The purpose of the medication-assisted treatment (MAT) facility maps is to identify areas on a state-by-state basis that may be potentially underserved by existing treatment facilities. The maps are created with a methodology that seeks to include the highest potential need areas from individual counties so that county-level stakeholders are also informed. The maps are meant to be used as a tool for policy makers to determine potentially underserved areas—not as a definitive representation of these areas.

This data collection is the first wave of an intensive study in Boston, Chicago, and San Antonio, which was initiated to assess the well-being of low-income children and families in the post-welfare reform era. The project investigates the strategies families have used to respond to reform, in terms of employment, schooling or other forms of training, residential mobility, and fertility. Central to this project is a focus on how these strategies affect children's lives, with an emphasis on their health and development as well as their need for, and use of, social services. For the first wave of the study, between March 1999 and December 1999, a random sample of approximately 2,400 households with children in low-income neighborhoods in Boston, Chicago, and San Antonio were selected for interviews. Forty percent of the families interviewed were receiving cash welfare payments at the time of the interview. Each household had a child aged 0 to 4 or aged 10 to 14 at the time of the interview. The child and the child's primary female caregiver are the focus of the study. Extensive baseline information was gathered at the initial personal interview with the caregivers, tested younger children were assessed, and older children were interviewed. All interviews were conducted in-person using a computerized instrument. The third wave of data collection took place between February 2005 and January 2006, when the focal children were aged 5 to 10 or aged 15 to 20. Between May 2005 and May 2006, interviews were conducted with the teachers of the focal children.

IntroductionAccess to COVID-19 testing has been inequitable and misaligned with community need. However, community health centers have played a critical role in addressing the COVID-19 testing needs of historically disadvantaged communities. The aim of this paper is to explore the perceptions of COVID-19 testing barriers in six Massachusetts communities that are predominantly low income and describe how these findings were used to build tailored clinical-community strategies to addressing testing inequities.MethodsBetween November 2020 and February 2021, we conducted 84 semi-structured qualitative interviews with 107 community health center staff, community partners, and residents. Resident interviews were conducted in English, Spanish, Vietnamese, and Arabic. We used a 2-phase framework analysis to analyze the data, including deductive coding to facilitate rapid analysis for action and an in-depth thematic analysis applying the Social Ecological Model.ResultsThrough the rapid needs assessment, we developed cross-site suggestions to improve testing implementation and communications, as well as community-specific recommendations (e.g., locations for mobile testing sites and local communication channels). Upstream barriers identified in the thematic analysis included accessibility of state-run testing sites, weak social safety nets, and lack of testing supplies and staffing that contributed to long wait times. These factors hindered residents' abilities to get tested, which was further exacerbated by individual fears surrounding the testing process and limited knowledge on testing availability.DiscussionOur rapid, qualitative approach created the foundation for implementing strategies that reached underserved populations at the peak of the COVID-19 pandemic in winter 2021. We explored perceptions of testing barriers and created actionable summaries within 1–2 months of data collection. Partnering community health centers in Massachusetts were able to use these data to respond to the local needs of each community. This study underscores the substantial impact of upstream, structural disparities on the individual experience of COVID-19 and demonstrates the utility of shifting from a typical years' long research translation process to a rapid approach of using data for action.