A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic

Davide Manca, Dario Caldiroli, Enrico Storti

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number106945
JournalComputers and Chemical Engineering
Volume140
DOIs
Publication statusPublished - Sep 2 2020

Keywords

  • Covid-19
  • Deaths
  • Emergency planning
  • ICU beds prediction
  • ICU patients
  • Resource allocation

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Computer Science Applications

Fingerprint

Dive into the research topics of 'A simplified math approach to predict ICU beds and mortality rate for hospital emergency planning under Covid-19 pandemic'. Together they form a unique fingerprint.

Cite this