Are the Bay Area's new Covid-19 stay-at-home orders changing anything?
Thanks for joining me for the 26th issue of the Golden Stats Warrior, a newsletter for data-based insights about the Bay Area. If this is your first time reading, welcome! You can sign up here. I am grateful for your support.
Starting December 7th, Alameda, Contra Costa, San Francisco and Santa Clara counties implemented new stay-at-home orders. The orders require people to stay home as much as possible and stop gathering with people who are not a part of their household, either inside or outside. They also mandated the closure of indoor and outdoor dining, hair salons, barbershops, and nail salons. The maximum capacity of retail stores was reduced to 20%. Marin County joined these other counties on December 8. (San Francisco changed their rules to allow for meeting between two people from different households outside on December 10th, but my understanding is that this was superseded by a state order not to do so on December 17th. It’s all very confusing.)
The rules were put in place because of the fast rising number of Covid-19 cases. Skyrocketing cases meant an increase in hospitalizations, which has lowered the region’s ICU capacity. The chart below shows the trajectory of new cases in these counties.
Clearly, the new rules haven’t stopped coronavirus cases from exploding. But it’s still possible they are making a difference. Cases might have risen even faster without the rules. In the short-term, it’s nearly impossible to know. (For a skeptical view of the new policies, I suggest listening to this interview with UCSF infectious diseases doctor Monica Gandhi.)
Though we can’t know at this point if the policies are working to reduce transmission, we can see if they are changing any behaviors. There are a number of a fast turnaround data sources that can give us a hint as to whether the new rules altered people’s choices.
For example, one big question is whether the rules are actually causing people to stay at home more. The company SafeGraph uses mobile phone data to track the share of people who never leave the house on a given day (Defined as not going more than 100 meters from your house). The chart below shows SafeGraph’s stay-at-home data for San Francisco—SafeGraph’s sample includes more than 10% of the county’s residents. The data show that in the week after the order, rates of staying at home did go up. They then fell in the week after that.
It’s hard to know why that might be. It could have also been a result of the weather or other factors besides the stay-at-home orders, like the need to go Christmas shopping. But I think it is suggestive of people taking the rules seriously for a bit, but then deciding to go back to normal.
Below are the stay at home rates for the other four counties. They mostly show a similar patten. Stay-at-home rates were higher on the 11th and 18th than on the Friday, December 4th, suggesting the stay-at-home rules might be doing something. But they were generally lower on the 18th than the 11th.
Another way we can look at behavior is by looking at driving directions data collected by Apple. During the pandemic, Apple has been releasing data on the number of requests for driving directions in US counties compared to prior to the pandemic. For example, on November 29th, driving requests were more than 40% lower in San Francisco than on January 13th of this year.
This data tells a similar story about the response to the new restrictions. Driving direction requests dropped in the week after the order but then jump backed up the next week. For example, in Alameda County driving direction requests were down 14% on the average day from November 30th to December 6th. They then fell to 19% below normal from December 7th to 13th, but went back up to only 13% from December 14th to 20th. Apple’s data on requests from walking and public transit directions tell a similar tory.
Google also produces data based on direction requests in Google Maps. This data shows the increase or decline in directions to certain locations, like grocery stores and parks. This data does not show quite as clear a story, but it does appear there was a dip in people going to parks and retail after the order went into effect, but that it didn’t last long.
Finally, I examined data on BART usage. It also shows a pattern of a decline and a bounce back, though it’s subtle. From November 30th to December 6th, BART use was down 86% compared to the same period last year. It jumped to 88% below average the next week, but then returned to just 87% the week after.
Again, it’s hard to say with any certainty how much these trends have to do with the stay-at-home orders. But the data does make it clear that the orders did not make a massive long-lasting change in how much people were going places. This isn’t much a surprise given there has been little enforcement of the rules. Still, we can hope that the impositions of the rules scared some people into making safer choices in terms of distancing and being inside when they do see people.
Bay Area media recommendations of the week
Add the Department of Building Inspection (DBI) to the long list of factors that makes San Francisco life so expensive. In a recent article for the San Francisco Chronicle, the excellent reporter Heather Knight details just how difficult it is for an average person to get a permit to make changes to their home in the city.
Knight points out that the city’s “Getting a City Permit” guide starts with the following quote: “Obtaining a city permit can undoubtedly be one of the most confusing processes you may ever experience.” For the rich though, it’s not such a big deal. They can hire a “permit expediter” to deal with the hassle of getting permission to rebuild their gazebo or fix their garage. For residents with less financial means, it can mean waiting years or foregoing projects. The main problems, according to Knight, are a lack of an easy-to-use online permitting system and a byzantine set of rules for many permits.
(Seen any great Bay Area media recently? Send it to me!)
Dan’s favorite things
Jenny Odell’s How to Do Nothing: Resisting the Attention Economy is a brilliant book about how tapping into local nature and culture is the best way to tap out of social media. It was also, to my surprise, an incredible guidebook for the Bay Area. Odell lives in Oakland, and much of the book is spent describing neighborhoods, parks, and organizations in the region.
Even if you have no interest in getting off Twitter or Facebook, you will probably love her descriptions of Bay Area birds. Here is an excerpt I particularly loved that weaves together her experience after Trump won the presidency with a description of a common local bird:
“In the middle of this postelection heartbreak and anxiety, I was still looking at birds. Not just any birds, and not even a species, but a few specific individuals. First, it was a couple of black-crowned night herons that reliably perch outside of a KFC in my neighborhood, almost day and night. If you’ve never seen one, night herons are stocky compared to other herons. My boyfriend once described them as a cross between a penguin and Paul Giamatti. They have a grumpy stoicism about them, sitting hunched over with their long neck completely hidden away. I sometimes affectionately refer to these birds as the ‘colonels’ (because of their location) or ‘my precious footballs’ (because of their shape).
Without really thinking about it, I modified my path home from the bus to pass by the night herons whenever I could, just to be reassured by their presence. I remember specifically feeling comforted by the presence of these strange birds, like I could look up from the horrifying maelstrom of the day’s Twitter and they’d probably be there, unmoving with their formidable beaks and their laser-red eyes… The KFC is near Lake Merritt, a man-made lake in a completely developed area that, like much of the East Bay and the Peninsula, used to be the type of wetlands that herons and other shorebirds love. Night herons have existed here since before Oakland was a city, holdovers from that marshier time. Knowing this made the KFC night herons begin to seem like ghosts to me, especially at night when the streetlights would make their white bellies glow from below.”
Thanks for your time, and see you in a couple of weeks.
If you think a friend might enjoy this newsletter, please forward it along. You can follow me on Twitter at @dkopf or email me at firstname.lastname@example.org. The Golden Stats Warrior logo was made by the great Jared Joiner, the best friend a newsletter writer could have. Follow him @jnjoiner. Also, thanks to my favorite mushroom forager Kanchan Gautam for copy editing this week.