Why some states became coronavirus hot spots and others haven’t

If you look at a map of coronavirus cases in the US, it can be hard to figure out any patterns. California reported some of the first coronavirus infections — including the country’s first instance of community transmission — but New York has reported 12 times as many deaths.

Michigan, meanwhile, has the third-highest number of coronavirus deaths in the US, but neighboring Ohio doesn’t even register in the top 10.

Florida was slow to shut down in response to the pandemic, but so far it’s reporting fewer deaths than nine other states, many of which were quicker to act.

Why? What explains why some states become hot spots for Covid-19, the disease caused by the SARS-CoV-2 coronavirus, but not others?

I turned to experts with these questions. While they cautioned that there’s a lot about the coronavirus and how pandemics work in modern society that we don’t know and are still learning about, they gave two major explanations for why some areas become hot spots and others don’t.
First, sometimes it just comes down to chance. Some places just happen to have populations, like the elderly and those with underlying medical conditions, that are more vulnerable to Covid-19. Factors beyond an area’s immediate control, such as its population density and perhaps even its weather, can also contribute to the virus’s spread. Whether any given place experiences a super-spreading event, in which one or more individuals transmit the coronavirus to a disproportionate number of people, can partly come down to chance, too.

Second, early action did appear to prevent coronavirus cases. Even in states that are not suffering a high number of Covid-19 deaths, chances are those figures would be even lower if they — or if the country as a whole — had acted sooner. There’s good evidence for this in some states, but there’s also research of past pandemics to back it up.

“A hot spot is a reflection of the combination of the random nature of things — in terms of who gets hit harder earlier — and then the timing of what we call non-pharmaceutical interventions” such as social distancing, William Hanage, an epidemiologist at Harvard University, told me.

The key here is that states have direct control over one of these two factors. They can’t do much about luck. They have little ability to predict whether someone infected within their borders happens to spread the virus to a lot of people, and little control over their local weather or population density. But they can take swift, aggressive action to mitigate their chances of an outbreak — to limit the risk, for example, that someone becomes a super-spreader or that people are gathering in very dense crowds.

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