Published September 21, 2021 | Version v1
Dataset Open

An interactive tool to forecast us hospital needs in the Coronavirus 2019 pandemic

  • 1. Rush University Medical Center

Description

We developed an application (https://rush-covid19.herokuapp.com/) to aid US hospitals in planning their response to the ongoing COVID-19 pandemic. Our application forecasts hospital visits, admits, discharges, and needs for hospital beds, ventilators, and personal protective equipment by coupling COVID-19 predictions to models of time lags, patient carry-over, and length-of-stay. Users can choose from seven COVID-19 models, customize a large set of parameters, examine trends in testing and hospitalization, and download forecast data.

The data and scripts contained herein are used to generate Figure 1 of the associated manuscript, which presents general forms of the models used by our application and presents results for each model across time.

Notes

1. The model_results_dataframe.pkl file is a python specific file format.

2. Running the ModelFxns_Figs.py and ModelPerformance_Figs.py is all that is needed to recreate the subplots of figure 1. The user should have the following libraries/softwares installed:

Python 3.6 or greater
numpy 1.16 or greater
pandas 0.24 or greater

Files

Data_And_Scripts.zip

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