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When should the United States flatten the curve?

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—Every day the number of confirmed COVID-19 cases in the United States is increasing. On March 26, the country overtook China to climb to the top of the list of the most reported cases of the new coronavirus in the world, and the spread of the disease shows little sign of reduction.

However, the United States is a huge country, and the growth patterns of SARS-CoV-2, the virus that causes the disease, differ considerably from state to state. Researchers from the University of Washington recently analyzed these early trends, as well as factors such as how states are implementing social distance, their hospital and testing capabilities, and have developed a projection of what the future holds for everyone regarding the coronavirus pandemic. . The bottom line: the longer it takes a state to reach its peaks for hospitalization and mortality, the lower these peaks.

“It’s all this flattening of the curve construction – that if you have slower transmission, you slowly reach a lower peak,” says Dr. Christopher Murray, director of the Institute for the Institute for Health Metrics and Evaluation (IHME) and professor and president of health. metric sciences at the University of Washington. The IHME statistical model “takes this model back into the data and that’s what we project,” says Murray.

TIME crossed the numbers to create two graphs which, taken together, suggest that “flattening the curve” seems to be true for states as well as for countries.

In the graph above, the red dots indicate the cases in which, when a state reaches its peaks of daily hospital admissions, it will exceed (or will already have exceeded) the current hospital bed capacity of that state. State. The fact that most of the blue dots are on the far right of the graph suggests that the later a state peaks in daily hospital admissions, the less likely it is that the state’s hospital systems will eventually overtake their ability. This, in turn, means that these states are likely to have fewer deaths per capita, as their health systems will not be as overburdened as these states in red. (Louisiana might be an outlier here due to its relatively high number of hospital beds per capita; according to the Kaiser Family Foundation, the state has 3.3 hospital beds per 10,000 population, compared to 2.5 for Michigan and 2.4 for New Jersey, for example.)

There are some caveats. Murray warns that there is not yet clear evidence as to why some regions are dealing with more COVID-19 transmission (and therefore should have faster and more dangerous peaks than others) at the moment. For example, the transmission rate in New York, which has become a major epicenter of the epidemic in the United States, has been “very high,” notes Murray. At 8 p.m. EST on April 2, New York reported more than 92,000 confirmed cases of COVID-19 and more than 2,300 deaths, according to a tracker researchers from Johns Hopkins University. But it might have less to do with the policies New York has in place than with the fact that “in dense urban areas where the dominant mode of transportation involves people being in fairly close contact with each other, like subways or bus systems, “may be more COVID-19 transmissions,” says Murray.

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Then there is Louisiana. “It certainly stands out,” says Murray, as one of the few areas of the country that is not particularly urban, and yet has been hit hard by COVID-19, with approximately 9,100 cases of COVID-19 and 300 deaths. in April 2. But there could also be an explanation: the governor of Louisiana, John Bel Edwards, speculated if the state’s celebration of Mardi Gras could be partly to blame for the high number of state reports.

In states that have seen fewer cases, the current IHME model is “not great,” admits Murray, but expects it to improve over time as data reporting increases. Researchers plan to update the data daily. “People should think of this as a weather forecast,” says Murray. “Everyone has gotten used to the fact that these changes change as the weather changes and new data arrives. It is really a very similar construction.”

These graphs are “not surprising because they illustrate the importance of flattening the curve,” says Dr. Leana Wen, emergency physician and professor of public health at George Washington University. Even if a state ends up with the same total number of COVID-19 cases, “If you are able to spread infections over time, you reduce the burden on the health care system and therefore the mortality rates.” But it also goes without saying that if you flatten the curve, you also reduce the total number of cases. That’s what appears to be reflected in TIME’s charts, notes Wen. “It makes sense that the infection rate correlates with the peak of hospitalization and therefore with the mortality rates,” she said.

What states should do to try to flatten the curve

This is why it is essential that the states of the United States focus on two things that are under their control, according to Wen. First: the capacity of hospitals to manage capacity. And second: reduce person-to-person transmission in the community, especially in the context of a shortage of ventilators and other essential medical equipment.

While the charts provide useful information on how the flattening of the curve can help save lives, Wen notes that the data should not be used to guide the policy of each state, especially to signal to any state. that they are clear. Each state should do “everything it can to prepare for and prevent” an increasingly large epidemic of COVID-19, she said, in particular social distancing.

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David W. Hutton, Associate Professor of Health Management and Policy at the University of Michigan School of Public Health, explains that the graphs provide an approximate short-term picture of the leadership of individual states, but that it may still be too early to see the impact of recent interventions, including a national call for social distancing. Judging by trends in China, Italy and Spain, the impact of these interventions would likely be reflected in the data “about two weeks later,” said Hutton.

Wen also warns that state-reported data may not be a fully reliable indicator of the depth of penetration of the coronavirus into communities. (States reporting COVID-19 and higher deaths may do so in part due to relatively higher testing; those reporting lower numbers may reflect a lack of testing.) Therefore, even if the figures suggest that states may have time before a spike hits, it would be a big mistake for them to underestimate the threat that an epidemic of COVID-19 could pose. “The worst thing that can happen is if a state thinks” oh the peak for my region is not going to last three months, so I don’t need to prepare now, “says Wen. “The direction I would give to the states is that you may well be the next epicenter of the epidemic. We saw how quickly this happened in the New York area, so be prepared for that. “

TIME also tracks the daily trajectories of COVID-19 cases in the United States, to see if they actually flatten the curve:

Write to Sanya Mansoor at sanya.mansoor@time.com.


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