Tech
Data stories track the impact of COVID and notify Boston policy
The MetroLab Network has partnered with Government Technology to provide readers with a segment called the MetroLab Innovation of the Month series. This segment focuses on influential technology, data and innovation projects underway between cities and universities. If you would like to know more or contact the project leader, please contact MetroLab ([email protected]) for more information.
This month’s Innovation of the Month series focuses on a combination of efforts being made in Boston to combine existing data on neighborhood-level quality of life with a survey of residents’ behavior during a pandemic. This data was then extracted into digestible stories that help researchers better connect with the community on these topics. Ben Levine of MetroLab talked with Dan O’Brien, Alina Ristea and David Brade of Northeastern University about their project.
Ben Levine: Your team is working on multiple initiatives summarized in the “Urban Data Support Systems During a Pandemic” project. What are the different parts of this project and who is involved in them?
Dan O’Brien: Boston’s data support system consists of two main initiatives. First, the COVID in the Boston database includes a number of managed and internet-collected data sources curated by us to capture events and situations in the Boston metropolitan area before, during, and after the pandemic. It is. Second, a “Life in Boston during COVID-19” survey, conducted in collaboration with the UMass Boston Research Center and the Boston Public Health Commission (BPHC), found 1,600 people on pandemic-wide behavior, experience, and attitudes. Answers were collected from Boston citizens. The combination of these two resources addresses a variety of questions and concerns, emphasizing the range of racial and socio-economic inequality, especially from infection rates to social distance capabilities, housing and evictions, and regional economic activity. I’m talking.
In addition to the research collaborators, we worked closely with various partners to design and collect these resources. We are currently working closely with many public agencies such as BPHC, New Urban Mechanics Mayor’s Office, Neighborhood Development Bureau, Metropolitan Planning Council, Boston Police Department, Neighborhood Services Department, and Massachusetts Bay Transportation Department. Focus on insights that can help you recover.
Levine: What kind of data does the COVID in the Boston database have? How do you think you can take advantage of them?
Alina Ristea: The Boston database COVID is a mix of management records and data taken from online sources, and we have created variable-by-variable documentation for potential users. The database was originally built in the summer and updated this month. Management records include asset valuations, building permits, code and asset breaches, food inspections, and Boston CityScore performance tracking. During the update, we will add data for 911 and 311 and weekly and daily cases of COVID infection in Massachusetts. Online data includes Craigslist posts and Yelp. Reviews from various sources (such as Foursquare), Airbnb lists, and Places of Interest (POI). Due to their vast metadata, geographical specificity, and vertical nature, these data can be leveraged for multiple topics related to urban systems. You can also merge these to facilitate more advanced analysis. The database supports a wide range of questions, including commerce and economic activity, such as tracking restaurant viability through Yelp. And food inspection; disadvantages due to housing dynamics and Craigslist and code and property breaches. City planning and gentrification by building permit. Crime and disorder due to code and property breaches, and reports of 911 and 311. And, of course, public health by analyzing the timeline of infections throughout the community.
Levine: Please tell us about the “Life in Boston during COVID-19” survey. How does this effort work with the database?
O’Brien: Surveys are a unique window to personal experience and perspective, often underestimated in the age of big data. The survey responses will show how residents of different Boston communities were affected by the pandemic. Their concerns about the threat that viruses and recessions pose to themselves, their families and their neighborhoods. Their attitude towards masks, social distance, and transmission risk. And the challenges they faced to keep their families safe, healthy and nourished. However, the depth of these responses and their implications for the community can be greatly improved if coordinated with other datasets. Importantly, the extensive data from the Boston Regional Survey Initiative (BARI) on Neighbors allows these respondents to observe how they are active in the region, from crime to economic activity to housing.
Ristea: We also analyzed the survey responses, along with Cuebiq and SafeGraph, two sources of anonymized, mobile-generated mobility data. Both have been widely used by researchers around the world during COVID to understand the effects of mobility on communication, changes in human behavior, and the effectiveness of social distance policies. Of particular interest is SafeGraph’s capture of patterns of visits to POIs such as grocery stores and parks. We use a combination of these data and research to further analyze the factors that drive activity and movement communication and impact on equity during a pandemic.
Levine: What did you find in creating a bite-sized data story? Did you find anything particularly surprising?
O’Brien: Having presented insights from our work, we wanted to stay true to the dual purpose of scientific rigor and public influence. The former requires a long-term report with a thorough methodology and accurate explanation of the results. These are not always accessible to our most important audience: policy makers and practitioners who are too absorbed in serving the community to compile such reports. For this reason, we decided to split the report into “data stories” so that we could provide one working insight at a time.
David Brade: Data stories have been able to facilitate conversations with communities that are usually less interested in the impact and exposure of data. By releasing these data stories via social media, especially Twitter, we have attracted the attention of the media, community leaders, and elected officials. This allowed the community to engage with us and each other and gain a better understanding of pandemic sub-themes such as wearing masks, high-risk behavior, asymptomatic spread, and pandemic political polarization. .. The data story proved to be an important driving force in emphasizing the value of the entire series of reports.
Levine: Can you elaborate on one of these data stories? What is a particularly compelling lesson? Also, how do you think the information can be used in the future?
Blade: A data story that balances food access and risk of infection surveyed households that were able to adopt strategies to secure food while limiting the risk of exposure. The analysis reveals a very clear strategy for this throughout the socio-economic spectrum. Residents of Color’s neighborhood visited the grocery store much more often than others. Many scholars began to explain when they posted this data story. For example, you can’t afford to make large, infrequent purchases, or it’s difficult to carry groceries for those who don’t have a car. Somewhat surprisingly, it turns out that the tendency of wealthy locals to deliver food and groceries fully explains these disparities. This was a clear underestimated example that income inequality was a major driver of how to navigate exposure during a pandemic.
Levine: This model, which measures the difference in the effects of COVID-19 in different regions of the same city, is fascinating. Can other cities adopt this model? What is Boston’s next step on this project?
O’Brien: Of course. Some parts of this work are more ambitious than others, but they are all replicable. The most accessible access to cities across the country is the careful use of administrative records to better understand the needs of the community. This is at the heart of recent trends towards data-driven policies and practices and is currently the most important. Cities need to closely track their business licenses to find out where the closure is. The housing court records to find out where the eviction is. 311 and 911 report to find out where problems and tensions are rising. Building permits are to know where the capital is returning (and not). Given that these data systems usually already exist, they are used to identify the most needed communities, more specifically, the exact needs of the present and the coming months. Is not a distant bridge. Scraping Internet data to complement these resources requires an additional layer of skill and capacity, but it is certainly within reach for many communities.
Finally, research is expensive and requires foresight and patience. However, many universities and private sectors are ready to help. It’s easy to forget that society hasn’t left the forest yet, and even if vaccination achieves herd immunity, economists expect a long, if not years, recovery period. I will. Research continues to help community members see, understand, and feel the experience and perspectives of navigating these difficult and unprecedented times in ways that “big data” cannot.
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