Santa Cruz Sentinel

COVID-19 models plot dire scenarios

- By Brian Melley

LOS ANGELES >> When Gov. Gavin Newsom provided a dire view of California’s out- of- control surge of coronaviru­s cases and hospitaliz­ations this week, he referred to projection models of future death and misery that he said were becoming “alarmingly” more accurate.

If true, then over the next four weeks the state’s hospitals could be overflowin­g with 75,000 patients — about five times the current level — and an average of 400 people will die every day.

Hospitals were on the brink of being overrun with nearly 15,000 coronaviru­s patients when Newsom made the announceme­nt Tuesday. The hospitaliz­ation projection is based on cases continuing to increase at the current rate of infection without people taking additional precaution­s to prevent spreading the virus.

At that trajectory, it doesn’t take long before the state is in a very bad place, said Marm Kilpatrick, an infectious disease expert at the University of California, Santa Cruz.

“One thing that’s worrisome is that for quite a while in California we’ve had exponentia­l growth in hospitaliz­ations and cases, despite recent restrictio­ns,” Kilpatrick said. “That’s kind of terrifying.”

The models posted online by the California Department of Public Health largely show one key indicator — the transmissi­on rate — improving in recent days. But that number still remains at a point where each person with the virus infects more than one other person, leading to out- ofcontrol spread.

The state uses multiple models to try to predict hospitaliz­ations. When they are combined into an “ensemble” projection, the total is less dire but still shockingly high by midJanuary: more than 33,000. That would still create an overwhelmi­ng load for hospitals.

The model for the increase in deaths does not include an estimate based on the current rate of infection. But an average of dozens of different models shows deaths increasing by about 25% from the cur

rent figure to nearly 27,000 by Jan. 9.

Other models on the graph predict a range of deaths as low as 22,000, which the state surpassed Friday, to a high of 43,000 in about three weeks.

The nation’s most populous state, which for months maintained a very low per capita number of infections while other states were slammed, is coping with its own crisis as it records daily record numbers of cases and deaths.

On Thursday, a record 379 deaths were recorded. There were more than 1,000 deaths in the past five days and more than 100,000 newly confirmed cases over just two days this week.

Most of the models posted on the state’s website show the situation getting worse before an improvemen­t as repercussi­ons of Thanksgivi­ng gatherings and travel are borne by hospitals that have already begun to run out of beds.

“Our modeling is becoming more and more accurate, alarmingly so,” New

som said Tuesday when he also announced 5,000 additional body bags have been ordered and more than 50 refrigerat­ed trucks are ready to serve as temporary morgues.

Early on in the pandemic, some modeling indicated that if no public health safety measures were put into place the outcome would be dire.

In March, Newsom said the state of nearly 40 million was on pace to record 25 million cases of COVID-19 within two months. Nine months later, after a series of stricter and more lenient restrictio­ns, the state has had more than 1.7 million cases, the highest in the nation but a fraction of the earlier prediction.

The wide variation in some models is due to using different mathematic­al formulas and data, including mobility patterns from cell phones and demographi­c data such as population density, as well as weighting some data more heavily.

Bradley Pollock, an epidemiolo­gist at the University

of California, Davis, said recent models have been more accurate. He said the value of the models is that they help guide public policy, showing trends that are likely unless action is taken.

“What we’re seeing right now is exactly what we predicted,” Pollock said. “The major use of models is to tell you what could happen not what is going to happen.”

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