COVID-19 and the response to it are having far-reaching impacts throughout society, and the MBTA is no exception. Here at OPMI, we are working hard to analyze its impacts on ridership, performance, and other aspects of the T and the transportation system. Last week, we posted about how the pandemic is affecting ridership, and provided daily updates in that post. Apart from informing the public, this work is also helping the MBTA make service decisions about where extra service is needed in order to keep our passengers and employees safe. This post looks back at the week of 3/16, when major changes in ridership began to occur.
While we are trying to match service with demand, we should remind everyone that Governor Baker has issued a stay at home advisory and ordered all non-essential businesses to be closed. In his words: “Just because the T is open does not mean we think it’s a good idea to take the train downtown to meet up with friends.
By limiting the use of public transportation to essential activities, we will not only slow the spread of the virus — but we will better protect our health care workers, grocery store workers and others who are working every day to keep us safe.
Everyone is advised to stay at home and limit all unnecessary activities.”
Please see the continuously-updated page here for the latest updates on how the MBTA is responding to the pandemic: www.mbta.com/covid-19
Our usual ridership reporting includes factors to account for passengers who we do not observe through our automated equipment, and we usually wait at least a few weeks before reporting anything due to the delay in transferring data from our vehicles. We also conduct in-person counts to verify automated data and improve accuracy for our end of year reporting.
We did not have time to do our normal analysis and reporting, so we had to focus on the best sources we have that were reasonably representative of the system. So we focused on three data sources for this post: Counts of validations at gated stations from the fare collection system, bus ridership estimates from automated passenger counters, and mTicket activations to get an idea of ridership on commuter rail. Because all of these sources usually have extra processing and QA/QC done as noted in the previous paragraph, all ridership estimates in this post should be considered very preliminary and subject to change.
To examine ridership on the rapid transit system, we used validations (taps or ticket insertions) at the 64 gated stations in the MBTA system. This data came from the fare collection system and is not adjusted to account for passengers who enter the gates without interacting with the equipment (this can be children, fare evaders, or people who enter when the gates aren’t functioning).
We set up a special data transfer to gather the total validations by day, and then grouped them by station and by line. For stations where passengers can board multiple lines, we use a rough “split” factor to assign riders to each line (For example, at Park St, we estimate that 54% of people entering the gates are then going to board the Red Line, and 46% go on to board the Green Line).
The below chart shows the total taps by line since March 1:
To show these data a different way, see the below table. We’ve chosen the week of 2/24-2/28 as a “normal” comparison week and calculated the percentage change last week from that point. You can also download these data as CSV files at the end of this section.
|Line||Average week of 2/24||Change 3/18||Change 3/19||Change 3/20*|
*3/20 data does not include validations at Malden Center due to a data issue
The major impacts of the pandemic and shutdown are clear from the above. Importantly, though, the change in ridership was not uniform. You can see from the above that the Blue Line was roughly 70% less busy than normal by the end of the week, while the Silver Line’s gated stations had lost over 90% of their usual passengers. There were other differences when you break ridership down by station.
Stations with the largest and smallest changes are listed below:
|Station||Change from week of 2/24 to Friday, 3/20|
|World Trade Center||-93%|
|Station||Change from week of 2/24 to Friday, 3/20|
As you can see, stations where much of the ridership comes from a nearby college, or tends to be more white-collar, had a larger drop, while much of the Blue Line had a much smaller drop.
Download more data here (These files are updated periodically. Last update: 3/31/20):
Gated Stations by Line [csv]
The above chart shows total ridership by day as estimated from the APCs on board buses. The more recent dates here have less precision than the earlier dates, but we are fairly confident in these totals. You can see that the overall drop in bus ridership was significant but more modest — roughly a 69% drop from the week of 2/24 through last week (comparing weekdays). You can see the differences by route in the below chart of the top 20 routes:
As with the gated stations, you can see a fairly wide range in the level of change depending on the route. Without doing a detailed analysis, it seems plausible that as you might expect, routes where more riders are able to take time off, work from home, and self-isolate saw a larger drop in ridership. We will keep an eye on these trends as the response to COVID-19 continues.
While we don’t have detailed ridership from commuter rail on a daily basis, we took a look at the number of activations and purchases on the mTicket app as a proxy for total riders. mTicket activations were at about 3% of their normal amount by the end of the week, although ridership is likely somewhat higher since mTicket usage is made up of more occasional riders.
For the RIDE, we have very detailed data as each completed trip is recorded in the RIDE’s software. We compared the trips taken last week to the average daily trips taken the week of 2/24 and found the following:
|Date||Trips Taken||Change from week of 2/24|
Understanding that a significant number of people continue to rely on the MBTA, we will keep a close eye on ridership levels and as always, learn what we can from them to continue making data-driven decisions that best address our customers’ needs. Safety for customers and employees is, and always will be, at the forefront of our decision-making.