President Trump and many governors are openly talking about when and how to reopen the nation’s economy. They should be looking closely at the regional data regarding coronavirus infection rates as they make these decisions. Different parts of the country show much different rates of infection, suggesting that some places might be able to reopen earlier than others.

The data shows that the United States has a national problem with severe regional crises. As of Monday, the country had about 579,000 recorded cases of covid-19. Data from the New York Times shows that nearly half —almost 256,000 cases — were from the New York metropolitan area. Broaden that out to other counties in the New York area, and you add 19,000 more cases. An area that contains less than 7 percent of the national population had nearly 50 percent of the nation’s cases.

A mere four other regions of the country combined for roughly 68,000 more cases. The Boston and Detroit combined statistical areas had almost 47,000 cases between them, while the regions in eastern and southern Louisiana, including the New Orleans and Baton Rouge metro areas, had 17,000. Add the Hartford, Conn., metro area and the western part of Massachusetts to these areas and New York, and you’ve accounted for 60 percent of the nation’s cases.

The disparities become even clearer when one looks at the number of cases per million inhabitants. In addition to the crisis areas mentioned above, only 15 of the 80 metro areas with 750,000 people or more have infection rates greater than 1,000 per million people. This includes large cities such as Los Angeles, Dallas, Houston, Atlanta and Phoenix. Assuming the data, which comes from the Centers of Disease Control and Prevention, is accurate, most Americans live in places where covid-19 infections are rare and deaths are few.

There are hot spots outside the major metro areas. Certain counties in the Rocky Mountains with ski resorts, such as Eagle and Gunnsion counties in Colorado, Summit County, Utah, and Blaine County, Idaho, have rates of infection as high as 20,000 per million. A collection of counties in southwestern Georgia have infection rates between 3,000 and nearly 13,000 per million. Minnehaha County in South Dakota and Navajo County, Ariz., had more than 3,000 infections per million. There are nearly 100 other counties with infection rates at or above those found in the hardest stricken metro areas.

Even still, there are patterns worth noting. Many of the hardest hit regions have high population density; highly populated and dense central business districts; and high usage of rapid transit, especially by rail. They are also more likely to be located in northerly latitudes, have concentrated poverty and have high levels of tourism.

New York — the hardest hit region — has all six attributes. It’s reasonable to believe based on these data that people with the coronavirus spread the disease more rapidly in the close quarters in which people live and work in the Big Apple, with infected workers then spreading the virus to their homes when they commute home after work. New York’s JFK airport was also one of three airports receiving the most travelers directly from Wuhan, China, that was singled out for special screening of those passengers in mid-January. London has similar attributes, and British data shows it is easily the hardest hit on a per capita basis of England’s regions, with the commuter-heavy South West region the second hardest hit.

The connection between latitude and infection rates is one of the most intriguing relationships emerging from the data. Outside Louisiana, none of the 80 most populous metro areas south of 35 degrees north had an infection rate more than 2,000 per million, and only tourist-heavy Miami was close to that mark. Every metro area with infection rates at or above 2,000 per million as of Monday is above or close to 40 degrees north. These largely newer metro areas are also characterized by less dense central business districts and low levels of public transit usage, especially by rail.

None of these data suggest that the national social distancing measures we have lived through were unneeded. Infections rates everywhere would surely be much higher without them, saving tens of thousands of lives. Nor are they dispositive in and of themselves. Experts looking at these data more closely will discover more than my nonexpert eyes could discern.

They are, however, strongly suggestive that not every place in the nation faces the same risks from reopening the economy. At some point, we need to do what we can to establish a level of acceptable risk that allows normal life to haltingly resume. These data suggest some areas of the country might reach those benchmarks sooner than others. Let’s hope that federal and state policymakers consider that as we try to emerge from our self-imposed cocoon.

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