How education and racial segregation intersect in neighborhoods with persistently low COVID-19 vaccination rates in Philadelphia

Spatial inequities in COVID-19 vaccination in Philadelphia by race and income

Objective

Vaccination is a key intervention to prevent severe COVID-19, but in the early months of vaccination availability in the United States, there were wide spatial inequities in vaccination by neighborood racial-ethnic composition and socioeconomic status. To explore whether and how these inequities persisted, we examined the association between neighborhood-level income and racial-ethnic composition and COVID-19 vaccination coverage in Philadelphia, and described trends in inequities in 2021 and 2022.

Methods

Using vaccination data for 46 Philadelphia neighborhoods (zip codes), from the Philadelphia Department of Public Health, we estimated vaccination coverage on April 18th, September 26th, and November 21st of 2021, as well as April 3rd, June 26th, and August 7th of 2022. We estimated and compared average vaccination coverage by neighborhood-level income and racial-ethnic composition. We explored inequities in coverage by estimating absolute and relative differences in vaccination by date.

Results

COVID-19 vaccination coverage varied substantially by neighborhood-level income and racial-ethnic composition. On all dates, rates were higher in high income and non-Hispanic White neighborhoods compared to medium-income, low-income, mixed, and non-Hispanic Black neighborhoods. The absolute and relative differences in vaccination between neighborhoods narrowed over time but persisted through August 2022.

Conclusions

This study provides evidence for the importance of policies that target low-income and non-Hispanic Black neighborhoods during pandemics, including during vaccination rollout, as they have experienced a disproportionate infection, hospitalization, and mortality burden due to COVID-19 and experienced lower vaccination rates.

The difference-making role of staff support in implementing nurse care management for opioid use disorder treatment: A configurational analysis

INTRODUCTION

Understanding conditions in which interventions succeed or fail is critical. The PRimary care Opioid Use Disorders treatment (PROUD) trial, a cluster-randomized hybrid study, tested whether implementation of office-based addiction treatment supported by a nurse increased medication of OUD. Six health systems each provided two primary care (PC) clinics that were randomly assigned to implement the intervention or usual care. This secondary, exploratory study used an innovative mixed methods approach to understand contextual factors that consistently distinguished intervention clinics that increased OUD treatment from those that did not.

METHODS

The study collected contextual information through field notes, health system debriefs, and nurse interviews. Rapid qualitative analysis using a template based on the Practical, Robust Implementation and Sustainability Model identified themes reflecting the external environment, recipients, and implementation infrastructure. The study used qualitative themes to create binary factors reflecting barriers and facilitators potentially critical to implementation success and assigned clinics a factor value of 1 if present and 0 if absent. Two clinic-level outcomes were defined: 1) significant increase in patient-years of OUD treatment from baseline to two-year follow-up; and 2) high rate of OUD treatment at two-year follow-up (≥20 per 10,000 patient-years). Coincidence analysis, a cross-case configurational method, identified difference-makers for both OUD outcomes across intervention clinics.

RESULTS

Qualitative analysis yielded 11 themes which were dichotomized and consolidated into 9 factors. Two factor values perfectly distinguished between intervention clinics with and without increased OUD treatment (outcome #1): (a) presence of strong support from PC staff and providers and (b) lack of OUD treatment in the community. Intervention clinics increased OUD treatment when either factor value was present; when both were absent, clinics did not increase treatment. Strong support from PC staff and providers was independently sufficient to achieve high rates of OUD treatment (outcome #2) while the absence of support explained low rates of treatment. Importantly, strong support from leadership was not sufficient for either outcome.

CONCLUSION

Strong support from staff and providers consistently differentiated between clinics with increased OUD treatment across both outcomes in the PROUD trial from those without. OUD programs should consider increasing support across clinic roles.

Modern approaches to predicting vaccine hesitancy: A scoping review

Introduction

Motivated by the disproportionate burden of infectious diseases on vulnerable populations and the risk of future pandemics, we conducted a scoping review to analyze the state of the literature about "vaccine uptake indices," defined as models that predict vaccination rates by geospatial area. We analyzed novel vaccine uptake indices created in response to the recent COVID-19 pandemic. The aim of this scoping review is to survey the state of the literature regarding vaccine uptake indices relating to COVID-19 and other infectious diseases.

Methods

We conducted a scoping review with a systematic search strategy to identify relevant articles from the databases Embase, PubMed, and Web of Science with title and abstract screening, full-text review, and data extraction.

Results

Database searches resulted in 3,615 potential articles, of which 229 reports were included. Fifteen studies (7%) were determined to be methodologically advanced vaccine uptake indices that had at least three of the following characteristics: the use of individual- and population-level predictor variables (100 [44%]), geo-spatiotemporal analysis (58 [25%]), data usage agnostic to vaccine specificity (50 [22%]), or sociobehavioral frameworks of health (such as the Health Belief Model and Theory of Planned Behavior) (30 [13%]).

Conclusion

This scoping review offers suggestions for future research of next-generation vaccine uptake indices before use in vaccination campaigns of recurring or novel infectious diseases. Areas to pursue include utilizing individual-level data about vaccination behaviors in conjunction with administrative data, solving the challenge of implementing small-area spatiotemporal analysis, using vaccine-agnostic methods that consider data from more than one infectious disease, and assisting causal inference with theoretical frameworks.

Does education influence COVID-19 vaccination? A global view

After the recent hard attempts felt on a global scale, notably in the health sector, the steady efforts of scientists have been materialized in maybe one of the most expected findings of the last decades, i.e. the launching of the COVID-19 vaccines. Although it is not our goal to plead for vaccination, as the decision in this regard is a matter of individual choice, we believe it is necessary and enlightening to analyze how one's educational status interferes with COVID-19 vaccination. There are discrepancies between world states vis-à-vis their well-being and their feedback to crises, and from the collection of features that can segregate the states in handling vaccination, in this paper, the spotlight is on education. We are referring to this topic because, generally, researches converge rather on the linkage between economic issues and COVID-19 vaccination, while education levels are less tackled in relation to this. To notice the weight of each type of education (primary, secondary, tertiary) in this process, we employ an assortment of statistical methods, for three clusters: 45 low-income countries (LICs), 72 middle-income countries (MICs) and 53 high-income countries (HICs). The estimates suggest that education counts in the COVID-19 vaccination, the tertiary one having the greatest meaning in accepting it. It is also illustrated that the imprint of education on vaccination fluctuates across the country groups scrutinized, with HICs recording the upper rates. The heterogeneity of COVID-19 vaccination-related behaviors should determine health authorities to treat this subject differently. To expand the COVID-19 vaccines uptake, they should be in an ongoing dialogue with all population categories and, remarkably, with those belonging to vulnerable communities, originated mostly in LICs. Education is imperative for vaccination, and it would ought to be on the schedule of any state, for being assimilated into health strategies and policies.

Association Between Racial Segregation and COVID-19 Vaccination Rates

OBJECTIVE

To examine the association between county-level Black-White residential segregation and COVID-19 vaccination rates.

DESIGN

Observational cross-sectional study using multivariable generalized linear models with state fixed effects to estimate the average marginal effects of segregation on vaccination rates.

SETTING

National analysis of county-level vaccination rates.

MAIN OUTCOME MEASURE

County-level vaccination rates across the United States.

RESULTS

We found an overall positive association between county-level segregation and the proportion population fully vaccinated, with a 6.8, 11.3, and 12.8 percentage point increase in the proportion fully vaccinated by May 3, September 27, and December 6, 2021, respectively. Effects were muted after adjustment for sociodemographic variables. Furthermore, in analyses including an interaction term between the county proportion of Black residents and the county dissimilarity index, the association between segregation and vaccination is positive in counties with a lower proportion of Black residents (ie, 5%) but negative in counties with the highest proportions of Black residents (ie, 70%).

CONCLUSIONS

Findings highlight the importance of methodological decisions when modeling disparities in COVID-19 vaccinations. Researchers should consider mediating and moderating factors and examine interaction effects and stratified analyses taking racial group distributions into account. Results can inform policies around the prioritization of vaccine distribution and outreach.

Pandemic distress associated with segregation and social stressors

Background

Racial/ethnic minorities are disproportionately impacted by the COVID-19 pandemic, as they are more likely to experience structural and interpersonal racial discrimination, and thus social marginalization. Based on this, we tested for associations between pandemic distress outcomes and four exposures: racial segregation, coronavirus-related racial bias, social status, and social support.

Methods

Data were collected as part of a larger longitudinal national study on mental health during the pandemic (n = 1,309). We tested if county-level segregation and individual-level social status, social support, and coronavirus racial bias were associated with pandemic distress using cumulative ordinal regression models, both unadjusted and adjusted for covariates (gender, age, education, and income).

Results

Both the segregation index (PR = 1.19; 95% CI 1.03, 1.36) and the coronavirus racial bias scale (PR = 1.17; 95% CI 1.06, 1.29) were significantly associated with pandemic distress. Estimates were similar, after adjusting for covariates, for both segregation (aPR = 1.15; 95% CI 1.01, 1.31) and coronavirus racial bias (PR = 1.12; 95% CI 1.02, 1.24). Higher social status (aPR = 0.74; 95% CI 0.64, 0.86) and social support (aPR = 0.81; 95% CI 0.73, 0.90) were associated with lower pandemic distress after adjustment.

Conclusion

Segregation and coronavirus racial bias are relevant pandemic stressors, and thus have implications for minority health. Future research exploring potential mechanisms of this relationship, including specific forms of racial discrimination related to pandemic distress and implications for social justice efforts, are recommended.

Factors associated with timely COVID-19 vaccination in a population-based cohort of patients with cancer

BACKGROUND

In many jurisdictions, cancer patients were prioritized for COVID-19 vaccination because of increased risk of infection and death. To understand sociodemographic disparities that affected timely receipt of COVID-19 vaccination among cancer patients, we undertook a population-based study in Ontario, Canada.

METHODS

Patients older than 18 years and diagnosed with cancer January 2010 to September 2020 were identified using administrative data; vaccination administration was captured between approval (December 2020) up to February 2022. Factors associated with time to vaccination were evaluated using multivariable Cox proportional hazards regression.

RESULTS

The cohort consisted of 356 535 patients, the majority of whom had solid tumor cancers (85.9%) and were not on active treatment (74.1%); 86.8% had received at least 2 doses. The rate of vaccination was 25% lower in recent (hazard ratio [HR] = 0.74, 95% confidence interval [CI] = 0.72 to 0.76) and nonrecent immigrants (HR = 0.80, 95% CI = 0.79 to 0.81). A greater proportion of unvaccinated patients were from neighborhoods with a high concentration of new immigrants or self-reported members of racialized groups (26.0% vs 21.3%, standardized difference = 0.111, P < .001), residential instability (27.1% vs 23.0%, standardized difference = 0.094, P < .001), or material deprivation (22.1% vs 16.8%, standardized difference = 0.134, P < .001) and low socioeconomic status (20.9% vs 16.0%, standardized difference = 0.041, P < .001). The rate of vaccination was 20% lower in patients from neighborhoods with the lowest socioeconomic status (HR = 0.82, 95% CI = 0.81 to 0.84) and highest material deprivation (HR = 0.80, 95% CI = 0.78 to 0.81) relative to those in more advantaged neighborhoods.

CONCLUSIONS

Despite funding of vaccines and prioritization of high-risk populations, marginalized patients were less likely to be vaccinated. Differences are likely due to the interplay between systemic barriers to access and cultural or social influences affecting uptake.

Social Determinants of COVID-19 Vaccination Rates: A Time-Constrained Multiple Mediation Analysis

Objective To estimate the multiple direct/indirect effects of social, environmental, and economic factors on COVID-19 vaccination rates (series complete) in the 3109 continental counties in the United States (U.S.). Study design  The dependent variable was the COVID-19 vaccination rates in the U.S. (April 15, 2022). Independent variables were collected from reliable secondary data sources, including the Census and CDC. Independent variables measured at two different time frames were utilized to predict vaccination rates. The number of vaccination sites in a given county was calculated using the geographic information system (GIS) packages as of April 9, 2022. The Internet Archive (Way Back Machine) was used to look up data for historical dates. Methods  A chain of temporally-constrained least absolute shrinkage and selection operator (LASSO) regressions was used to identify direct and indirect effects on vaccination rates. The first regression identified direct predictors of vaccination rates. Next, the direct predictors were set as response variables in subsequent regressions and regressed on variables that occurred before them. These regressions identified additional indirect predictors of vaccination. Finally, both direct and indirect variables were included in a network model. Results  Fifteen variables directly predicted vaccination rates and explained 43% of the variation in vaccination rates in April 2022. In addition, 11 variables indirectly affected vaccination rates, and their influence on vaccination was mediated by direct factors. For example, children in poverty rate mediated the effect of (a) median household income, (b) children in single-parent homes, and (c) income inequality. For another example, median household income mediated the effect of (a) the percentage of residents under the age of 18, (b) the percentage of residents who are Asian, (c) home ownership, and (d) traffic volume in the prior year. Our findings describe not only the direct but also the indirect effect of variables. Conclusions  A diverse set of demographics, social determinants, public health status, and provider characteristics predicted vaccination rates. Vaccination rates change systematically and are affected by the demographic composition and social determinants of illness within the county. One of the merits of our study is that it shows how the direct predictors of vaccination rates could be mediators of the effects of other variables.

The role of secondary traumatic stress breakthrough champions in reducing worker trauma and improving organizational health using a configurational analysis approach

Background

Emerging research has demonstrated that organizational efforts at becoming secondary traumatic stress (STS)-informed can improve the overall well-being of the workforce, especially when implementation activity by a champion team is high. Questions remain, however, regarding the mechanisms that enable these improvements.

Method

This study uses configurational analysis to determine necessary and sufficient conditions to produce reductions in STS symptoms in workers as well as organizational improvements toward being more STS-informed in a cohort survey of 6,033 professionals working with individuals exposed to trauma representing 52 organizations. The Secondary Traumatic Stress Informed Organizational Assessment (STSI-OA) was used to measure professional's perceptions of how well the unit addressed secondary trauma in the workplace, and the Secondary Traumatic Stress Scale (STSS) assessed traumatic stress symptoms in respondents. Champions' activity was scored using the categories suggested by Shea.

Results

For the STSS outcome, either a STSI-OA positive increase of 10 or more points or high levels of champion problem-solving were independently sufficient for an improvement in the outcome. The STSI-OA model had two pathways: high levels of peer engagement via the scaling up of innovations using PDSAs or the combination of facilitation of peer knowledge and skills together with working in a child welfare organization. Either pathway was sufficient by itself to yield the STSI-OA outcome.

Conclusions

Identifying and cultivating the champions' use of problem-solving and peer engagement strategies can transform the threat posed by indirect trauma exposure into an opportunity for shared experience and healing.

Plain Language Summary

Organizational champions are individuals or teams that strive to promote change within their workplace. These champions are integral to spreading innovative ideas and strategies and creating organization-wide changes ( Powell et al., 2015). However, little is known about the processes or specific strategies that make champions successful. One area in which champions are needed is in improving organizations' response to and understanding of secondary traumatic stress (STS), among those in helping professions that are indirectly exposed to trauma through the traumatic stories of those they work with. In fact, research has shown that organizational efforts to address STS improve the well-being of individual professionals within that organization ( Sprang et al., 2021). The present study sought to better understand what champion-related processes or conditions led to organizational change in addressing the effects of indirect exposure and improving symptoms related to STS. Results showed that organizational change in addressing STS and champions' problem-solving strategies resulted in reductions in individual professionals' STS symptoms. Furthermore, champions' use of peer engagement or sharing of knowledge among peers in child welfare settings led to improvements at an organizational level. These results show that organization-level change can have a direct impact on individual well-being and there are specific champion activities that can promote this change. Specifically, results demonstrate a need to identify and support champions' use of problem-solving and peer engagement strategies to turn the individual and organizational threat posed by indirect trauma into an opportunity for shared healing.