Real-Time Geospatial analysis Identifies Gaps in Covid-19 Vaccination in a Minority Population

COVID-19 vaccination is being rapidly rolled out in the US and many other countries, and it is crucial to provide fast and accurate assessment of vaccination coverage and vaccination gaps to make strategic adjustments promoting vaccine coverage. We reported the effective use of real-time geospatial analysis to identify barriers and gaps in COVID-19 vaccination in a minority population living in South Texas on the US-Mexico Border, to inform vaccination campaign strategies. We developed 4 rank-based approaches to evaluate the vaccination gap at the census tract level, which considered both population vulnerability and vaccination priority and eligibility. We identified areas with the highest vaccination gaps using different assessment approaches. Real-time geospatial analysis to identify vaccination gaps is critical to rapidly increase vaccination uptake, and to reach herd immunity in the vulnerable and the vaccine hesitant groups. Our results assisted the City of Brownsville Public Health Department in adjusting real-time targeting of vaccination, gathering coverage assessment, and deploying services to areas identified as high vaccination gap. The analyses and responses can be adopted in other locations

How does community context influence coalitions in the formation stage? a multiple case study based on the Community Coalition Action Theory

<p>Abstract</p> <p>Background</p> <p>Community coalitions are rooted in complex and dynamic community systems. Despite recognition that environmental factors affect coalition behavior, few studies have examined how community context impacts coalition formation. Using the Community Coalition Action theory as an organizing framework, the current study employs multiple case study methodology to examine how five domains of community context affect coalitions in the formation stage of coalition development. Domains are history of collaboration, geography, community demographics and economic conditions, community politics and history, and community norms and values.</p> <p>Methods</p> <p>Data were from 8 sites that participated in an evaluation of a healthy cities and communities initiative in California. Twenty-three focus groups were conducted with coalition members, and 76 semi-structured interviews were conducted with local coordinators and coalition leaders. Cross-site analyses were conducted to identify the ways contextual domains influenced selection of the lead agency, coalition membership, staffing and leadership, and coalition processes and structures.</p> <p>Results</p> <p>History of collaboration influenced all four coalition factors examined, from lead agency selection to coalition structure. Geography influenced coalition formation largely through membership and staffing, whereas the demographic and economic makeup of the community had an impact on coalition membership, staffing, and infrastructure for coalition processes. The influence of community politics, history, norms and values was most noticeable on coalition membership.</p> <p>Conclusions</p> <p>Findings contribute to an ecologic and theory-based understanding of the range of ways community context influences coalitions in their formative stage.</p

Weight loss and weight gain among participants in a community-based weight loss Challenge

Abstract Background To describe the characteristics of participants who registered for multiple annual offerings of a community-based weight loss program called The Challenge, and to determine participant characteristics associated with weight change over multiple offerings of The Challenge occurring during the years 2010–2016. Methods Multivariable linear mixed effects analyses were conducted to describe percent weight change within and between offerings of The Challenge by participant characteristics. Results There were 669 and 575 participants included in the within and between analyses, respectively, for offerings of The Challenge. Among the 434 participants who lost weight in their first attempt at The Challenge and completed the initial weigh-in for a subsequent offering of The Challenge, 22.4% maintained their weight loss or had greater weight loss by the next Challenge, 40.3% gained back some weight, and 37.3% gained back all or more of the weight they lost during their first Challenge. Men had a significantly greater percent weight loss compared to women in their first and second Challenge and men were more likely to gain weight between Challenges. Participants who returned to more Challenges had a greater accumulated percent weight loss compared to those who returned to fewer Challenges. Conclusions The current weight loss Challenge appears to contribute to helping a percentage of participants lose weight and maintain some or all of the weight loss