The Landscape of Severe Combined Immunodeficiency Newborn Screening in the United States in 2020: A Review of Screening Methodologies and Targets, Communication Pathways, and Long-Term Follow-Up Practices.

Severe combined immunodeficiency (SCID) is T cell development disorders in the immune system and can be detected at birth. As of December 2018, all 53 newborn screening (NBS) programs within the United States and associated territories offer universal screening for SCID. The Association of Public Health Laboratories (APHL), along with the Immune Deficiency Foundation (IDF), surveyed public health NBS system laboratory and follow-up coordinators regarding their NBS program's screening methodologies and targets, protocols for stakeholder notifications, and long-term follow-up practices. This report explores the variation that exists across NBS practices, revealing needs for efficiencies and educational resources across the NBS system to ensure the best outcomes for newborns.

Information and Emotional Support Needs of Families Whose Infant Was Diagnosed With SCID Through Newborn Screening.

Background: Now that severe combined immune deficiency (SCID) has been added to newborn screening panels in all 50 states in the U.S., there is a need to develop and disseminate well-designed educational materials to parents who need information to make informed decisions about treatment and care for identified infants. SCID Compass was designed to address this gap. We summarize the results of two needs assessment activities for parents-a journey mapping exercise and online survey-which will inform the development of a website and new resources. Methods: We conducted in-depth interviews with seven parents of children with SCID identified through newborn screening. Participants were asked to complete a journey map to describe key timepoints related to SCID, starting at diagnosis through present day. This qualitative information informed an online survey that was completed by 76 parents who had a child with SCID. All participants were from the United States. Results: Analysis of journey maps revealed five distinct stages that parents experience: (1) Diagnosis, (2) Pre-Treatment, (3) Treatment, (4) Post-Treatment, and (5) The New Normal. At each stage, parents described unique emotions, challenges, contextual factors that can make a difference in their experience, and information and resource needs. Survey results indicated the highest-rated information needs for parents were understanding available treatment options and what to expect across the SCID lifespan. Emotional support needs included dealing with uncertainty about child's future and additional opportunities to connect with other families. Parents preferred receiving new materials from their healthcare provider or other families, and preferred materials in print, from social media, or online. Several differences were found among subgroups of parents, including those whose child had been identified through newborn screening as well as those considered medically underserved. Conclusions: Findings about unmet parent needs and informational preferences will serve as the foundation for creating a suite of resources for those who have a child with SCID. The materials will be tailored to specific stages of the journey. By using a family-centered approach, we will help to ensure that the materials designed and developed as part of SCID Compass will be understandable, comprehensive, and useful.

County lung cancer mortality: a decision tree model for control and prevention.

OBJECTIVE: It is widely accepted that smoking prevalence and poverty predict the occurrence of lung cancer mortality. The question asked in the study was: What are the important factors for counties that are useful to public health professionals? We sought to provide an answer, using a recursive partitioning approach applied to county-level indicators. METHODS: Classification and regression tree analysis is relatively unexplored for its utility in public health. Using available ecologic data, county lung cancer mortality was modeled by several predictor variables from a larger set of candidates. We constructed a tree on the basis of statistical software, R. RESULTS: Seven groupings were defined. Not surprisingly, smoking prevalence was a major determiner of tree nodes, as were prior coronary heart disease mortality, poverty, and National Air Toxics Assessment excess cancer deaths estimates. Lung cancer mortality groupings ranged from 47 per 100000 in the best 2 groupings (leaves) to 85 per 100000 in the worst grouping of 52 local jurisdictions. CONCLUSIONS: Ecologic data portrayed in a classification and regression tree have utility for spurring etiologic investigation, tracking county outcomes, developing policy at any governmental level, and guiding program design and management. Community by community, improvements are not yet at Healthy People 2010 targets. Individual communities may benefit through efforts to focus attention on aspects such as smoking levels, poverty, air quality, or region, highlighted by this analysis.