Your browser doesn't support javascript.
A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic.
Manca, Davide; Caldiroli, Dario; Storti, Enrico.
  • Manca D; PSE-Lab, Process Systems Engineering Laboratory, Dipartimento di Chimica, Materiali e Ingegneria Chimica "Giulio Natta", Politecnico di Milano - Piazza Leonardo da Vinci 32, 20133 Milano, Italy.
  • Caldiroli D; Neuroanestesia e Rianimazione Fondazione IRCCS Istituto Neurologico Carlo Besta, Milano, Italy.
  • Storti E; Anesthesia and ICU Department Maggiore Hospital, ASST Lodi, Lodi, Italy.
Comput Chem Eng ; 140: 106945, 2020 Sep 02.
Article in English | MEDLINE | ID: covidwho-526543
ABSTRACT
The different stages of Covid-19 pandemic can be described by two key-variables ICU patients and deaths in hospitals. We propose simple models that can be used by medical doctors and decision makers to predict the trends on both short-term and long-term horizons. Daily updates of the models with real data allow forecasting some key indicators for decision-making (an Excel file in the Supplemental material allows computing them). These are beds allocation, residence time, doubling time, rate of renewal, maximum daily rate of change (positive/negative), halfway points, maximum plateaus, asymptotic conditions, and dates and time intervals when some key thresholds are overtaken. Doubling time of ICU beds for Covid-19 emergency can be as low as 2-3 days at the outbreak of the pandemic. The models allow identifying the possible departure of the phenomenon from the predicted trend and thus can play the role of early warning systems and describe further outbreaks.
Keywords

Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Comput Chem Eng Year: 2020 Document Type: Article Affiliation country: J.compchemeng.2020.106945

Similar

MEDLINE

...
LILACS

LIS


Full text: Available Collection: International databases Database: MEDLINE Type of study: Prognostic study Language: English Journal: Comput Chem Eng Year: 2020 Document Type: Article Affiliation country: J.compchemeng.2020.106945