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Across the United States, U.S. leaders are grappling with the difficult decision of when to loosen the social distancing restrictions that helped keep COVID-19 under control. Already this week, the Governor of Georgia has authorized the reopening of businesses ranging from gymnasiums to hair salons and cinemas – although he does not comply with most of the White House guidelines for phase 1 reopening . The governor of South Carolina has taken a similar approach – including the reopening of state beaches.
And governors of other states, including Tennessee and Ohio, have declared that they will allow the expiration of their residence orders next week, with varying degrees of social distancing required beyond this point.
But how should states decide when to reopen? Epidemiologists and other public health experts warn against moving too quickly. They note that the coronavirus is still circulating. Cases could again reach catastrophic levels unless appropriate action is taken. The consensus opinion is that states should not open up unless they have a robust system to detect and cancel new flares by testing to see who is infected, finding their contacts and isolating and quarantining if necessary.
Unfortunately, most states will not be ready to launch such a system anytime soon – due to persistent problems with testing capacity, as well as limited staff in local and local health departments.
For example, a team of disease modellers – from the University of Washington Institute of Health Metrology or IHME – developed a different standard. They ask the question: what is the maximum number of new infections that States could manage with their current test and ability to find contacts?
IHME response: one new infection per million people in a given condition. They believe states with this level of transmission should be able to prevent outbreaks from spreading even after people start mixing again, although researchers point out that states should still limit large gatherings.
The IHME team has built a model to predict when each state will reach the threshold of one new infection per million. Their main conclusion is that very few states are close.
By May 10, only five states are slated to arrive: Alaska, Hawaii, Montana, West Virginia, and Vermont. Twenty-one states will not reach the threshold until early June or later. These include two of the states whose governors have been the most aggressive over the reopening – Georgia and South Carolina. Likewise, Ohio is not expected to meet the standard until May 14; Tennessee not before May 20.
For a graph of the projected date for each state, scroll below or click here.
But first several caveats.
Ali Mokdad, professor of health metrics science at IHME, said the team had developed the standard of one new infection per million based on a survey of existing health service capabilities locals across the country. But, he adds, “It was very difficult for us to be sure. So we made a very conservative estimate. ” And, he says, already, “states are starting to contact us saying,” I can do more than that, so [instead] can you tell me what your data is about when we reach, say, two cases per million? ‘»
On the other hand, Mokdad warns that the opening bar may in fact need to be raised even more in light of new research released Thursday that about 20% of New Yorkers have already been infected with COVID -19. This is many times the number of confirmed cases. And this suggests that the coronavirus is spread by asymptomatic people to a much greater extent than the IHME team and other modellers have explained. “It baffled many of us,” said Mokdad. “We have long meetings on this. “
Among the implications, a locality where infections have fallen to one in a million may still require much more testing capacity than suggested by the current IHME approach, as officials will need to ensure that workers who return at work in overcrowded industries – such as meat packing plants – are not asymptomatic spreaders of the disease. “We have to be very careful about that,” says Mokdad.
One final caveat: the IHME model is just one of many that have been created to map the progression of COVID-19, and some other models offer less optimistic projections of the trend in infection rates. In general, models of this type should not be considered as literal predictions of the future. They can be useful tools for assessing the likely trend line of an emerging disease and the likely impact of various response strategies. But models are inherently subject to error because they are based on many assumptions on which scientists can only make educated guesses at the moment.
You do not see the graphic above? Click here.