Coronavirus State-By-State Projections: When Will Each State Peak?

As COVID-19 surges in places throughout the country, Americans are left to wonder, "When will my state hit its worst point?"

A widely cited model offers some predictions. The Institute for Health Metrics and Evaluation's COVID-19 projections were cited in recent White House briefings and take into account how the pandemic is playing out in several countries around the world. They incorporate the current trend line of deaths in U.S. states and the estimated impact of social distancing measures to predict when each state may reach peak daily deaths and hospital usage.

While projections like these are imprecise, they're useful to policy makers and hospital leaders trying to prepare for surges. The model was designed to give hospitals an idea of how quickly and how much they need to expand capacity.

Researchers at IHME make frequent updates to the model based on newly available data, and some of those changes have resulted in drastic shifts. The latest major update, made Sunday, shows fewer people dying over a shorter period of time, the model's lead researcher Chris Murray says.

However, he cautioned that when social distancing measures lift, outbreaks could spark up again.

"If you ease up prematurely the epidemic can rebound right back to the level we are at now in a matter of weeks," Murray says. "So the potential for rebound is enormous if we let up on social distancing."

To compare states with vast differences in populations, NPR analyzed the projections by looking at deaths per 100,000 residents.

Want to see the projection for your state? Jump to our state lookup tool.

Understanding the projected range

It's important to note that much uncertainty comes with modeling into the future. The national model has a massive gap between its low and high estimates for peak daily deaths: 1,300 and 7,700. But individual states have large gaps too. The model, for example, estimates New York's daily deaths could range between 200 to 2,800 at its peak.

Murray acknowledged the challenge this wide range poses to decision-makers at a press conference Monday announcing updates. He advised hospitals to hope for the best-case scenarios — but to prepare for the worst.

"In places where there's a rapidly rising epidemic — New York, New Jersey, now other places — the ability to predict that exact peak is not as accurate as we previously said," Murray said. "Resource planners should pay attention to the upper bound so we're not caught off guard."

New York was nearing 5,500 COVID-19 deaths as of Tuesday. It is expected to be the hardest hit state, in terms of raw numbers. The model projects between 12,000 and 22,000 deaths in the state, with daily deaths peaking on Thursday. That amounts to between 60 and 110 deaths for every 100,000 New Yorkers, putting New York among the worst hit states per capita as well.

The model also looks at hospital bed shortages. It projects a dramatic shortfall in New York, culminating this week. On Wednesday, the state is projected to need between 14,000 and 45,000 beds. Under normal circumstances there are only 13,000 beds available in the state, according to the modelers. (This does not take into account ongoing efforts to expand bed capacity.)

The effect of social distancing

The model projects California will see fewer deaths than New York, despite having twice as many people living in the state. That gives California a much lower death rate relative to its number of residents.

The difference reflects social distancing measures California took, says Ali Mokdad, a professor of health metrics sciences at IHME who helped create the model.

"California started social distancing before New York. [Californians] had one week ahead of them in order to deal with the problem, and took the right measures," Mokdad says. "And we're seeing the benefit."

The model makes some key assumptions about how state leaders will act — and depending on what they do, the picture could change. First, it assumes that all states will continue social distancing through the end of May — which is longer than the White House has asked Americans to practice social distancing. Second, it assumes states that have not already implemented three key social distancing measures — closing schools, closing nonessential businesses and issuing stay-at-home orders — will do so in one week.

This second assumption is particularly important for a state like Massachusetts, which has closed nonessential businesses and schools, but has not ordered residents to stay at home. Republican Gov. Charlie Baker has resisted calls to mandate a stay-at-home order, though he has enacted a voluntary stay-at-home advisory. "I do not believe I can or should order U.S. citizens to keep confined to their homes for days on end," Baker said last month.

The model's highest projections could spell tragedy for Massachusetts, estimating worse daily death tolls at the upper bounds than what even New York has experienced so far. But the figure it forecasts would still be devastating for a state of its size: 373 daily deaths near the middle of April.

Through social distancing, Mokdad says, communities and individuals can still make a difference in how bad things will get.

"We're modeling [based on] your deck of cards right now," he says. "If you change the deck of cards, it's going to be totally different. If people do a better job, it's going to go down. If they don't — if they ignore recommendations and start partying and going out — then they will have more mortality."

A final important note about this model: The data shows the day each state may reach its worst day for deaths between now and the beginning of August. It does not reflect surges that could happen after that.

You can view your own state's peak and projected totals below, or see how all states compare.

Note: This projection is current as of April 7, at 5 p.m. ET, and will be updated periodically as the modelers input new data. The visualization shows the day each state may reach its worst day for deaths between now and Aug. 4.

Stephanie Adeline, Nurith Aizenman, Daniel Wood contributed to this report.

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