Lessons Learned from Health Disparities in Coronavirus Disease-2019 in the United States.

In the United States, the coronavirus disease-2019 (COVID-19) pandemic has disproportionally affected Black, Latinx, and Indigenous populations, immigrants, and economically disadvantaged individuals. Such historically marginalized groups are more often employed in low-wage jobs without health insurance and have higher rates of infection, hospitalization, and death from COVID-19 than non-Latinx White individuals. Mistrust in the health care system, language barriers, and limited health literacy have hindered vaccination rates in minorities, further exacerbating health disparities rooted in structural, institutional, and socioeconomic inequities. In this article, we discuss the lessons learned over the last 2 years and how to mitigate health disparities moving forward.

Challenges in providing special care dentistry during COVID-19 pandemic: a survey of public dental care services in Italy.

BACKGROUND: The aim of this paper was to assess COVID-19 pandemic impact over the public health care services (HCS) involved in special care dentistry (SCD). METHODS: Customized questionnaire was sent to 45 HCS involved in SCD. Healthcare personnel (HP) on duty, safety of HCS, time of suspension and reduction of routine dental practice in special needs patients (SNP), kind of SNP mostly penalized during pre-COVID period/T1, lockdown (phase 1/T2) and post pandemic reopening (phase 2/T3) were analyzed by statistical means (P<0.05). RESULTS: 21 questionnaires were returned. A significant decrease of median number of HP during T2 was observed. Prevalence of COVID-19 infection among HP was not significantly different between T2 vs. T3. Medical surveillance of HP during T2 was significantly lower than during T3. Patients with lack of cooperation were the most disadvantaged during both phases dental procedures were significantly lower between T1 and T2 and between T1 and T3 as well. Patients with lack of cooperation and/or living in residential care homes were the most disadvantaged in relation to access to dental care during both phases. CONCLUSIONS: COVID-19 pandemic determined significant restrictions in daily access to routine oral care resulting in reduction of preventive evaluations and decline of oral health in a population which is already at a higher risk of oral pathologies. Our data reveal that reduction of dental procedures, healthcare professionals and days of suspension of clinical activity were still considerable also in T3 with respect to T1 and in some cases not significantly different from T2.

A scoping review on the impact of austerity on healthcare access in the European Union: rethinking austerity for the most vulnerable.

BACKGROUND: There is consensus that the 2008 financial and economic crisis and related austerity measures adversely impacted access to healthcare. In light of the growing debt caused by the COVID-19 crisis, it is uncertain whether a period of austerity will return. OBJECTIVE: This study aims to provide a structured overview of the impact of austerity policies in the EU-28 zone, applied in response to the Great Recession, on access to health care for the adult population, using the five access dimensions by Levesque et al. (2013). METHODS: This study followed the PRISMA extension for Scoping Reviews guideline. Medline (PubMed) and Web of Science were searched between February 2021 and June 2021. Primary studies in the English language published after the 1st of January 2008 reporting on the possible change in access to the healthcare system for the adult population induced by austerity in an EU28 country were included. RESULTS: The final search strategy resulted in 525 articles, of which 75 studies were reviewed for full-text analysis, and a total of 21 studies were included. Results revealed that austerity policy has been primarily associated with a reduction in access to healthcare, described through four main categories: i) Increase in rates of reported unmet needs (86%); ii) Affordability (38%); iii) Appropriateness (38%); iv) and Availability and Accommodation (19%). Vulnerable populations were more affected by austerity measures than the general population when specific safeguards were not in place. The main affected adult vulnerable population groups were: patients with chronic diseases, elderly people, (undocumented) migrants, unemployed, economically inactive people and individuals with lower levels of education or socioeconomic status. CONCLUSION: Austerity measures have led to a deterioration in access to healthcare in the vast majority of the countries studied in the EU-28 zone. Findings should prompt policymakers to rethink the fiscal agenda across all policies in times of economic crisis and focus on the needs of the most vulnerable populations from the health perspective.

Huddling with families after disaster: Human resilience and social disparity.

Disasters, from hurricanes to pandemics, tremendously impact human lives and behaviors. Physical closeness to family post-disaster plays a critical role in mental healing and societal sustainability. Nonetheless, little is known about whether and how family colocation alters after a disaster, a topic of immense importance to a post-disaster society. We analyze 1 billion records of population-scale, granular, individual-level mobile location data to quantify family colocation, and examine the magnitude, dynamics, and socioeconomic heterogeneity of the shift in family colocation from the pre- to post-disaster period. Leveraging Hurricane Florence as a natural experiment, and Geographic Information System (GIS), machine learning, and statistical methods to investigate the shift across the landfall (treated) city of Wilmington, three partially treated cites on the hurricane's path, and two control cities off the path, we uncover dramatic (18.9%), widespread (even among the partially treated cities), and enduring (over at least 3 months) escalations in family colocation. These findings reveal the powerful psychological and behavioral impacts of the disaster upon the broader populations, and simultaneously remarkable human resilience via behavioral adaptations during disastrous times. Importantly, the disaster created a gap across socioeconomic groups non-existent beforehand, with the disadvantaged displaying weaker lifts in family colocation. This sheds important lights on policy making and policy communication to promote sustainable family colocation, healthy coping strategies against traumatic experiences, social parity, and societal recovery.

Medical avoidance among marginalized groups: the impact of the COVID-19 pandemic.

Medical avoidance is common among U.S. adults, and may be emphasized among members of marginalized communities due to discrimination concerns. In the current study, we investigated whether this disparity in avoidance was maintained or exacerbated during the onset of the COVID-19 pandemic. We assessed the likelihood of avoiding medical care due to general-, discrimination-, and COVID-19-related concerns in an online sample (N = 471). As hypothesized, marginalized groups (i.e., non-White race, Latinx/e ethnicity, non-heterosexual sexual orientation, high BMI) endorsed more general- and discrimination-related medical avoidance than majoritized groups. However, marginalized groups were equally likely to seek COVID-19 treatment as majoritized groups. Implications for reducing medical avoidance among marginalized groups are discussed.

Assessment of a Crisis Standards of Care Scoring System for Resource Prioritization and Estimated Excess Mortality by Race, Ethnicity, and Socially Vulnerable Area During a Regional Surge in COVID-19.

Importance: Crisis standards of care (CSOC) scores designed to allocate scarce resources during the COVID-19 pandemic could exacerbate racial disparities in health care. Objective: To analyze the association of a CSOC scoring system with resource prioritization and estimated excess mortality by race, ethnicity, and residence in a socially vulnerable area. Design, Setting, and Participants: This retrospective cohort analysis included adult patients in the intensive care unit during a regional COVID-19 surge from April 13 to May 22, 2020, at 6 hospitals in a health care network in greater Boston, Massachusetts. Participants were scored by acute severity of illness using the Sequential Organ Failure Assessment score and chronic severity of illness using comorbidity and life expectancy scores, and only participants with complete scores were included. The score was ordinal, with cutoff points suggested by the Massachusetts guidelines. Exposures: Race, ethnicity, Social Vulnerability Index. Main Outcomes and Measures: The primary outcome was proportion of patients in the lowest priority score category stratified by self-reported race. Secondary outcomes were discrimination and calibration of the score overall and by race, ethnicity, and neighborhood Social Vulnerability Index. Projected excess deaths were modeled by race, using the priority scoring system and a random lottery. Results: Of 608 patients in the intensive care unit during the study period, 498 had complete data and were included in the analysis; this population had a median (IQR) age of 67 (56-75) years, 191 (38.4%) female participants, 79 (15.9%) Black participants, and 225 patients (45.7%) with COVID-19. The area under the receiver operating characteristic curve for the priority score was 0.79 and was similar across racial groups. Black patients were more likely than others to be in the lowest priority group (12 [15.2%] vs 34 [8.1%]; P = .046). In an exploratory simulation model using the score for ventilator allocation, with only those in the highest priority group receiving ventilators, there were 43.9% excess deaths among Black patients (18 of 41 patients) and 28.6% (58 of 203 patients among all others (P = .05); when the highest and intermediate priority groups received ventilators, there were 4.9% (2 of 41 patients) excess deaths among Black patients and 3.0% (6 of 203) among all others (P = .53). A random lottery resulted in more excess deaths than the score. Conclusions and Relevance: In this study, a CSOC priority score resulted in lower prioritization of Black patients to receive scarce resources. A model using a random lottery resulted in more estimated excess deaths overall without improving equity by race. CSOC policies must be evaluated for their potential association with racial disparities in health care.

Telehealth use in cystic fibrosis during COVID-19: Association with race, ethnicity, and socioeconomic factors.

BACKGROUND: Due to the COVID-19 pandemic, there was an uptake of telehealth in cystic fibrosis care. Previous studies show disparities in telehealth use based on socioeconomic status (SES). We aimed to: (1) understand telehealth use and perceptions and (2) identify the facilitators and barriers to telehealth use among people with CF and their families (PwCF) from diverse racial/ethnic and socioeconomic backgrounds. METHODS: We conducted an analysis of the 2020 Cystic Fibrosis State of Care surveys completed by PwCF (PFSoC), CF Care Programs (SoC1) and the CF Foundation Patient Registry (CFFPR). RESULTS: A total of 424 PwCF and 286 programs responded to the PFSoC and SoC1. Among PwCF, 90% self-identified as White, 6% as Hispanic/Latino, and 2% as Black. Racial/ethnic minorities were less likely to have had a telehealth visit (p=.015). This difference was pronounced among the Hispanic/Latino population (p<.01). Telehealth use did not differ by health insurance and was similarly offered independent of financial status. Compared to PwCF who denied financial constraints, those who reported financial difficulties found telehealth more difficult to use (p=.018) and were less likely to think that their concerns (p=.010) or issues that mattered most to them (p=.020) were addressed during telehealth. Programs perceived lack of technology, language barriers, and home conditions as barriers to telehealth in vulnerable populations. CONCLUSION: PFSoC and SoC1 identified differences in telehealth use and care perceptions by ethnicity, race, and socioeconomic characteristics. Further studies are needed to understand how telehealth can change access to CF care in diverse subpopulations.

Time-varying associations between COVID-19 case incidence and community-level sociodemographic, occupational, environmental, and mobility risk factors in Massachusetts.

BACKGROUND: Associations between community-level risk factors and COVID-19 incidence have been used to identify vulnerable subpopulations and target interventions, but the variability of these associations over time remains largely unknown. We evaluated variability in the associations between community-level predictors and COVID-19 case incidence in 351 cities and towns in Massachusetts from March to October 2020. METHODS: Using publicly available sociodemographic, occupational, environmental, and mobility datasets, we developed mixed-effect, adjusted Poisson regression models to depict associations between these variables and town-level COVID-19 case incidence data across five distinct time periods from March to October 2020. We examined town-level demographic variables, including population proportions by race, ethnicity, and age, as well as factors related to occupation, housing density, economic vulnerability, air pollution (PM2.5), and institutional facilities. We calculated incidence rate ratios (IRR) associated with these predictors and compared these values across the multiple time periods to assess variability in the observed associations over time. RESULTS: Associations between key predictor variables and town-level incidence varied across the five time periods. We observed reductions over time in the association with percentage of Black residents (IRR = 1.12 [95%CI: 1.12-1.13]) in early spring, IRR = 1.01 [95%CI: 1.00-1.01] in early fall) and COVID-19 incidence. The association with number of long-term care facility beds per capita also decreased over time (IRR = 1.28 [95%CI: 1.26-1.31] in spring, IRR = 1.07 [95%CI: 1.05-1.09] in fall). Controlling for other factors, towns with higher percentages of essential workers experienced elevated incidences of COVID-19 throughout the pandemic (e.g., IRR = 1.30 [95%CI: 1.27-1.33] in spring, IRR = 1.20 [95%CI: 1.17-1.22] in fall). Towns with higher proportions of Latinx residents also had sustained elevated incidence over time (IRR = 1.19 [95%CI: 1.18-1.21] in spring, IRR = 1.14 [95%CI: 1.13-1.15] in fall). CONCLUSIONS: Town-level COVID-19 risk factors varied with time in this study. In Massachusetts, racial (but not ethnic) disparities in COVID-19 incidence may have decreased across the first 8 months of the pandemic, perhaps indicating greater success in risk mitigation in selected communities. Our approach can be used to evaluate effectiveness of public health interventions and target specific mitigation efforts on the community level.

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.

COVID-19 in socially vulnerable quilombola populations in Salvaterra, Pará, Eastern Amazon, Brazil.

INTRODUCTION: COVID-19 is a severe respiratory syndrome caused by the SARS-CoV-2 virus. In Brazil the highest infection rates are associated with socially vulnerable populations. This study therefore sought to analyze the spatial distribution of the disease and its relation with geographic, socioeconomic and public health policy characteristics associated with quilombola communities in Salvaterra municipality, state of Pará, for the period of March to September, 2020. METHODOLOGY: This cross-sectional and ecological study used data from the Disease Notification System and the National Registry of Health Establishments of the Ministry of Health, the Income Transfer Registry of the Ministry of Citizenship and the 2010 census of the Brazilian Institute of Geography and Statistics. Statistical and spatial analysis of the data was done through percentages of cases and Flow and Kernel map techniques. RESULTS: Seventy-five notified cases of COVID-19 distributed among 7 quilombola communities in the municipality were analyzed. The epidemiological profile followed a national trend, with a higher percentage of cases among persons who were female, adults with low schooling levels, working as family farmers and with an outcome ending in recovery. The spatial distribution of the disease was not homogenous and showed clusters of cases and high incidence rates, especially in communities close to the municipal seat or to highways. CONCLUSIONS: The use of data analysis techniques was satisfactory for providing an understanding of the socioeconomic production of the disease in the areas studied. Accordingly, the need for intensifying epidemiological survey actions in the quilombola communities of the municipality is emphasized.