On Monday, the CDC published an early report examining the "timing of community mitigation" strategies aimed at slowing the spread of COVID-19. The study focused on four major metropolitan areas—Seattle, San Francisco, New York City, and New Orleans—from February 26 to April 1. Here are the key findings:
- We already understand that measures like social distancing, regular cleaning, and the use of fabric masks can help reduce the transmission of viral diseases during a pandemic.
- During the period studied, movement in these cities slowed down as local governments implemented health policies and as the number of reported cases increased sharply.
- Policies encouraging people to stay home may have had some effect, but it's still unclear whether they directly reduced the spread of the virus.
What’s the real story here?
The report found that people didn’t significantly increase their time at home when a state of emergency was declared. It wasn’t until restrictions on large gatherings, school closures, and other public health measures were put in place that mobility started to drop. As the White House launched its “30 Days to Slow the Spread†initiative, movement decreased even more. And once states introduced formal stay-at-home orders, the decline became more pronounced. In fact, while 80% of people were leaving their homes on February 26, by April 1, that figure had dropped to around 50% on average across all states.
However, what remains uncertain is whether these changes actually led to a slowdown in the spread of the virus. In all four cities, case numbers continued to rise even as mobility decreased. The CDC's graphs show a slight downward trend in mobility, while the cumulative number of cases climbed sharply. Meanwhile, the three-day average percentage change in cases fluctuated before eventually beginning to slow down.
One possible explanation is that it took a combination of multiple public health interventions to get people to stay home. At the same time, the long incubation period of the virus meant that infections were spreading undetected for days before symptoms appeared and testing occurred.
Eventually, stay-at-home orders seem to have had an impact. When health officials looked at the three-day average change in case numbers, they noticed a gradual decline over time, even though the total number of cases kept rising rapidly.
How do we measure community mitigation?
The CDC based its analysis on anonymized and aggregated cell phone location data provided by SafeGraph. This data tracks devices that move more than 150 meters from their typical nighttime locations—essentially, if your phone moves away from where you usually sleep during the day, it’s assumed you’ve left home and aren’t sheltering in place.
The CDC recommends several mitigation strategies, including limiting large gatherings, closing schools, restricting business operations, and issuing shelter-in-place orders. But right now, the evidence linking these policies directly to a reduction in cases is still limited. Researchers can observe a correlation between policy changes and mobility patterns, but proving causality is more complex.
Additionally, there's still uncertainty about how many people actually have the virus, due to ongoing limitations in testing availability. Another factor to consider is that behavior may vary widely between urban centers like Seattle or New York and more rural areas like Alabama, Wyoming, or Minnesota.
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