Dwayne E. Porter

Background: Children with Down syndrome often have co-occurring physical conditions affecting well-being, and respiratory issues remain a leading cause of hospitalization and death among people with Down syndrome. Parents of children with Down syndrome experience stressors associated with respiratory illness and challenges navigating healthcare access. No prior qualitative study has examined parental perspectives on respiratory health specifically among children with Down syndrome. Identifying parental concerns can help in the development of strategies to mitigate respiratory ailments in children with Down syndrome. Methods: One-hour, semi-structured interviews were conducted among 24 families of children with Down syndrome to understand respiratory concerns. Findings were identified through codebook thematic analysis. Results: The themes identified included persistent concerns about respiratory health, repeated impact from acute and chronic respiratory issues, a rapid and unexpected decline in health during respiratory illness, insurance coverage concerns, and a lack of confidence in assessing air quality which could impact respiratory health. Conclusions: Insights gained from interviews of parents of children with Down syndrome can help policy makers identify opportunities to prevent and mitigate respiratory health problems. Findings underscore the importance of clinician responsiveness to parental concern about rapid deterioration and suggest that insurance coverage policies for this high-risk population warrant further research and policy consideration.

Schools are well-positioned to provide physical activity opportunities to help youth achieve the recommended 60 or more daily minutes of moderate-to-vigorous physical activity. The Children’s Physical Activity Research Group (CPARG) at the University of South Carolina has focused on understanding physical activity in school-aged youth for 30+ years. The purpose of this article was to critically review (CPARG) contributions to the field in school settings and school-age youth. We reviewed 127 published CPARG articles from six research projects conducted between 1993–2019. The review was guided by questions in five categories: measurement of physical activity and its determinants, characteristics of physical activity behavior, correlates/determinants of physical activity, physical activity interventions, and race/ethnicity and physical activity. Results were summarized by question and synthesized across categories. CPARG contributions included assessing physical activity levels, patterns, forms, and contexts; identifying and measuring physical activity correlates/determinants; and conducting school-based physical activity interventions. Identifying multiple domains of physical activity determinants enables researchers and practitioners to select/design age-appropriate, valid, and reliable instruments to assess determinants. Focusing on determinants enables them to create effective physical activity interventions, environments, programs, and policies in schools. These efforts must address race/ethnicity differences, ensuring that measurement instruments and intervention strategies are culturally appropriate.

In response to increasing threats from sea-level rise and storm surge, the City of Charleston, South Carolina, and the US Army Corps of Engineers (USACE) propose constructing a seawall around the Charleston peninsula. The proposed seawall will terminate close to lower wealth, predominantly minority communities. These communities are identified as environmental justice (EJ) communities due to their history of inequitable burdens of industrial and urban pollution and proximity to highways and US Environmental Protection Agency (EPA) designated Superfund sites. The present study documents community concerns and opinions related to the proposed seawall, existing flooding problems, and other issues. The project was guided by knowledge co-production and participant-observation approaches and included interviews with community members, collection of locality-specific data, GIS mapping to visualize key issues, development of an ArcGIS Story Map, and participation in public meetings. Community concerns are reported in the voices of community members and fell into eight major themes: community connections, drainage, impacts of road infrastructure, displacement, increasing vulnerability, sense of exclusion and isolation, mistrust of government, and civic engagement. Community members were significantly engaged in the study and are the owners of the results. As one of the first US East Coast cities pursuing major structural adaptation for flooding, Charleston is likely to become a model for other cities considering waterfront protection measures. We demonstrate the importance of meaningful engagement to ensure that climate adaptation will benefit all, including marginalized communities, and have as few unintended negative consequences as possible. Bringing more people to the table and creating vibrant, long-term partnerships between academic institutions and community-based organizations that include robust links to governmental organizations should be among the first steps in building inclusive, equitable, and climate resilient cities.

Opioid dependence and opioid-related mortality have been increasing in recent years in the United States. Available and accessible treatments may result in a reduction of opioid-related mortality. This work describes the geographic variation of spatial accessibility to opioid treatment programs (OTPs) and identifies areas with poor access to care in South Carolina. The study develops a new index of access that builds on the two-step floating catchment area (2SFCA) method, and has three dimensions: a facility attractiveness index, defined by services rendered incorporated into the Huff Model; a facility catchment area, defined as a function of facility attractiveness to account for variable catchment size; and a Social Vulnerability Index (SVI) to account for nonspatial factors that mitigate or compound the impacts of spatial access to care. Results of the study indicate a significant variation in access to OTPs statewide. Spatial access to OTPs is low across the entire state except for in a limited number of metropolitan areas. The majority of the population with low access (85%) live in areas with a moderate-to-high levels of social vulnerability. This research provides more realistic estimates of access to care and aims to assist policymakers in better targeting disadvantaged areas for OTP program expansion and resource allocation.

Background: Human movement is one of the forces that drive the spatial spread of infectious diseases. To date, reducing and tracking human movement during the COVID-19 pandemic has proven effective in limiting the spread of the virus. Existing methods for monitoring and modeling the spatial spread of infectious diseases rely on various data sources as proxies of human movement, such as airline travel data, mobile phone data, and banknote tracking. However, intrinsic limitations of these data sources prevent us from systematic monitoring and analyses of human movement on different spatial scales (from local to global). Objective: Big data from social media such as geotagged tweets have been widely used in human mobility studies, yet more research is needed to validate the capabilities and limitations of using such data for studying human movement at different geographic scales (eg, from local to global) in the context of global infectious disease transmission. This study aims to develop a novel data-driven public health approach using big data from Twitter coupled with other human mobility data sources and artificial intelligence to monitor and analyze human movement at different spatial scales (from global to regional to local). Methods: We will first develop a database with optimized spatiotemporal indexing to store and manage the multisource data sets collected in this project. This database will be connected to our in-house Hadoop computing cluster for efficient big data computing and analytics. We will then develop innovative data models, predictive models, and computing algorithms to effectively extract and analyze human movement patterns using geotagged big data from Twitter and other human mobility data sources, with the goal of enhancing situational awareness and risk prediction in public health emergency response and disease surveillance systems. Results: This project was funded as of May 2020. We have started the data collection, processing, and analysis for the project. Conclusions: Research findings can help government officials, public health managers, emergency responders, and researchers answer critical questions during the pandemic regarding the current and future infectious risk of a state, county, or community and the effectiveness of social/physical distancing practices in curtailing the spread of the virus. International Registered Report Identifier (IRRID): DERR1-10.2196/24432

The Gulf of Mexico (GoM) region is prone to disasters, including recurrent oil spills, hurricanes, floods, industrial accidents, harmful algal blooms, and the current COVID-19 pandemic. The GoM and other regions of the U.S. lack sufficient baseline health information to identify, attribute, mitigate, and facilitate prevention of major health effects of disasters. Developing capacity to assess adverse human health consequences of future disasters requires establishment of a comprehensive, sustained community health observing system, similar to the extensive and well-established environmental observing systems. We propose a system that combines six levels of health data domains, beginning with three existing, national surveys and studies plus three new nested, longitudinal cohort studies. The latter are the unique and most important parts of the system and are focused on the coastal regions of the five GoM States. A statistically representative sample of participants is proposed for the new cohort studies, stratified to ensure proportional inclusion of urban and rural populations and with additional recruitment as necessary to enroll participants from particularly vulnerable or under-represented groups. Secondary data sources such as syndromic surveillance systems, electronic health records, national community surveys, environmental exposure databases, social media, and remote sensing will inform and augment the collection of primary data. Primary data sources will include participant-provided information via questionnaires, clinical measures of mental and physical health, acquisition of biological specimens, and wearable health monitoring devices. A suite of biomarkers may be derived from biological specimens for use in health assessments, including calculation of allostatic load, a measure of cumulative stress. The framework also addresses data management and sharing, participant retention, and system governance. The observing system is designed to continue indefinitely to ensure that essential pre-, during-, and post-disaster health data are collected and maintained. It could also provide a model/vehicle for effective health observation related to infectious disease pandemics such as COVID-19. To our knowledge, there is no comprehensive, disaster-focused health observing system such as the one proposed here currently in existence or planned elsewhere. Significant strengths of the GoM Community Health Observing System (CHOS) are its longitudinal cohorts and ability to adapt rapidly as needs arise and new technologies develop.