Home Science The Mathematics of Predicting the Course of the Coronavirus

The Mathematics of Predicting the Course of the Coronavirus

The Mathematics of Predicting the Course of the Coronavirus 1

So Brandenburg’s team got to work. They had already begun ordering more masks, gloves, face shields, and ventilators. They had opened a drive-thru testing station. Now they moved to deploy a surge plan, canceling all elective surgeries and trying to clear out as many beds as possible. They built wedding-party-size triage tents outside hospitals’ emergency room departments to keep potential Covid-19 patients away from others seeking care. They called up ICU nurses who’d retired within the past five years. They began shuffling in nurses, respiratory therapists, and technicians from other departments, training them up on the specifics of critical care.

Murray’s team embedded with Brandenburg’s, providing them with daily updated projections as new data came in. In the most recent models from late last week, things started to take a turn—and for the first time, they were for the better. The curve is flattening out. In the new worst-case scenario, the number of patients has dropped by 20 percent compared with IHME’s first report. The peak is now 10 days later, on April 17.

Across UWM’s four hospitals, Covid-19 cases are down too. At the end of last week, doctors and nurses were caring for just over 60 Covid-19 patients, down from about 75 a few days prior. “It looks like the social distancing is helping,” says Brandenburg.

She knows the projections can change any time, for the worse. And that’s still what they’re preparing for. But for the first time, she says, looking at those graphs she allowed herself to think that maybe, maybe, it was no longer a question of when Seattle would become the next Spain, the next Italy, the next New York. “For the first time I feel like, ‘OK, maybe we are actually going to have all our plans in place,’” she says.

Other hospital administrators and local public health officials should take note. After word got out about the work IHME was doing for hospitals in Seattle, other health care providers around the US began sending Murray emails, asking for help with their own preparedness plans. As the individual requests piled up, his team decided to go public with their work last week, providing interactive state-by-state projections for how the nation’s supply of hospital beds, intensive care units, and ventilators will hold up over the next few months.

The new coronavirus will spread through different regions at different speeds—depending on population density, transit patterns, and how well people are adhering to whatever social distancing measures are in place. So Murray’s hope is that local policymakers can use the models to get a more fine-grained view on when their particular wave might be cresting. “We want to help them figure out when their worst week will be and to prepare accordingly, however they can,” says Murray. His team plans to update their models every Monday, pulling in the latest death counts and adjusting for any changes to statewide social distancing policies. It’s still too soon to say if Washington will be a success story. But at least right now, it appears to be an outlier.

According to IHME’s models, 41 states will need more hospital beds than they currently have. Twelve states will need to boost their numbers of ICU beds by 50 percent or more. The models predict that over the next four months, these shortfalls will contribute to the deaths of 81,000 Americans, with the number of deaths per day peaking as soon as mid-April.

Even this estimate is generous. As epidemiologists have been pointing out on Twitter, Murray’s models assume that states that haven’t yet enacted strict stay-at-home orders will do so in the next week, in light of what’s happening in New York—and that they’ll achieve Wuhan-level lockdowns, which many public health experts are skeptical Americans can pull off. Indeed, plenty of states, mostly conservative-leaning and where case counts so far remain low, have resisted taking those steps. Even before Covid-19, scientists had trouble getting policymakers to pay attention to their warnings. Now they can’t get enough data to make those warnings specific, and politicians are working to undermine what little the scientists are sure of. What was already a tragedy has evolved into a disaster, reaching toward catastrophe. And all of it was predictable.


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