all others in terms of the quick spread of contaminations, the high number of deaths (more than 5,5 Million globally and 123,893 in France) and the accrued number of patients hospitalized and induced in intensive care units. All sanitary procedures have proven to be inadequate. Several actors at different levels, whether international, European, national and local, as well as at the level of public and private organizations have been involved in the management of this type of crisis. These actors deal with different aspects of it, i.e., health, people protection, and economic and social situations. Existing procedures revealed a big lack in the relationships between different local and departmental actors. We did a number of interviews with strategic actors addressing the COVID’19 crisis in the City of Troyes. The objective of these interviews is to identify lessons learned from their experience feedback about relational problems and modifications needed. We present in this paper the first results of this study.  
  Address University of Technology of Troyes; University of Technology of Troyes; Hospital of Simon Weil of Troyes; Orange Lab  
  Corporate Author Thesis  
  Publisher Place of Publication Tarbes, France Editor Rob Grace; Hossein Baharmand  
  Language English Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 2411-3387 ISBN 978-82-8427-099-9 Medium  
  Track AI and Intelligent Systems for Crises and Risks Expedition Conference  
  Notes Approved no  
  Call Number ISCRAM @ idladmin @ Serial 2420  
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