Qventus AI predicts major capacity shortfalls in ICU beds due to coronavirus

By adapting the CDC's Flu Surge model to fit the known patterns of COVID-19, the disease caused by the novel coronavirus, artificial intelligence platform Qventus has built a predictive model estimating the effects of the disease on the U.S. healthcare system.

The analysis breaks down the forecasted effects by state and by the demand for both ICU and non-ICU beds over time, detailing predictions of the total number of patients who will be hospitalized for COVID-19 in the U.S., the number of deaths and the effects on hospital bed, ICU and ventilator capacity.

According to the model, if the disease spreads at a "moderate" level, approximately 6.1 million people in the U.S. will be infected, with just over 1 million hospitalized and about 200,000 deaths. At the peak of the pandemic, there will potentially be a shortage of 9,100 ICU beds and 115,000 non-ICU beds, and these increases in care will require 325,000 additional healthcare workers.

On a state level, the increases will result in capacity shortfalls in nearly every region, with Vermont, Hawaii, Maryland, New York and Delaware expected to see the greatest shortfalls in ICU beds.

View the full model and its results here.

More articles on AI:
Illinois ACO deploys AI to identify high risk COVID-19 patients
Researchers criticize opacity of Google's mammogram-reading AI study
AI provider releases social determinants of health tool

© Copyright ASC COMMUNICATIONS 2020. Interested in LINKING to or REPRINTING this content? View our policies by clicking here.


Featured Content

Featured Webinars

Featured Whitepapers