When will California emerge from the coronavirus crisis? What models can – and can’t – predict

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The US’s most influential coronavirus model predicts California will see its outbreak peak this week – exactly one month after San Francisco and several other Bay Area counties enforced the nation’s first shelter-in-place orders. According to the state’s own projections, however, the number of coronavirus hospitalizations and deaths won’t peak until mid- or late May.

“We are not out of the woods yet,” the California governor, Gavin Newsom, said on Tuesday.

So when will California get out of the woods and emerge from the crisis? Since the coronavirus first emerged as a serious threat this winter, epidemiologists around the world have designed several disease models, plotting best- and worst-case scenarios to estimate how many thousands or millions might contract the disease. These projections have informed lawmakers and public health officials and riveted an anxious public.

Unfortunately, none of these predictions can say for certain when the outbreak will fade, epidemiologists say. At best, they are a tool to help officials prepare for a potentially prolonged public health crisis, biostatisticians and infectious disease experts told the Guardian. At worst – they’re entirely useless.

What do the large-scale disease models predict will happen in California?

According to the model developed by the University of Washington’s Institute for Health Metrics and Evaluation (IHME), one of the nation’s most influential and popular coronavirus models, the number of hospitalizations in California will max out on 17 April. The model predicts that the daily death toll in the state will peak two days later. Ultimately, a total of 1,483 Californians will die from Covid-19 by early August, according to the IHME, and nearly 69,000 people will die nationally.

The model has been tweaked to account for stay-at-home orders, and has more or less matched the reality in California. Its predictions for the number of hospital beds that would be occupied per day were off by fewer than 10 over the weekend.

But even though it has proved more or less accurate in recent days, “it’s not informed by any epidemiological science,” said Joseph Lewnard, an epidemiologist at the University of California, Berkeley, who specializes in using mathematical and statistical modeling to study infectious diseases. “The model aims to be a crystal ball – and in some sense, that’s dangerous.”

In statistical terms, the model “fits deaths to a curve”, Lewnard explained – expecting that the trajectory of the disease in California or New York or Florida will more or less resemble the trajectory of other outbreaks in China and Europe, with new infections building up and fading away at a certain rate.

The IHME’s outlook is much rosier than other models, including an initially harrowing projection from Imperial College London, which mapped out a scenario that more than 1 million Americans could die. “If you do the math, that translates to 44,500 deaths predicted in the Bay Area,” said George Rutherford, a professor of epidemiology and biostatistics at the University of California, San Francisco. In reality, there have been about 150 deaths in the region so far. “The takeaway is that shelter-in-place has been hugely life-saving,” Rutherford told the Guardian.

What’s up with California’s own modeling?

California’s state officials have based their models on a system developed by researchers at Johns Hopkins University. The model assumes that 10% of Californians with coronavirus will end up in the hospital, and about a third of those hospitalized patients will end up in the intensive care unit.

Increasingly, the predictions have diverged from reality, overestimating the number of people who might become seriously ill. For instance, on 28 March, the model predicted that a median of 5,690 people would be hospitalized due to Covid-19. In reality, 4,362 Californians were hospitalized due to known or suspected infections. On 12 April, California’s model predicted that a median of 10,711 people would be hospitalized with the disease. In reality, 5,048 – less than half the predicted number – Californians with known or suspected infections ended up hospitalized.