[Nationwide exposure model for COVID-19 intensive care unit admission].

ABSTRACT:

Background

Forecasting models for intensive care occupancy of coronavirus disease 2019 (COVID-19) patients are important in the current pandemic for strategic planning of patient allocation and avoidance of regional overcrowding. They are often trained entirely on retrospective infection and occupancy data, which can cause forecast uncertainty to grow exponentially with the forecast horizon.

Methodology

We propose an alternative modeling approach in which the model is created largely independent of the occupancy data being simulated. The distribution of bed occupancies for patient cohorts is calculated directly from occupancy data from "sentinel clinics". By coupling with infection scenarios, the prediction error is constrained by the error of the infection dynamics scenario

SUBMITTER: Schuppert A 

PROVIDER: S-EPMC7856858 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature