In this month’s installment of the Innovation of the Month series, we focus on a combination of efforts happening in Boston to combine existing data about quality of life at the neighborhood level with surveys about residents’ behavior during the pandemic. This data was then distilled into digestible stories that help the researchers better connect with their community on these topics. MetroLab’s Ben Levine spoke with Dan O’Brien, Alina Ristea and David Brade from Northeastern University about their project.
Ben Levine: Your team is working on multiple efforts, rolled up under the “Data-Support System for a City During a Pandemic” project. What are the different parts of this project, and who has been involved in them?
Dan O’Brien: The data-support system for Boston comprises two main efforts. First, the COVID in Boston Database contains numerous administrative and Internet-gathered data sources we curated that capture the events and conditions of greater Boston before, during and after the onset of the pandemic. Second, the “Living in Boston During COVID-19” survey, which we conducted with UMass Boston’s Center for Survey Research and the Boston Public Health Commission (BPHC), collected responses from 1,600 Bostonians about their behaviors, experiences and attitudes throughout the pandemic. The combination of these two resources has spoken to a wide variety of questions and concerns, especially highlighting a range of racial and socioeconomic inequities — from infection rates, to the ability to social distance, to housing and evictions, to local economic activity.
In addition to our collaborators on the survey, we have worked closely with a variety of partners to design and collect these resources. We are now working closely with numerous public agencies, including BPHC, the Mayor’s Office of New Urban Mechanics, the Department of Neighborhood Development, the Metropolitan Area Planning Council, Boston Police Department, the Office of Neighborhood Services and the Massachusetts Bay Transportation Authority, as we turn our attention to insights that can inform the recovery.
Levine: What kinds of data are in the COVID in Boston Database? How do you expect they could best be leveraged?
Levine: Can you tell us about the “Living in Boston During COVID-19” survey? How does this effort interlock with the database?
O’Brien: Surveys are a unique window into the experiences and perspectives of individuals, something that is often undervalued in the age of big data. Through the survey responses we see how the residents of Boston’s various communities have been impacted by the pandemic; their concerns about the threats the virus and the economic recession pose to themselves, their families and their neighborhoods; their attitudes toward masks, social distancing and transmission risk; and the challenges they have faced in keeping their families safe, healthy and fed. The depth of these responses and what they mean for communities, however, is greatly enhanced if we can coordinate them with other data sets. Crucially, extensive data from the Boston Area Research Initiative (BARI) on neighborhoods allow us to observe the context within which these respondents are operating locally on various dimensions, from crime to economic activity to housing.
Ristea: We have also analyzed the survey responses alongside two sources of anonymized, cellphone-generated mobility data: Cuebiq and SafeGraph. Both have been used extensively by researchers worldwide during COVID to understand the impacts of mobility on transmission, changes in human behaviors and the effectiveness of social distancing policies. Of particular interest, SafeGraph captures patterns of visitation to POI, like grocery stores and parks. We are using the combination of these data and surveys to give greater depth to analyses of the factors that drive transmission and the equity implications of activities and movements during the pandemic.
Levine: What did you find in the creation of the bite-size data stories? Were any of the findings particularly surprising?
O’Brien: As we have released the insights from our work, we wanted to be true to the dual purposes of scientific rigor and public impact. The former requires long-winded reports that are thorough in their methodology and precise in the description of results. These are not necessarily accessible to our most important audience: the policymakers and practitioners who are too consumed with serving their communities to piece through such a report. For this reason, we decided to slice the reports up into “data stories” that could provide one actionable insight at a time.
David Brade: The data stories have been able to drive conversations with communities typically less interested in the impact and revelations of data. Releasing these data stories via social media, especially Twitter, has captured the attention of the media, community leaders and elected officials. This has allowed the community to engage with us and each other and elevated the understanding of subthemes of the pandemic, such as mask-wearing, high-risk behaviors, asymptomatic spread and the political polarization of the pandemic. We’ve found the data stories to be a key driver in highlighting the value of the overall series of reports.
Levine: Can you go into detail on one of these data stories? What lessons were particularly compelling, and how do you think the information can be used moving forward?
Levine: This model of measuring the differences in the effects of COVID-19 across different neighborhoods in the same city is fascinating. Can other cities adopt this model? What are the next steps for Boston regarding this project?
O’Brien: Absolutely. Some parts of this work are more ambitious than others, but they are all replicable. The piece that is most immediately accessible to cities around the country is the thoughtful use of administrative records to better understand the needs of communities. This has been at the heart of the trend toward data-driven policy and practice in recent years and is of the utmost importance now. Cities should be scrupulously tracking business licenses to know where closures are; housing courts records to know where evictions are; 311 and 911 reports to know where issues and tensions are rising; and building permits to know where capital is returning (and where it’s not). Given that these data systems typically already exist, it is not a far bridge to cross to use them to pinpoint the communities most in need and, more specifically, the precise needs they have now and will have in the coming months. Scraping Internet data to complement these resources requires an extra layer of skill and capacity but is certainly within reach for many communities.
Last, surveys are expensive and require forethought and patience. But many universities and private vendors are prepared to help. We often forget as a society that we are not out of the woods just yet, and even when we achieve herd immunity through vaccination, economists anticipate a lengthy recovery period lasting months if not years. Surveys will continue to help us see, understand and feel the experiences and perspectives of community members as we navigate these challenging and unprecedented times in a way that “big data” is unable to do.
