Heterogeneity in Spatial Inequities in COVID-19 Vaccination Across 16 Large US Cities

Spatiotemporal variability in socioeconomic inequalities in COVID-19 vaccination in Catalonia, Spain

OBJECTIVES

Socioeconomic inequalities have played a significant role in the unequal coverage of the COVID-19 vaccine. The objectives of this study were to (1) assess the socioeconomic inequalities in COVID-19 vaccination coverage in Catalonia, Spain; (2) analyse the spatial variation over time of these inequalities; and (3) assess variations in time and space in the effect of vaccination on inequalities in COVID-19 outcomes.

STUDY DESIGN

A mixed longitudinal ecological study design was used.

METHODS

Catalonia is divided in to 373 Basic Health Areas. Weekly data from these Basic Health Areas were obtained from the last week of December 2020 until the first week of March of 2022. A joint spatio-temporal model was used with the dependent variables of vaccination and COVID-19 outcomes, which were estimated using a Bayesian approach. The study controlled for observed confounders, unobserved heterogeneity, and spatial and temporal dependencies. The study allowed the effect of the explanatory variables on the dependent variables to vary in space and in time.

RESULTS

Areas with lower socioeconomic level were those with the lowest vaccination rates and the highest risk of COVID-19 outcomes. In general, individuals in areas that were located in the upper two quartiles of average net income per person and in the lower two quartiles of unemployment rate (i.e., the least economically disadvantaged) had a higher propensity to be vaccinated than those in the most economically disadvantaged areas. In the same sense, the greater the percentage of the population aged ≥65 years, the higher the propensity to be vaccinated, while areas located in the two upper quartiles of population density and areas with a high percentage of poor housing had a lower propensity to be vaccinated. Higher vaccination rates reduced the risk of COVID-19 outcomes, while COVID-19 outcomes did not influence the propensity to be vaccinated. The effects of the explanatory variables were not the same in all areas or between the different waves of the pandemic, and clusters of excess risk of low vaccination in the most disadvantaged areas were detected.

CONCLUSIONS

COVID-19 vaccination inequalities in the most disadvantaged areas could be a result of structural barriers, such as the lack of access to information about the vaccination process, and/or logistical challenges, such as the lack of transportation, limited Internet access or difficulty in scheduling appointments. Public health strategies should be developed to mitigate these barriers and reduce vaccination inequalities.

La equidad en la campaña de vacunación COVID de la Provincia de Buenos Aires (Argentina): un análisis del Municipio de Quilmes

INTRODUCCIÓN

la pandemia de la COVID-19 ha acentuado las desigualdades sociales, económicas y relacionadas con la salud, afectando desproporcionadamente a las personas en situación de vulnerabilidad y perpetuando la inequidad en salud. En Argentina se implementó una campaña nacional gratuita de vacunación contra la COVID-19 con una perspectiva de equidad.

OBJETIVO

identificar desigualdades territoriales en el acceso a la vacunación contra la COVID-19 en Quilmes.

MÉTODOS

se analizó la información referida a la vacunación contra la COVID-19 de personas residentes en el Municipio. Se efectuó la georreferenciación de cada vacunatorio y de cada persona a partir del domicilio declarado en el momento de la vacunación. Para caracterizar el grado de vulnerabilidad de las personas vacunadas, a cada una se le asignó el índice de carencias múltiples (ICM) correspondiente al radio censal de residencia.

RESULTADOS

al menos el 82 % de la población completó el esquema primario de vacunación (dosis 1 y dosis 2), porcentaje que alcanzó el 97 % en los mayores de 65 años. Analizando la media de dosis aplicadas se observa algo similar con un gradiente hacia los quintiles más altos pero con una mínima diferencia entre sí, situación que también se corrobora en todos los grupos etarios.

DISCUSIÓN

no se observaron brechas significativas entre los diferentes niveles socioeconómicos. Si bien se observó un mínimo gradiente en el promedio de dosis recibidas, el tiempo de acceso a las diferentes vacunas y el porcentaje de esquemas primarios completos recibidos, las mismas tienen escasa relevancia clínica y sanitaria.

Dynamic predictors of COVID-19 vaccination uptake and their interconnections over two years in Hong Kong

The global rollout of COVID-19 vaccines faces a significant barrier in the form of vaccine hesitancy. This study adopts a dynamic and network perspective to explore the determinants of COVID-19 vaccine uptake in Hong Kong, focusing on multi-level determinants and their interconnections. Following the framework proposed by the Strategic Advisory Group of Experts (SAGE), the study used repeated cross-sectional surveys to map these determinants at multiple levels and investigates their interconnections simultaneously in a sample of 15,179 over two years. The results highlight the dynamic nature of COVID-19 vaccine hesitancy in an evolving pandemic. The findings suggest that vaccine confidence attitudes play crucial roles in vaccination uptake, with their importance shifting over time. The initial emphasis on vaccine safety gradually transitioned to heightened consideration of vaccine effectiveness at a later stage. The study also highlights the impact of chronic condition, age, COVID-19 case numbers, and non-pharmaceutical preventive behaviours on vaccine uptake. Higher educational attainment and being married were associated with primary and booster vaccine uptake and it may be possible to leverage these groups as early innovation adopters. Trust in government acts as a crucial bridging factor linking various variables in the networks with vaccine confidence attitudes, which subsequently closely linked to vaccine uptake. This study provides insights for designing future effective vaccination programmes for changing circumstances.

An Electronic Health Record Alert for Inpatient Coronavirus Disease 2019 Vaccinations Increases Vaccination Ordering and Uncovers Workflow Inefficiencies

BACKGROUND

 Despite mortality benefits, only 19.9% of U.S. adults are fully vaccinated against the coronavirus disease 2019 (COVID-19). The inpatient setting is an opportune environment to update vaccinations, and inpatient electronic health record (EHR) alerts have been shown to increase vaccination rates.

OBJECTIVE

 Our objective was to evaluate whether an EHR alert could increase COVID-19 vaccinations in eligible hospitalized adults by prompting providers to order the vaccine.

METHODS

 This was a quasiexperimental pre-post-interventional design study at an academic and community hospital in the western United States between 1 January, 2021 and 31 October, 2021. Inclusion criteria were unvaccinated hospitalized adults. A soft-stop, interruptive EHR alert prompted providers to order COVID-19 vaccines for those with an expected discharge date within 48 hours and interest in vaccination. The outcome measured was the proportion of all eligible patients for whom vaccines were ordered and administered before and after alert implementation.

RESULTS

 Vaccine ordering rates increased from 4.0 to 13.0% at the academic hospital (odds ratio [OR]: 4.01, 95% confidence interval [CI]: 3.39-4.74, p < 0.001) and from 7.4 to 11.6% at the community hospital (OR: 1.62, 95% CI: 1.23-2.13, p < 0.001) after alert implementation. Administration increased postalert from 3.6 to 12.7% at the academic hospital (OR: 3.21, 95% CI: 2.70-3.82, p < 0.001) but was unchanged at the community hospital, 6.7 to 6.7% (OR: 0.99, 95% CI: 0.73-1.37, p = 0.994). Further analysis revealed infrequent vaccine availability at the community hospital.

CONCLUSION

 Vaccine ordering rates improved at both sites after alert implementation. Vaccine administration rates, however, only improved at the academic hospital, likely due in part to vaccine dispensation inefficiency at the community hospital. This study demonstrates the potential impact of complex workflow patterns on new EHR alert success and provides a rationale for subsequent qualitative workflow analysis with alert implementation.

Can psychological distress account for the associations between COVID-19 vaccination acceptance and socio-economic vulnerability?

Socially disadvantaged individuals and communities consistently showed lower COVID-19 vaccination acceptance. We aimed to examine the psychological mechanisms that could explain such vaccination disparities. This study used data from serial population-based surveys conducted since the COVID-19 vaccination programme being launched in Hong Kong (N = 28,734). We first assessed the correlations of community-level and individual-level social vulnerability with COVID-19 vaccination acceptance. Structural equation modelling (SEM) was then conducted to test whether psychological distress measured by PHQ-4 can account for the associations between participants' socio-economic vulnerability and COVID-19 vaccination acceptance. The third part analysis examined whether perceived negativity of vaccine-related news and affect towards COVID-19 vaccines accounted for the association between psychological distress and COVID-19 vaccination. Communities with higher social vulnerability scores and participants who had more vulnerable socio-economic status showed lower COVID-19 vaccination acceptance. Individuals with more vulnerable socio-economic status reported higher psychological distress, which lowered COVID-19 vaccination acceptance. Furthermore, higher psychological distress was associated with lower vaccination acceptance through its psychological mechanisms of processing vaccine-related information. We proposed a renewed focus on tackling psychological distress rather than merely increasing vaccine accessibility in more socio-economic-disadvantaged groups for promoting COVID-19 vaccination acceptance.

Social inequalities and COVID-19 mortality between neighborhoods of Bariloche city, Argentina

BACKGROUND

The COVID-19 pandemic has shown how intraurban inequalities are likely to reinforce health and social inequalities. Studies at small area level help to visualize social inequialities hidden in large areas as cities or regions.

AIM

To describe the spatial patterning of COVID-19 death rates in neighborhoods of the medium-sized city of Bariloche, Argentina, and to explore its relationship with the socioeconomic characteristics of neighborhoods.

METHODS

We conducted an ecological study in Bariloche, Argentina. The outcome was counts of COVID-19 deaths between June 2020 and May 2022 obtained from the surveillance system and georeferenced to neighborhoods. We estimated crude- and age-adjusted death rates by neighborhood using a Bayesian approach through a Poisson regression that accounts for spatial-autocorrelation via Conditional Autoregressive (CAR) structure. We also analyzed associations of age-adjusted death rates with area-level socioeconomic indicators.

RESULTS

Median COVID-19 death rate across neighborhoods was 17.9 (10th/90th percentile of 6.3/35.2) per 10,000 inhabitants. We found lower age-adjusted rates in the city core and western part of the city. The age-adjusted death rate in the most deprived areas was almost double than in the least deprived areas, with an education-related relative index of inequality (RII) of 2.14 (95% CI 1.55 to 2.96).

CONCLUSION

We found spatial heterogeneity and intraurban variability in age-adjusted COVID-19 death rates, with a clear social gradient, and a higher burden in already deprived areas. This highlights the importance of studying inequalities in health outcomes across small areas to inform placed-based interventions.

Salivary SARS-CoV-2 RNA for diagnosis of COVID-19 patients: a systematic revisew and meta-analysis of diagnostic accuracy

Accurate, self-collected, and non-invasive diagnostics are critical to perform mass-screening diagnostic tests for COVID-19. This systematic review with meta-analysis evaluated the accuracy, sensitivity, and specificity of salivary diagnostics for COVID-19 based on SARS-CoV-2 RNA compared with the current reference tests using a nasopharyngeal swab (NPS) and/or oropharyngeal swab (OPS). An electronic search was performed in seven databases to find COVID-19 diagnostic studies simultaneously using saliva and NPS/OPS tests to detect SARS-CoV-2 by RT-PCR. The search resulted in 10,902 records, of which 44 studies were considered eligible. The total sample consisted of 14,043 participants from 21 countries. The accuracy, specificity, and sensitivity for saliva compared with the NPS/OPS was 94.3% (95%CI= 92.1;95.9), 96.4% (95%CI= 96.1;96.7), and 89.2% (95%CI= 85.5;92.0), respectively. Besides, the sensitivity of NPS/OPS was 90.3% (95%CI= 86.4;93.2) and saliva was 86.4% (95%CI= 82.1;89.8) compared to the combination of saliva and NPS/OPS as the gold standard. These findings suggest a similarity in SARS-CoV-2 RNA detection between NPS/OPS swabs and saliva, and the association of both testing approaches as a reference standard can increase by 3.6% the SARS-CoV-2 detection compared with NPS/OPS alone. This study supports saliva as an attractive alternative for diagnostic platforms to provide a non-invasive detection of SARS-CoV-2.

Social and ideological determinants of COVID-19 vaccination status in Spain

OBJECTIVES

This study analysed the association between social and ideological determinants with COVID-19 vaccine accessibility and hesitancy in the Spanish adult population.

STUDY DESIGN

This was a repeated cross-sectional study.

METHODS

The data analysed are based on monthly surveys conducted by the Centre for Sociological Research between May 2021 and February 2022. Individuals were classified according to their COVID-19 vaccination status into (1) vaccinated (reference group); (2) willing to vaccinate but not vaccinated, proxy of lack of vaccine accessibility; and (3) hesitant, proxy of vaccine hesitancy. Independent variables included social (educational attainment, gender) and ideological determinants (voting in the last elections, importance attached to the health vs the economic impact of the pandemic, and political self-placement). We estimated odds ratio (OR) and 95% confidence interval (CI) conducting one age-adjusted multinomial logistic regression model for each determinant and then stratified them by gender.

RESULTS

Both social and ideological determinants had a weak association with the lack of vaccine accessibility. Individuals with medium educational attainment had higher odds of vaccine hesitancy (OR = 1.44, CI 1.08-1.93) compared with those with high educational attainment. People self-identified as conservative (OR = 2.90; CI 2.02-4.15) and those who prioritised the economic impact (OR = 3.80; CI 2.62-5.49) and voted for parties opposed to the Government (OR = 2.00; CI 1.54-2.60) showed higher vaccine hesitancy. The stratified analysis showed a similar pattern for both men and women.

CONCLUSIONS

Considering the determinants of vaccine uptake and hesitancy could help to design strategies that increase immunisation at the population level and minimise health inequities.

One Year of COVID-19 Vaccine Misinformation on Twitter: Longitudinal Study

BACKGROUND

Vaccinations play a critical role in mitigating the impact of COVID-19 and other diseases. Past research has linked misinformation to increased hesitancy and lower vaccination rates. Gaps remain in our knowledge about the main drivers of vaccine misinformation on social media and effective ways to intervene.

OBJECTIVE

Our longitudinal study had two primary objectives: (1) to investigate the patterns of prevalence and contagion of COVID-19 vaccine misinformation on Twitter in 2021, and (2) to identify the main spreaders of vaccine misinformation. Given our initial results, we further considered the likely drivers of misinformation and its spread, providing insights for potential interventions.

METHODS

We collected almost 300 million English-language tweets related to COVID-19 vaccines using a list of over 80 relevant keywords over a period of 12 months. We then extracted and labeled news articles at the source level based on third-party lists of low-credibility and mainstream news sources, and measured the prevalence of different kinds of information. We also considered suspicious YouTube videos shared on Twitter. We focused our analysis of vaccine misinformation spreaders on verified and automated Twitter accounts.

RESULTS

Our findings showed a relatively low prevalence of low-credibility information compared to the entirety of mainstream news. However, the most popular low-credibility sources had reshare volumes comparable to those of many mainstream sources, and had larger volumes than those of authoritative sources such as the US Centers for Disease Control and Prevention and the World Health Organization. Throughout the year, we observed an increasing trend in the prevalence of low-credibility news about vaccines. We also observed a considerable amount of suspicious YouTube videos shared on Twitter. Tweets by a small group of approximately 800 "superspreaders" verified by Twitter accounted for approximately 35% of all reshares of misinformation on an average day, with the top superspreader (@RobertKennedyJr) responsible for over 13% of retweets. Finally, low-credibility news and suspicious YouTube videos were more likely to be shared by automated accounts.

CONCLUSIONS

The wide spread of misinformation around COVID-19 vaccines on Twitter during 2021 shows that there was an audience for this type of content. Our findings are also consistent with the hypothesis that superspreaders are driven by financial incentives that allow them to profit from health misinformation. Despite high-profile cases of deplatformed misinformation superspreaders, our results show that in 2021, a few individuals still played an outsized role in the spread of low-credibility vaccine content. As a result, social media moderation efforts would be better served by focusing on reducing the online visibility of repeat spreaders of harmful content, especially during public health crises.

Higher COVID-19 Vaccination And Narrower Disparities In US Cities With Paid Sick Leave Compared To Those Without

Paid sick leave provides workers with paid time off to receive COVID-19 vaccines and to recover from potential vaccine adverse effects. We hypothesized that US cities with paid sick leave would have higher COVID-19 vaccination coverage and narrower coverage disparities than those without such policies. Using county-level vaccination data and paid sick leave data from thirty-seven large US cities in 2021, we estimated the association between city-level paid sick leave policies and vaccination coverage in the working-age population and repeated the analysis using coverage in the population ages sixty-five and older as a negative control. We also examined associations by neighborhood social vulnerability. Cities with a paid sick leave policy had 17 percent higher vaccination coverage than cities without such a policy. We found stronger associations between paid sick leave and vaccination in the most socially vulnerable neighborhoods compared with the least socially vulnerable ones, and no association in the population ages sixty-five and older. Paid sick leave policies are associated with higher COVID-19 vaccination coverage and narrower coverage disparities. Increasing access to these policies may help increase vaccination and reduce inequities in coverage.

A Scoping Review of Three Dimensions for Long-Term COVID-19 Vaccination Models: Hybrid Immunity, Individual Drivers of Vaccinal Choice, and Human Errors

The virus that causes COVID-19 changes over time, occasionally leading to Variants of Interest (VOIs) and Variants of Concern (VOCs) that can behave differently with respect to detection kits, treatments, or vaccines. For instance, two vaccination doses were 61% effective against the BA.1 predominant variant, but only 24% effective when BA.2 became predominant. While doses still confer protection against severe disease outcomes, the BA.5 variant demonstrates the possibility that individuals who have received a few doses built for previous variants can still be infected with newer variants. As previous vaccines become less effective, new ones will be released to target specific variants and the whole process of vaccinating the population will restart. While previous models have detailed logistical aspects and disease progression, there are three additional key elements to model COVID-19 vaccination coverage in the long term. First, the willingness of the population to participate in regular vaccination campaigns is essential for long-term effective COVID-19 vaccination coverage. Previous research has shown that several categories of variables drive vaccination status: sociodemographic, health-related, psychological, and information-related constructs. However, the inclusion of these categories in future models raises questions about the identification of specific factors (e.g., which sociodemographic aspects?) and their operationalization (e.g., how to initialize agents with a plausible combination of factors?). While previous models separately accounted for natural- and vaccine-induced immunity, the reality is that a significant fraction of individuals will be both vaccinated and infected over the coming years. Modeling the decay in immunity with respect to new VOCs will thus need to account for hybrid immunity. Finally, models rarely assume that individuals make mistakes, even though this over-reliance on perfectly rational individuals can miss essential dynamics. Using the U.S. as a guiding example, our scoping review summarizes these aspects (vaccinal choice, immunity, and errors) through ten recommendations to support the modeling community in developing long-term COVID-19 vaccination models.

Inequities in spatial accessibility to COVID-19 testing in 30 large US cities

Testing for SARS-CoV-2 infection has been a key strategy to mitigate and control the COVID-19 pandemic. Wide spatial and racial/ethnic disparities in COVID-19 outcomes have emerged in US cities. Previous research has highlighted the role of unequal access to testing as a potential driver of these disparities. We described inequities in spatial accessibility to COVID-19 testing locations in 30 large US cities. We used location data from Castlight Health Inc corresponding to October 2021. We created an accessibility metric at the level of the census block group (CBG) based on the number of sites per population in a 15-minute walkshed around the centroid of each CBG. We also calculated spatial accessibility using only testing sites without restrictions, i.e., no requirement for an appointment or a physician order prior to testing. We measured the association between the social vulnerability index (SVI) and spatial accessibility using a multilevel negative binomial model with random city intercepts and random SVI slopes. Among the 27,195 CBG analyzed, 53% had at least one testing site within a 15-minute walkshed, and 36% had at least one site without restrictions. On average, a 1-decile increase in the SVI was associated with a 3% (95% Confidence Interval: 2% - 4%) lower accessibility. Spatial inequities were similar across various components of the SVI and for sites with no restrictions. Despite this general pattern, several cities had inverted inequity, i.e., better accessibility in more vulnerable areas, which indicates that some cities may be on the right track when it comes to promoting equity in COVID-19 testing. Testing is a key component of the strategy to mitigate transmission of SARS-CoV-2 and efforts should be made to improve accessibility to testing, particularly as new and more contagious variants become dominant.

Changes in Racial/Ethnic Disparities in Opioid-Related Outcomes in Urban Areas during the COVID-19 Pandemic: A Rapid Review of the Literature

Opioid use disorders (OUDs) are increasingly common among minoritized populations, who have historically experienced limited access to healthcare, a situation that may have worsened during the COVID-19 pandemic. Using a structured keyword search in Pubmed, we reviewed the literature to synthesize the evidence on changes in racial/ethnic disparities in OUD-related outcomes in urban areas during the COVID-19 pandemic in the US. Nine articles were included in the final analysis. Six found increases in OUD-related outcomes during the pandemic, with four showing a widening of disparities. Results also point to the worsening of opioid outcomes among Black and Latinx individuals related to shelter-in-place or stay-at-home orders. Studies examining the use of telehealth and access to OUD treatment showed that minoritized groups have benefited from telehealth programs. The limited number of studies in a small number of jurisdictions indicate a gap in research examining the intersection between COVID-19 and OUD-related outcomes with a focus on disparities. More research is needed to understand the impact of the COVID-19 pandemic and related policies on OUD outcomes among racial/ethnic minoritized groups, including examining the impact of service disruptions on vulnerable groups with OUD.

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

BACKGROUND

COVID-19 infection has disproportionately affected socially disadvantaged neighborhoods. Despite this disproportionate burden of infection, these neighborhoods have also lagged in COVID-19 vaccinations. To date, we have little understanding of the ways that various types of social conditions intersect to explain the complex causes of lower COVID-19 vaccination rates in neighborhoods.

METHODS

We used configurational comparative methods (CCMs) to study COVID-19 vaccination rates in Philadelphia by neighborhood (proxied by zip code tabulation areas). Specifically, we identified neighborhoods where COVID-19 vaccination rates (per 10,000) were persistently low from March 2021 - May 2021. We then assessed how different combinations of social conditions (pathways) uniquely distinguished neighborhoods with persistently low vaccination rates from the other neighborhoods in the city. Social conditions included measures of economic inequities, racial segregation, education, overcrowding, service employment, public transit use, health insurance and limited English proficiency.

RESULTS

Two factors consistently distinguished neighborhoods with persistently low COVID-19 vaccination rates from the others: college education and concentrated racial privilege. Two factor values together - low college education AND low/medium concentrated racial privilege - identified persistently low COVID-19 vaccination rates in neighborhoods, with high consistency (0.92) and high coverage (0.86). Different values for education and concentrated racial privilege - medium/high college education OR high concentrated racial privilege - were each sufficient by themselves to explain neighborhoods where COVID-19 vaccination rates were not persistently low, likewise with high consistency (0.93) and high coverage (0.97).

CONCLUSIONS

Pairing CCMs with geospatial mapping can help identify complex relationships between social conditions linked to low COVID-19 vaccination rates. Understanding how neighborhood conditions combine to create inequities in communities could inform the design of interventions tailored to address COVID-19 vaccination disparities.

Racial/ethnic and neighbourhood social vulnerability disparities in COVID-19 testing positivity, hospitalization, and in-hospital mortality in a large hospital system in Pennsylvania: A prospective study of electronic health records

Background

Disparities in COVID-19 mortality by race/ethnicity or neighborhood have been documented using surveillance data. We aimed to describe disparities by race/ethnicity and neighbourhood social vulnerability in COVID-19 positivity, hospitalization, and mortality.

Methods

We obtained data from the electronic health records of all individuals who tested positive for COVID-19 in the University of Pennsylvania Health System (UPHS) or were hospitalized with confirmed COVID-19 infection in five UPHS hospitals from March 1, 2020, to March 31, 2021. The main predictors were race/ethnicity and neighbourhood-level social vulnerability. The main outcomes were COVID-19 test positivity, hospitalization with COVID-19, and 30-day in-hospital mortality following hospitalization with COVID-19.

Findings

A total of 225,129 unique individuals received COVID-19 testing and 18,995 had a positive test result. A total of 5,794 unique patients were hospitalized with COVID-19 and 511 died in-hospital within 30 days. Racial/ethnic minority groups and residents of higher social vulnerability neighbourhoods had higher test positivity and risk of hospitalization. We did not see in-hospital mortality disparities during the first wave but observed 75% and 68% higher odds of death among Hispanic and Asians compared to Whites during subsequent waves.

Interpretation

We observed significant racial/ethnic and neighbourhood disparities in COVID-19 outcomes, especially test positivity and odds of hospitalization, highlighting the importance of equitably improving access to preventive measures to reduce SARS-CoV-2 infection, including reducing exposure to the virus and ensuring equity in vaccination.

Funding

National Institutes of Health.