ICUBAM (Intensive Care Unit Bed Availability Monitoring) Intensive care unit bed availability monitoring and analysis in the Grand Est region of France during the COVID-19 epidemic

Reliable information is an essential component of responding to a sudden and large disease outbreak such as COVID-19, particularly with respect to critical care beds (CCBs) availability. This article presents: i) the development and construction of ICUBAM, a tool that collects in real-time and visua...

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সংরক্ষণ করুন:
গ্রন্থ-পঞ্জীর বিবরন
প্রকাশিত:URI:https://journals.openedition.org/statsoc,
প্রধান লেখক: ICUBAM, Consortium, Bonnasse-Gahot, Laurent, Dénès, Maxime, Dulac-Arnold, Gabriel, Girgin, Sertan, Husson, François, Iovene, Valentin, Josse, Julie, Kimmoun, Antoine, Landes, François, Nadal, Jean-Pierre, Primet, Romain, Quintao, Frederico, Raverdy, Pierre Guillaume, Rouvreau, Vincent, Teboul, Olivier, Yurchak, Roman
বিন্যাস: Article ou chapitre numérique
ভাষা:Anglais
প্রকাশিত: Statistique et société 2023
বিষয়গুলি:
অনলাইন ব্যবহার করুন:Accès Université d'Orléans et IFPM
Accès Université d'Orléans et IFPM
বিবরন
সংক্ষিপ্ত:Reliable information is an essential component of responding to a sudden and large disease outbreak such as COVID-19, particularly with respect to critical care beds (CCBs) availability. This article presents: i) the development and construction of ICUBAM, a tool that collects in real-time and visualizes information on CCB availability entered directly by intensivists; ii) an analysis and interpretation of the data collected over a 6-week period during the first wave of the epidemic in the hard-hit Grand Est region of France; iii) an analysis and interpretation of the data collected during the first wave of the epidemic in the Grand Est region; iv) the development of a medium and long term prediction using SEIR models, and a short term statistical model to predict the number of CCBs.Data ingested by ICUBAM were used to anticipate CCB shortages and predict future admissions. Most importantly, we demonstrate the importance of having a cross-functional team involving statisticians computer scientists and physicists working both with first-line medical responders and local health agencies and the importance of leveraging appropriate data. This allowed us to quickly implement effective tools to models the COVID-19 epidemic’s evolution and assist in critical decision-making processes.