Americans Didn’t Wait For Their Governors To Tell Them To Stay Home Because Of COVID-19

APS Member/Author: Kyle Bourassa

A favorite new debate taking place around the Twitter hearth is whether complying with social distancing guidelines is a partisan statement in and of itself. Blue states, such as Washington and New York, were initially hit hardest by the COVID-19 crisis, and stay-at-home orders went into effect as early as March 19 (California was first out of the gate). A number of red states have refrained from implementing such public-safety orders, and many Republican-leaning states, particularly in the South, didn’t issue orders for weeks afterward — as late as April 3 in Florida and Georgia. Florida Gov. Ron DeSantis waffled over closing the state but eventually did so under pressure from state lawmakers.

But, at least on the front end of this crisis, Americans weren’t deciding what to do based on politics. Americans living in red states appear to have taken the crisis plenty seriously; data shows that residents there were staying home well before their governors issued stay-at-home orders.

Cuebiq, a private data company, assessed the movement of people via GPS-enabled mobile devices across the U.S.¹ If you look at movement data in a cross-section of states President Trump won in the southeast in 2016 — Tennessee, Georgia, Louisiana, North Carolina, South Carolina and Kentucky — 23 percent of people were staying home on average during the first week of March. That proportion jumped to 47 percent a month later across these six states.

If defying social distancing orders were really a political statement, you’d think that the southeast would be a hotbed for dissent. Yet people in the six states we examined changed their behavior around mid-March, before the states’ official stay-at-home orders. In fact, about 90 percent of the total change between early March and mid-April had occurred in the week before the stay-at-home orders were passed in each state.

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Almost uniformly across these states, people started staying home beginning on March 14. The percentage of people staying home rose rapidly over the following nine days and tended to plateau by March 23.

The Cuebiq data suggests that behavioral changes were largely driven by people making a voluntary choice to stay home rather than being forced to do so by a state-sanctioned stay-at-home order. One need only look at the behavior of residents in North Carolina and their neighbors in South Carolina: While North Carolina issued a stay-at-home order eight days before South Carolina, a stabilized number of people in both states started staying at home about a week before North Carolina’s order.

Why did people begin to stay at home so early? In mid-March, the seriousness of the virus had begun to permeate the national and international conversation. On March 9, the Dow dropped to its lowest point since the 2008 financial crisis. Earlier that same day, Italy announced a nationwide lockdown. On March 11, the NBA announced that it would suspend its season indefinitely, a sign to many Americans that the pandemic would indeed change all facets of life, and on March 12, the World Health Organization declared COVID-19 a pandemic. Some of the earliest official actions in the U.S. occurred around that time in the state of Washington, when Gov. Jay Inslee announced on March 11 a ban in three counties on gatherings of more than 250 people and public schools in Seattle also announced they would close. Many other U.S. cities closed schools, restaurants and bars in rapid succession around March 16.

This sort of mass behavioral change in such a short time is significant. It took over 50 years and hundreds of billions of dollars in prevention efforts to lower the percentage of people who smoke in the U.S. from 42 percent in 1965 to 13 percent in 2018. Americans reacted to the threat of COVID-19 in a relative blink of an eye.

The question that now looms, of course, is whether Americans’ individual behavioral changes will last as the pandemic wears on and the summer sun beckons. We’ll be watching movement data to get a sense of how quickly we will return to normal — or at least how quickly we establish a new normal.

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