An Interactive Tool to Forecast US Hospital Needs in the Coronavirus 2019 Pandemic

Locey, Kenneth J; Webb, Thomas A; Khan, Jawad; Antony, Anuja K; Hota, Bala

OBJECTIVE: We developed an application (https://rush-covid19.herokuapp.com/) to aid US hospitals in planning their response to the ongoing COVID-19 pandemic. MATERIALS AND METHODS: 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 23 parameters, examine trends in testing and hospitalization, and download forecast data. RESULTS: Our application accurately predicts the spread of COVID-19 across states and territories. Its hospital-level forecasts are in continuous use by our home institution and others. DISCUSSION: Our application is versatile, easy-to-use, and can help hospitals plan their response to the changing dynamics of COVID-19, while providing a platform for deeper study. CONCLUSION: Empowering healthcare responses to COVID-19 is as crucial as understanding the epidemiology of the disease. Our application will continue to evolve to meet this need. LAY SUMMARY: Hospitals have been continually faced with anticipating the resurgent spread of COVID-19 and its effects on visits, admissions, bed needs, and crucial supplies. However, few open source tools are available to aid hospitals in planning. We developed a web application (https://rush-covid19.herokuapp.com/) for US states and territories to predict the spread of COVID-19 and to provide forecasts for hospital visits, admissions, discharges and to anticipate needs for ICU and non-ICU beds, ventilators, and personal protective equipment. Users can choose from a suite of models to predict the spread of COVID-19, some of which explain > 99% of variation in COVID-19 cases within states. Users can modify a large set of inputs to obtain forecasts for their institution, examine variability in forecasts over time, download forecast data for further analysis, and explore trends in hospitalization and testing. We designed our application to be interactive, insightful, and easy to use for hospital leaders, healthcare workers, and government officials. However, specialists can use our models, open source code, and aggregated data for deeper study. As the dynamics of COVID-19 change, our application will also change to meet emerging needs of the healthcare community.