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New models: Arizona may reach coronavirus peak in May, June

New York reports first coronavirus-related death in state
Posted at 12:15 PM, Apr 22, 2020
and last updated 2020-04-23 00:02:05-04

According to Dr. Cara Christ with the Arizona Department of Health Services, our state may not have hit its peak for coronavirus cases, and it may be at least a month before we do.

FULL COVERAGE: Coronavirus in Arizona

In an ADHS blog post written by Dr. Christ Wednesday, she said initial Arizona projections estimated the peak number of resources will be needed to battle coronavirus around the middle to end of April. Those projections were based on new and limited information from February and March.

After learning more about the virus and our own environment, it now appears Arizona may reach its peak around May 22 or later, according to new models released Tuesday.

“It’s important to note: these models all vary dramatically and are updated as new data is available. The two most prominent are found at healthdata.org and COVIDActNow.org,” Dr. Christ says.

One updated model was compared with data from Arizona State University and University of Arizona. That data compilation estimates about 15,000 Arizonans would need to be hospitalized with a need for 7,000 ICU beds.

At the peak estimated date of May 22, Arizona would likely see 600 hospital beds and 300 ICU beds utilized.

However, a federal model suggests Arizona could reach its peak around June 11.

This federal model takes into account the current data from the state, as well as the mitigation strategies Arizona has put into place,” Dr. Christ said.

If this model remains accurate, Dr. Christ says it shows some good news.

“Its projections, even with the mitigation strategies lifted, predict that our current resources, including inpatient beds, ICU beds, and ventilators, will meet a healthcare surge due to COVID-19. This model appears the most realistic and the predictions are reassuring.”

Read more about the models and what Dr. Christ has to say about our state’s predicted case load on the ADHS blog.