Equitable allocation of COVID-19 vaccines in the United States

Supporting equitable and responsible highway safety improvement funding allocation strategies - Why AI prediction biases matter

The existing methodologies for allocating highway safety improvement funding closely rely on the utilization of crash prediction models. Specifically, these models produce predictions that estimate future crash hazard levels in different geographical areas, which subsequently support the future funding allocation strategies. In recent years, there is a burgeoning interest in applying artificial intelligence (AI)-based models to perform crash prediction tasks. Despite the remarkable accuracy of these AI-based crash prediction models, they have been observed to yield biased prediction outcomes across areas of different socioeconomic statuses. These biases are primarily attributed to the inherent measurement and representation biases of AI-based prediction models. More precisely, measurement bias arises from the selection of target variables to reflect crash hazard levels, while representation bias results from the issue of imbalanced number of samples representing areas with different socioeconomic statuses within the dataset. Consequently, these biased prediction outcomes have the potential to perpetuate an unfair allocation of funding resources, contributing to worsen social inequality over time. Drawing upon a real-world case study in North Carolina, this study designs an AI-based crash prediction model that utilizes previous sociodemographic and crash-related variables to predict future severe crash rate of each area to reflect the crash hazardous level. By incorporating a fair regression framework, this study endeavors to transform the crash prediction model to become both fair and accurate, aiming to support equitable and responsible safety improvement funding allocation strategies.

Incorporating social determinants of health into transmission modeling of COVID-19 vaccine in the US: a scoping review

During COVID-19 in the US, social determinants of health (SDH) have driven health disparities. However, the use of SDH in COVID-19 vaccine modeling is unclear. This review aimed to summarize the current landscape of incorporating SDH into COVID-19 vaccine transmission modeling in the US. Medline and Embase were searched up to October 2022. We included studies that used transmission modeling to assess the effects of COVID-19 vaccine strategies in the US. Studies' characteristics, factors incorporated into models, and approaches to incorporate these factors were extracted. Ninety-two studies were included. Of these, 11 studies incorporated SDH factors (alone or combined with demographic factors). Various sets of SDH factors were integrated, with occupation being the most common (8 studies), followed by geographical location (5 studies). The results show that few studies incorporate SDHs into their models, highlighting the need for research on SDH impact and approaches to incorporating SDH into modeling.

Funding

This research was funded by the Centers for Disease Control and Prevention (CDC).

Identification of factors associated with opioid-related and hepatitis C virus-related hospitalisations at the ZIP code area level in the USA: an ecological and modelling study

BACKGROUND

Opioid overdose and related diseases remain a growing public health crisis in the USA. Identifying sociostructural and other contextual factors associated with adverse health outcomes is needed to improve prediction models to inform policy and interventions. We aimed to identify high-risk communities for targeted delivery of screening and prevention interventions for opioid use disorder and hepatitis C virus (HCV).

METHODS

In this ecological and modelling study, we fit mixed-effects negative binomial regression models to identify factors associated with, and predict, opioid-related and HCV-related hospitalisations for ZIP code tabulation areas (ZCTAs) in South Carolina, USA. All individuals aged 18 years or older living in South Carolina from Jan 1, 2016, to Dec 31, 2021, were included. Data on opioid-related and HCV-related hospitalisations, as well as data on additional individual-level variables, were collected from medical claims records, which were obtained from the South Carolina Revenue and Fiscal Affairs Office. Demographic and socioeconomic variables were obtained from the United States Census Bureau (American Community Survey, 2021) with additional structural health-care barrier data obtained from South Carolina's Center for Rural and Primary Health Care, and the American Hospital Directory.

FINDINGS

Between Jan 1, 2016, and Dec 31, 2021, 41 691 individuals were hospitalised for opioid misuse and 26 860 were hospitalised for HCV. There were a median of 80 (IQR 24-213) opioid-related hospitalisations and 61 (21-196) HCV-related hospitalisations per ZCTA. A standard deviation increase in ZCTA-level uninsured rate (relative risk 1·24 [95% CI 1·17-1·31]), poverty rate (1·24 [1·17-1·31]), mortality (1·18 [1·12-1·25]), and social vulnerability index (1·17 [1·10-1·24]) was significantly associated with increased combined opioid-related and HCV-related hospitalisation rates. A standard deviation increase in ZCTA-level income (0·79 [0·75-0·84]) and unemployment rate (0·87 [0·82-0·93]) was significantly associated with decreased combined opioid-related and HCV-related hospitalisations. Using 2016-20 hospitalisations as training data, our models predicted ZCTA-level opioid-related hospitalisations in 2021 with a median of 80·4% (IQR 66·8-91·1) accuracy and HCV-related hospitalisations in 2021 with a median of 75·2% (61·2-87·7) accuracy. Several underserved high-risk ZCTAs were identified for delivery of targeted interventions.

INTERPRETATION

Our results suggest that individuals from economically disadvantaged and medically under-resourced communities are more likely to have an opioid-related or HCV-related hospitalisation. In conjunction with hospitalisation forecasts, our results could be used to identify and prioritise high-risk, underserved communities for delivery of field-level interventions.

FUNDING

South Carolina Center for Rural and Primary Healthcare, National Institute on Drug Abuse, and National Library of Medicine.

Spatial Interaction Analysis of Infectious Disease Import and Export between Regions

Human travel plays a crucial role in the spread of infectious disease between regions. Travel of infected individuals from one region to another can transport a virus to places that were previously unaffected or may accelerate the spread of disease in places where the disease is not yet well established. We develop and apply models and metrics to analyze the role of inter-regional travel relative to the spread of disease, drawing from data on COVID-19 in the United States. To better understand how transportation affects disease transmission, we established a multi-regional time-varying compartmental disease model with spatial interaction. The compartmental model was integrated with statistical estimates of travel between regions. From the integrated model, we derived a transmission import index to assess the risk of COVID-19 transmission between states. Based on the index, we determined states with high risk for disease spreading to other states at the scale of months, and we analyzed how the index changed over time during 2020. Our model provides a tool for policymakers to evaluate the influence of travel between regions on disease transmission in support of strategies for epidemic control.

Trusted Sources of Information and COVID-19 Vaccination Among Black Adults in Chicago

PURPOSE

Examine trust in sources of COVID-19 information and vaccination status.

DESIGN

Cross-sectional.

SETTING

Chicago, Illinois.

SUBJECTS

Convenience sample of 538 Black adults surveyed between September 2021 and March 2022.

MEASURES

Trust in sources of COVID-19 information, COVID-19 vaccination.

ANALYSIS

Using latent class analysis, we identified classes of trust in sources of COVID-19 information. We considered predictors of class membership using multinomial logistic regression and examined unadjusted and adjusted associations between trust class membership and COVID-19 vaccination while accounting for uncertainty in class assignment.

RESULTS

Our analytic sample (n = 522) was predominantly aged 18-34 (52%) and female (71%). Results suggested a four-class solution: (1) low trust, (2) high trust in all sources, (3) high trust in doctor and government, and (4) high trust in doctor, faith leader, and family. Unadjusted odds of vaccination were greater in the high trust in all sources (OR 2.0, 95% CI 1.2-3.2), high trust in doctor and government (OR 2.7, 95% CI 1.4-5.3), and high trust in doctor, faith leader, and family classes (OR 2.1, 95% CI 1.2, 3.9) than the low trust class. However, these associations were not significant after adjustment for sociodemographic and health status factors.

CONCLUSION

Although COVID-19 vaccination varied across trust classes, our adjusted findings do not suggest a direct association between trust and vaccination, reflecting complexities in the vaccine decision-making process.

Social determinants of health in pediatric trauma: Associations with injury mechanisms and outcomes in the context of the COVID-19 pandemic

BACKGROUND

Relationships between social determinants of health and pediatric trauma mechanisms and outcomes are unclear in context of COVID-19.

METHODS

Children <16 years old injured between 2016 and 2021 from ten pediatric trauma centers in Florida were included. Patients were stratified by high vs. low Social Vulnerability Index (SVI). Injury mechanisms studied were child abuse, ATV/golf carts, and firearms. Mechanism incidence trends and mortality were evaluated by interrupted time series and multivariable logistic regression.

RESULTS

Of 19,319 children, 68% and 32% had high and low SVI, respectively. Child abuse increased across SVI strata and did not change with COVID. ATV/golf cart injuries increased after COVID among children with low SVI. Firearm injuries increased after COVID among children with high SVI. Mortality was predicted by injury mechanism, but was not independently associated with SVI, race, or COVID.

CONCLUSION

Social vulnerability influences pediatric trauma mechanisms and COVID effects. Child abuse and firearm injuries should be targeted for prevention.

A systematic review and meta-analysis of the global prevalence and determinants of COVID-19 vaccine acceptance and uptake in people living with HIV

People living with HIV (PLHIV) are at higher risk of poor outcomes of SARS-CoV-2 infection. Here we report the pooled prevalence of COVID-19 vaccine acceptance/uptake and determinants among this vulnerable population of PLHIV based on a systematic review and meta-analysis of studies published by 25 August 2023. Among the 54 included studies (N = 167,485 participants), 53 (N = 166,455) provided data on vaccine acceptance rate, while 27 (N = 150,926) provided uptake data. The global prevalences of COVID-19 vaccine acceptance and uptake were 67.0% and 56.6%, respectively. Acceptance and uptake rates were 86.6% and 90.1% for the European Region, 74.9% and 71.6% for the Region of the Americas, 62.3% and 78.9% for the South-East Asian Region, 64.6% and 19.3% for the Eastern Mediterranean Region, 58.0% and 35.5% for the African Region, and 57.4% and 44.0% for the Western Pacific Region. The acceptance rate increased from 65.9% in 2020 to 71.0% in 2022, and the uptake rate increased from 55.9% in 2021 to 58.1% in 2022. Men, PLHIV aged ≥40 years and those who had recently received the influenza vaccine were more likely to accept and receive the COVID-19 vaccine. Factors associated with lower uptake included Black race, other races (Latinx/Hispanic/mixed race), low education level and being unemployed. Vaccine-related factors associated with higher acceptance included belief in vaccine effectiveness, vaccine trust, perceived high susceptibility to SARS-CoV-2 infection and fear of potential COVID-19 effect in PLHIV. Sustained efforts and targeted interventions are needed to reduce regional disparities in COVID-19 vaccine uptake among PLHIV.

How enlightened self-interest guided global vaccine sharing benefits all: A modeling study

Background

Despite consensus that vaccines play an important role in combatting the global spread of infectious diseases, vaccine inequity is still a prevalent issue due to a deep-seated mentality of self-priority. We aimed to evaluate the existence and possible outcomes of a more equitable global vaccine distribution and explore a concrete incentive mechanism that promotes vaccine equity.

Methods

We designed a metapopulation epidemiological model that simultaneously considers global vaccine distribution and human mobility, which we then calibrated by the number of infections and real-world vaccination records during the coronavirus disease 2019 (COVID-19) pandemic from March 2020 to July 2021. We explored the possibility of the enlightened self-interest incentive mechanism, which comprises improving one's own epidemic outcomes by sharing vaccines with other countries, by evaluating the number of infections and deaths under various vaccine sharing strategies using the proposed model. To understand how these strategies affect the national interests, we distinguished imported from local cases for further cost-benefit analyses that rationalise the enlightened self-interest incentive mechanism behind vaccine sharing.

Results

The proposed model accurately reproduces the real-world cumulative infections for both global and regional epidemics (R2>0.990), which can support the following evaluations of different vaccine sharing strategies: High-income countries can reduce 16.7 (95% confidence interval (CI) = 8.4-24.9, P < 0.001) million infection cases and 82.0 (95% CI = 76.6-87.4, P < 0.001) thousand deaths on average by more actively sharing vaccines in an enlightened self-interest manner, where the reduced internationally imported cases outweigh the threat from increased local infections. Such vaccine sharing strategies can also reduce 4.3 (95% CI = 1.2-7.5, P < 0.01) million infections and 7.0 (95% CI = 5.7-8.3, P < 0.001) thousand deaths in middle- and low-income countries, effectively benefiting the whole global population. Lastly, the more equitable vaccine distribution could help largely reduce the global mobility reduction needed for pandemic control.

Conclusions

The incentive mechanism of enlightened self-interest we explored here could motivate vaccine equity by realigning the national interest to more equitable vaccine distributions. The positive results could promote multilateral collaborations in global vaccine redistribution and reconcile conflicted national interests, which could in turn benefit the global population.

The Health Justice Policy Tracker: COVID-19 Policies To Advance Health Justice For Vulnerable Populations

The rapid spread of COVID-19 throughout the world in early 2020 created unprecedented challenges for national governments. Policies developed during the early months of the pandemic, before the first mRNA vaccines were authorized for emergency use, provide a window into national governments' prioritization of populations that were particularly vulnerable. We developed the COVID-19 Health Justice Policy Tracker to capture and categorize these policies using a health justice lens. In this article we present the results of a preliminary analysis of the tracker data. The tracker focuses on policies for six population groups: children, the elderly, people with disabilities, migrant workers, incarcerated people, and people who were refugees or were seeking political asylum. It includes 610 policies, most targeting children and the elderly and providing financial support. National governments also prioritized measures such as policies to ensure access to mental health care and social services, digital and teleservices, continuity of children's education, and food security. The tracker provides a resource for researchers and policy makers seeking model language and tested policy approaches to advance health justice during future crises.

Addressing health equity in pediatric surgical care in the United States- Progress and challenges

There are notable inequities in health outcomes for children based on their social determinants of health (SDOH), including where they are born and live, their primary language, their race and ethnicity, socioeconomic status, and more. These health inequities are not restricted to resource limited settings; here we highlight three broad topics that are relevant to pediatric surgeons in the United States (US): access to care and disparities, and examples of inequities in firearm-related injuries and appendicitis. Most of our patients will at some point require operative interventions, yet there can be significant challenges in accessing this care and navigating our health systems, particularly around complex perioperative care. There are significant opportunities to improve equitable care by helping patients navigate our health systems and connecting them with additional resources, including screening for primary care services. Firearm-related injuries are now the leading cause of death in children in the US, with significant associated morbidity for non-fatal injuries. There are notable inequities in the risk of injury and types of injuries experienced by children based on their SDOH. Appendicitis is one of the most common pathologies managed by pediatric surgeons, with similar inequities in the rates of perforated appendicitis based on a child's SDOH. For both issues, addressing the inequities our patients experience requires moving upstream and working towards prevention. Key opportunities include better research and data to understand the drivers for observed inequities, multidisciplinary collaboration, community engagement, and public health advocacy among others. As a profession, we have a responsibility to work to address the health inequities our patients experience.

The Supreme Court's Rulings on Race Neutrality Threaten Progress in Medicine and Health

This Viewpoint examines the recent Supreme Court rulings on race neutrality, striking down affirmative action programs in higher education, which will affect efforts to eliminate health inequities in the US.

The association between childhood opportunity index and pediatric hospitalization for firearm injury or motor vehicle crash

BACKGROUND

Community-level factors can profoundly impact children's health, including the risk of violent injury. This study's objective was to understand the relationship between the Childhood Opportunity Index and pediatric firearm injury owing to interpersonal violence compared with a motor vehicle crash.

METHODS

All pediatric patients (<18 years) who presented with an initial encounter with a firearm injury or motor vehicle crash between 2016 to 2021 were identified from 35 children's hospitals included in the Pediatric Health Information System database. The child-specific community-level vulnerability was determined by the Childhood Opportunity Index, a composite score of neighborhood opportunity level data specific to pediatric populations.

RESULTS

We identified 67,407 patients treated for injuries related to motor vehicle crashes (n = 61,527) or firearms (n = 5,880). The overall cohort had a mean age of 9.3 (standard deviation 5.4) years; 50.0% were male patients, 44.0% non-Hispanic Black, and were 60.8% publicly insured. Compared with motor vehicle crash injuries, patients with firearm-related injuries were older (12.2 vs 9.0 years), more likely to be male patients (77.7% vs 47.4%), non-Hispanic Black (63.5% vs 42.1%), and had public insurance (76.4 vs 59.3%; all P < .001). In multivariable analysis, children living in communities with lower Childhood Opportunity Index levels were more likely to present with firearm injury than those living in communities with a very high Childhood Opportunity Index. The odds increased as the Childhood Opportunity Index level decreased (odds ratio 1.33, 1.60, 1.73, 2.00 for high, moderate, low, and very low Childhood Opportunity Index, respectively; all P ≤ .001).

CONCLUSION

Children from lower-Childhood Opportunity Index communities are disproportionately impacted by firearm violence, and these findings have important implications for both clinical care and public health policy.

Can Geographically Targeted Vaccinations Be Ethically Justified? The Case of Norway During the COVID-19 Pandemic

This article discusses the fairness of geographically targeted vaccinations (GTVs). During the initial period of local and global vaccine scarcity, health authorities had to enact priority-setting strategies for mass vaccination campaigns against COVID-19. These strategies have in common that priority setting was based on personal characteristics, such as age, health status or profession. However, in 2021, an alternative to this strategy was employed in some countries, particularly Norway. In these countries, vaccine allocation was also based on the epidemiological situations in different regions, and vaccines were assigned based on local incidence rates. The aim of this article is to describe and examine how a geographical allocation mechanism may work by considering Norway as a case study and discuss what ethical issues may arise in this type of priority setting. We explain three core concepts: priority setting, geographical priority setting and GTVs. With a particular focus on Norway, we discuss the potential effects of GTV, the public perception of such a strategy, and if GTV can be considered a fair strategy. We conclude that the most reasonable defence of GTV seems to be through a consequentialist account that values both total health outcomes and more equal outcomes.

Disproportionate impacts of COVID-19 in a large US city

COVID-19 has disproportionately impacted individuals depending on where they live and work, and based on their race, ethnicity, and socioeconomic status. Studies have documented catastrophic disparities at critical points throughout the pandemic, but have not yet systematically tracked their severity through time. Using anonymized hospitalization data from March 11, 2020 to June 1, 2021 and fine-grain infection hospitalization rates, we estimate the time-varying burden of COVID-19 by age group and ZIP code in Austin, Texas. During this 15-month period, we estimate an overall 23.7% (95% CrI: 22.5-24.8%) infection rate and 29.4% (95% CrI: 28.0-31.0%) case reporting rate. Individuals over 65 were less likely to be infected than younger age groups (11.2% [95% CrI: 10.3-12.0%] vs 25.1% [95% CrI: 23.7-26.4%]), but more likely to be hospitalized (1,965 per 100,000 vs 376 per 100,000) and have their infections reported (53% [95% CrI: 49-57%] vs 28% [95% CrI: 27-30%]). We used a mixed effect poisson regression model to estimate disparities in infection and reporting rates as a function of social vulnerability. We compared ZIP codes ranking in the 75th percentile of vulnerability to those in the 25th percentile, and found that the more vulnerable communities had 2.5 (95% CrI: 2.0-3.0) times the infection rate and only 70% (95% CrI: 60%-82%) the reporting rate compared to the less vulnerable communities. Inequality persisted but declined significantly over the 15-month study period. Our results suggest that further public health efforts are needed to mitigate local COVID-19 disparities and that the CDC's social vulnerability index may serve as a reliable predictor of risk on a local scale when surveillance data are limited.

Factors associated with COVID-19 vaccination during June-October 2021: A multi-site prospective study

INTRODUCTION

Vaccine hesitancy presents a challenge to COVID-19 control efforts. To identify beliefs associated with delayed vaccine uptake, we developed and implemented a vaccine hesitancy survey for the COVID-19 Community Research Partnership.

METHODS

In June 2021, we assessed attitudes and beliefs associated with COVID-19 vaccination using an online survey. Self-reported vaccination data were requested daily through October 2021. We compared responses between vaccinated and unvaccinated respondents using absolute standardized mean differences (ASMD). We assessed validity and reliability using exploratory factor analysis and identified latent factors associated with a subset of survey items. Cox proportional hazards models and mediation analyses assessed predictors of subsequent vaccination among those initially unvaccinated.

RESULTS

In June 2021, 29,522 vaccinated and 1,272 unvaccinated participants completed surveys. Among those unvaccinated in June 2021, 559 (43.9 %) became vaccinated by October 31, 2021. In June, unvaccinated participants were less likely to feel "very concerned" about getting COVID-19 than vaccinated participants (10.6 % vs. 43.3 %, ASMD 0.792). Among those initially unvaccinated, greater intent to become vaccinated was associated with getting vaccinated and shorter time to vaccination. However, even among participants who reported no intention to become vaccinated, 28.5 % reported vaccination before study end. Two latent factors predicted subsequent vaccination-being 'more receptive' was derived from motivation to protect one's own or others' health and resume usual activities; being 'less receptive' was derived from concerns about COVID-19 vaccines. In a Cox model, both factors were partially mediated by vaccination intention.

CONCLUSION

This study characterizes vaccine hesitant individuals and identifies predictors of eventual COVID-19 vaccination through October 31, 2021. Even individuals with no intention to be vaccinated can shift to vaccine uptake. Our data suggest factors of perceived severity of COVID-19 disease, vaccine safety, and trust in the vaccine development process are predictive of vaccination and may be important opportunities for ongoing interventions.

What is the role of primary care in the COVID-19 vaccine roll-out and the barriers and facilitators to an equitable vaccine roll-out? A rapid scoping review of nine jurisdictions

OBJECTIVES

This study aimed to: (1) examine the experience of nine global jurisdictions that engaged primary care providers (PCPs) to administer COVID-19 vaccines during the pandemic; (2) describe how vaccine hesitancy and principles of equity were incorporated in the COVID-19 vaccine roll-out strategies and (3) identify the barriers and facilitators to the vaccine roll-out.

DESIGN

Rapid scoping review.

DATA SOURCES

Searches took place in MEDLINE, CINAHL, Embase, the Cochrane Library, SCOPUS and PsycINFO, Google, and the websites of national health departments. Searches and analyses took place from May 2021 to July 2021.

RESULTS

Sixty-two documents met the inclusion criteria (35=grey literature; 56% and 27=peer reviewed; 44%). This review found that the vaccine distribution approach started at hospitals in almost all jurisdictions. In some jurisdictions, PCPs were engaged at the beginning, and the majority included PCPs over time. In many jurisdictions, equity was considered in the prioritisation policies for various marginalised communities. However, vaccine hesitancy was not explicitly considered in the design of vaccine distribution approaches. The barriers to the roll-out of vaccines included personal, organisational and contextual factors. The vaccine roll-out strategy was facilitated by establishing policies and processes for pandemic preparedness, well-established and coordinated information systems, primary care interventions, adequate supply of providers, education and training of providers, and effective communications strategy.

CONCLUSIONS

Empirical evidence is lacking on the impact of a primary care-led vaccine distribution approach on vaccine hesitancy, adoption and equity. Future vaccine distribution approaches need to be informed by further research evaluating vaccine distribution approaches and their impact on patient and population outcomes.

Understanding mobility change in response to COVID-19: A Los Angeles case study

The COVID-19 pandemic has affected people's lives throughout the world. Governments have imposed restrictions on business and social activities to reduce the spread of the virus. In the US, the pandemic response has been largely left to state and local governments, resulting in a patchwork of policies that frequently changed. We examine travel behavior across income and race/ethnic groups in Los Angeles County over several stages of the pandemic. We use a difference-in-difference model based on mobile device data to compare mobility patterns before and during the various stages of the pandemic. We find a strong relationship between income/ethnicity and mobility. Residents of low-income and ethnic minority neighborhoods reduced travel less than residents of middle- and high-income neighborhoods during the shelter-in-place order, consistent with having to travel for work or other essential purposes. As public health rules were relaxed and COVID vaccines became available, residents of high-income and White neighborhoods increased travel more than other groups, suggesting more discretionary travel. Our trip purpose model results show that residents of low-income and ethnic minority neighborhoods reduced work and shopping travel less than those of White and high-income neighborhoods during the shelter-in-place order. Results are consistent with higher-income workers more likely being able to work at home than lower-income workers. In contrast, low-income/minorities apparently have more constraints associated with work or household care. The consequence is less capacity to avoid virus risk. Race and socioeconomic disparities are revealed in mobility patterns observed during the COVID-19 pandemic.

Research in the USA on COVID-19's long-term effects: measures needed to ensure black, indigenous and Latinx communities are not left behind

The SARS-CoV-2 (COVID-19) pandemic continues to expose underlying inequities in healthcare for black, indigenous and Latinx communities in the USA. The gaps in equitable care for communities of colour transcend the diagnosis, treatment and vaccinations related to COVID-19. We are experiencing a continued gap across racial and socioeconomic lines for those who suffer prolonged effects of COVID-19, also known as 'Long COVID-19'. What we know about the treatment for Long COVID-19 so far is that it is complex, requires a multidisciplinary approach and there is still much research needed to fully understand the effects. In this paper, we discuss pragmatic considerations for including affected communities, relevant stakeholders, and leaders from communities of colour in the planning and implementation of Long COVID-19 research.

Behavioral and Social Drivers of COVID-19 Vaccination in the United States, August-November 2021

INTRODUCTION

COVID-19 vaccines are safe, effective, and widely available, but many adults in the U.S. have not been vaccinated for COVID-19. This study examined the associations between behavioral and social drivers of vaccination with COVID-19 vaccine uptake in the U.S. adults and their prevalence by region.

METHODS

A nationally representative sample of U.S. adults participated in a cross-sectional telephone survey in August-November 2021; the analysis was conducted in January 2022. Survey questions assessed self-reported COVID-19 vaccine initiation, demographics, and behavioral and social drivers of vaccination.

RESULTS

Among the 255,763 respondents, 76% received their first dose of COVID-19 vaccine. Vaccine uptake was higher among respondents aged ≥75 years (94%), females (78%), and Asian non-Hispanic people (94%). The drivers of vaccination most strongly associated with uptake included higher anticipated regret from nonvaccination, risk perception, and confidence in vaccine safety and importance, followed by work- or school-related vaccination requirements, social norms, and provider recommendation (all p<0.05). The direction of association with uptake varied by reported level of difficulty in accessing vaccines. The prevalence of all of these behavioral and social drivers of vaccination was highest in the Northeast region and lowest in the Midwest and South.

CONCLUSIONS

This nationally representative survey found that COVID-19 vaccine uptake was most strongly associated with greater anticipated regret, risk perception, and confidence in vaccine safety and importance, followed by vaccination requirements and social norms. Interventions that leverage these social and behavioral drivers of vaccination have the potential to increase COVID-19 vaccine uptake and could be considered for other vaccine introductions.

Ethnic differences in COVID-19 mortality in the second and third waves of the pandemic in England during the vaccine rollout: a retrospective, population-based cohort study

BACKGROUND

Ethnic minority groups in England have been disproportionately affected by the COVID-19 pandemic and have lower vaccination rates than the White British population. We examined whether ethnic differences in COVID-19 mortality in England have continued since the vaccine rollout and to what extent differences in vaccination rates contributed to excess COVID-19 mortality after accounting for other risk factors.

METHODS

We conducted a retrospective, population-based cohort study of 28.8 million adults aged 30-100 years in England. Self-reported ethnicity was obtained from the 2011 Census. The outcome was death involving COVID-19 during the second (8 December 2020 to 12 June 2021) and third wave (13 June 2021 to 1 December 2021). We calculated hazard ratios (HRs) for death involving COVID-19, sequentially adjusting for age, residence type, geographical factors, sociodemographic characteristics, pre-pandemic health, and vaccination status.

RESULTS

Age-adjusted HRs of death involving COVID-19 were elevated for most ethnic minority groups during both waves, particularly for groups with lowest vaccination rates (Bangladeshi, Pakistani, Black African, and Black Caribbean). HRs were attenuated after adjusting for geographical factors, sociodemographic characteristics, and pre-pandemic health. Further adjusting for vaccination status substantially reduced residual HRs for Black African, Black Caribbean, and Pakistani groups in the third wave. Fully adjusted HRs only remained elevated for the Bangladeshi group (men: 2.19 [95% CI 1.72-2.78]; women: 2.12 [1.58-2.86]) and Pakistani men (1.24 [1.06-1.46]).

CONCLUSIONS

Lower COVID-19 vaccination uptake in several ethnic minority groups may drive some of the differences in COVID-19 mortality compared to White British. Public health strategies to increase vaccination uptake in ethnic minority groups would help reduce inequalities in COVID-19 mortality, which have remained substantial since the start of the vaccination campaign.

Private equity in ophthalmology and optometry: a time series analysis from 2012 to 2021

Purpose

To identify temporal and geographic trends in private equity (PE)-backed acquisitions of ophthalmology and optometry practices in the United States from 2012 to 2021.

Methods

In this cross-sectional time series, acquisition data from 10/21/2019 to 9/1/2021 and previously published data from 1/1/2012 to 10/20/2019 were analyzed. Acquisition data were compiled from 6 financial databases, 5 industry news outlets, and publicly available press releases. Linear regression models were used to compare rates of acquisition. Outcomes included number of total acquisitions, practice type, locations, provider details, and geographic footprint.

Results

A total of 245 practices associated with 614 clinical locations and 948 ophthalmologists or optometrists were acquired by 30 PE-backed platform companies between 10/21/2019 and 9/1/2021. Of 30 platform companies, 18 were new vis-à-vis our prior study. Of these acquisitions, 127 were comprehensive practices, 29 were retina practices, and 89 were optometry practices. From 2012 to 2021, monthly acquisitions increased by 0.947 acquisitions per year (P < 0.001*). Texas, Florida, Michigan, and New Jersey were the states with the greatest number of PE acquisitions, with 55, 48, 29, and 28 clinic acquisitions, respectively. Average monthly PE acquisitions were 5.71 per month from 1/1/2019 to 2/29/2020 (pre-COVID), 5.30 per month from 3/1/2020 to 12/31/2020 (COVID pre-vaccine [P = 0.81]), and 8.78 per month from 1/1/2021 to 9/1/2021 (COVID post-vaccine [P = 0.20]).

Conclusions

PE acquisitions increased during the period 2012-2021 as companies continue to utilize regionally focused strategies for acquisitions.

COVID-19 Booster Dose Vaccination Coverage and Factors Associated with Booster Vaccination among Adults, United States, March 2022

The Centers for Disease Control and Prevention recommends a COVID-19 vaccine booster dose for all persons >18 years of age. We analyzed data from the National Immunization Survey-Adult COVID Module collected during February 27-March 26, 2022 to assess COVID-19 booster dose vaccination coverage among adults. We used multivariable logistic regression analysis to assess factors associated with vaccination. COVID-19 booster dose coverage among fully vaccinated adults increased from 25.7% in November 2021 to 63.4% in March 2022. Coverage was lower among non-Hispanic Black (52.7%), and Hispanic (55.5%) than non-Hispanic White adults (67.7%). Coverage was 67.4% among essential healthcare personnel, 62.2% among adults who had a disability, and 69.9% among adults who had medical conditions. Booster dose coverage was not optimal, and disparities by race/ethnicity and other factors are apparent in coverage uptake. Tailored strategies are needed to educate the public and reduce disparities in COVID-19 vaccination coverage.

Ethical allocation of scarce vaccine doses: The Priority-Equality protocol

Background

Whenever vaccines for a new pandemic or widespread epidemic are developed, demand greatly exceeds the available supply of vaccine doses in the crucial, initial phases of vaccination. Rationing protocols must then fulfill a number of ethical principles balancing equal treatment of individuals and prioritization of at-risk and instrumental subpopulations. For COVID-19, actual rationing methods used a territory-based first allocation stage based on proportionality to population size, followed by locally-implemented prioritization rules. The results of this procedure have been argued to be ethically problematic.

Methods

We use a formal-analytical approach arising from the mathematical social sciences which allows to investigate whether any allocation methods (known or unknown) fulfill a combination of (ethical) desiderata and, if so, how they are formulated algorithmically.

Results

Strikingly, we find that there exists one and only one method that allows to treat people equally while giving priority to those who are worse off. We identify this method down to the algorithmic level and show that it is easily implementable and it exhibits additional, desirable properties. In contrast, we show that the procedures used during the COVID-19 pandemic violate both principles.

Conclusions

Our research delivers an actual algorithm that is readily applicable and improves upon previous ones. Since our axiomatic approach shows that any other algorithm would either fail to treat people equally or fail to prioritize those who are worse off, we conclude that ethical principles dictate the adoption of this algorithm as a standard for the COVID-19 or any other comparable vaccination campaigns.

The disparate impact of age-based COVID-19 vaccine prioritization by race/ethnicity in Denver, Colorado

COVID-19 vaccines are an effective tool in preventing severe disease. Most states used an age-based prioritization for vaccine rollout. We examined the impact of a primarily age-based prioritization policy on reductions of severe disease in different racial and ethnic groups. We calculated age-specific rates of COVID-19 hospitalization and death by race/ethnicity in Denver, Colorado. To assess potentially averted hospitalizations and deaths by race/ethnicity, we then applied the first three phases of Colorado's primarily age-based vaccine rollout criteria to historical 2020 COVID-19 hospitalizations and deaths in Denver, Colorado. In the first 3 phases, 40% (1403/3473) of hospitalizations and 83% (503/604) of deaths occurred among those meeting age and long-term care facility criteria and could have been averted. Impacts varied by race/ethnicity with only 28% (440/1587) of hospitalizations and 74% (131/178) of deaths averted among Hispanic or Latino residents, compared to 57% (619/1094) of hospitalizations and 92% (252/274) of deaths among non-Hispanic White residents. We demonstrate using local data and policy that early age-based prioritization decisions disproportionately promoted reductions in severe disease among non-Hispanic White residents irrespective of COVID-19 risk in Denver, Colorado. These findings suggest that more equitable future vaccine prioritization policies, which lead with a goal of reducing health disparities through prioritizing susceptibility to adverse health outcomes rather than overall population-based cutoffs, are necessary. Our results have implications for future vaccination rollouts in limited vaccine resource conditions.

Use Of Area-Based Socioeconomic Deprivation Indices: A Scoping Review And Qualitative Analysis

There is considerable interest among researchers, clinicians, and policy makers in understanding the impact of place on health. In this scoping review and qualitative analysis, we sought to assess area-level socioeconomic deprivation indices used in public health and health outcomes research in the US. We conducted a systematic scoping review to identify area-level socioeconomic deprivation indices commonly used in the US since 2015. We then qualitatively compared the indices based on the input-variable domains, data sources, index creation characteristics, index accessibility, the geography over which the index is applied, and the nature of the output measure or measures. We identified fifteen commonly used indices of area-level socioeconomic deprivation. There were notable differences in the characteristics of each index, particularly in how they define socioeconomic deprivation based on input-variable domains, the geography over which they are applied, and their output measures. These characteristics can help guide future index selection and application in clinical care, research, and policy decisions.

Assessment of Population-Level Disadvantage Indices to Inform Equitable Health Policy

Policy Points The rapid uptake of disadvantage indices during the pandemic highlights investment in implementing tools that address health equity to inform policy. Existing indices differ in their design, including data elements, social determinants of health domains, and geographic unit of analysis. These differences can lead to stark discrepancies in place-based social risk scores depending on the index utilized. Disadvantage indices are useful tools for identifying geographic patterns of social risk; however, indiscriminate use of indices can have varied policy implications and unintentionally worsen equity. Implementers should consider which indices are suitable for specific communities, objectives, potential interventions, and outcomes of interest.

CONTEXT

There has been unprecedented uptake of disadvantage indices such as the Centers for Disease Control and Prevention Social Vulnerability Index (SVI) to identify place-based patterns of social risk and guide equitable health policy during the COVID-19 pandemic. However, limited evidence around data elements, interoperability, and implementation leaves unanswered questions regarding the utility of indices to prioritize health equity.

METHODS

We identified disadvantage indices that were (a) used three or more times from 2018 to 2021, (b) designed using national-level data, and (c) available at the census-tract or block-group level. We used a network visualization to compare social determinants of health (SDOH) domains across indices. We then used geospatial analyses to compare disadvantage profiles across indices and geographic areas.

FINDINGS

We identified 14 indices. All incorporated data from public sources, with half using only American Community Survey data (n = 7) and the other half combining multiple sources (n = 7). Indices differed in geographic granularity, with county level (n = 5) and census-tract level (n = 5) being the most common. Most states used the SVI during the pandemic. The SVI, the Area Deprivation Index (ADI), the COVID-19 Community Vulnerability Index (CCVI), and the Child Opportunity Index (COI) met criteria for further analysis. Selected indices shared five indicators (income, poverty, English proficiency, no high school diploma, unemployment) but varied in other metrics and construction method. While mapping of social risk scores in Durham County, North Carolina; Cook County, Illinois; and Orleans Parish, Louisiana, showed differing patterns within the same locations depending on choice of disadvantage index, risk scores across indices showed moderate to high correlation (rs 0.7-1). However, spatial autocorrelation analyses revealed clustering, with discrepant distributions of social risk scores between different indices.

CONCLUSIONS

Existing disadvantage indices use varied metrics to represent place-based social risk. Within the same geographic area, different indices can provide differences in social risk values and interpretations, potentially leading to varied public health or policy responses.

Public attitudes about equitable COVID-19 vaccine allocation: a randomised experiment of race-based versus novel place-based frames

Equity was-and is-central in the US policy response to COVID-19, given its disproportionate impact on disadvantaged communities of colour. In an unprecedented turn, the majority of US states used place-based disadvantage indices to promote equity in vaccine allocation (eg, through larger vaccine shares for more disadvantaged areas and people of colour).We conducted a nationally representative survey experiment (n=2003) in April 2021 (before all US residents had become vaccine eligible), that examined respondents' perceptions of the acceptability of disadvantage indices relative to two ways of prioritising racial and ethnic groups more directly, and assessed the role of framing and expert anchors in shaping perceptions.A majority of respondents supported the use of disadvantage indices, and one-fifth opposed any of the three equity-promoting plans. Differences in support and opposition were identified by respondents' political party affiliation. Providing a numerical anchor (that indicated expert recommendations and states' actual practices in reserving a proportion of allocations for prioritised groups) led respondents to prefer a lower distribution of reserved vaccine allocations compared with the randomised condition without this anchor, and the effect of the anchor differed across the frames.Our findings support ongoing uses of disadvantage indices in vaccine allocation, and, by extension, in allocating tests, masks or treatments, especially when supply cannot meet demand. The findings can also inform US allocation frameworks in future pandemic planning, and could provide lessons on how to promote equity in clinical and public health outside of the pandemic setting.

Associations of 4 Geographic Social Vulnerability Indices With US COVID-19 Incidence and Mortality

Objectives. To examine and compare how 4 indices of population-level social disadvantage-the Social Vulnerability Index (SVI), the Area Deprivation Index (ADI), the COVID-19 Community Vulnerability Index (CCVI), and the Minority Health-Social Vulnerability Index (MH-SVI)-are associated with COVID-19 outcomes. Methods. Spatial autoregressive models adjusted for population density, urbanicity, and state fixed effects were used to estimate associations of county-level SVI, MH-SVI, CCVI, and ADI values with COVID-19 incidence and mortality. Results. All 4 disadvantage indices had similar positive associations with COVID-19 incidence. Each index was also significantly associated with COVID-19 mortality, but the ADI had a stronger association than the CCVI, MH-SVI, and SVI. Conclusions. Despite differences in component measures and weighting, all 4 of the indices we assessed demonstrated associations between greater disadvantage and COVID-19 incidence and mortality. Public Health Implications. Our findings suggest that each of the 4 disadvantage indices can be used to assist public health leaders in targeting ongoing first-dose and booster or third-dose vaccines as well as new vaccines or other resources to regions most vulnerable to negative COVID-19 outcomes, weighing potential tradeoffs in their political and practical acceptability. (Am J Public Health. 2022;112(11):1584-1588. https://doi.org/10.2105/AJPH.2022.307018).

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.

Location Optimization of COVID-19 Vaccination Sites: Case in Hillsborough County, Florida

The equitable allocation of COVID-19 vaccines is a critical challenge worldwide, given that the pandemic has been disproportionally affecting economically disadvantaged racial and ethnic groups. In the United States, the ongoing implementation efforts at different administrative levels and districts, to some extent, are standing in conflict with commitments to mitigate inequities. In this study, we developed a spatial optimization model to choose the best locations for vaccination sites. The model is a modified two-step maximal covering location problem (MCLP). It aims at maximizing the number of residents who can conveniently access the sites and mitigating inequity issues by prioritizing disadvantaged population groups who live in geographic areas identified through the CDC's Social Vulnerability Index (SVI). We conducted our study using the case of Hillsborough County, Florida. We found that by reserving up to 30% of total vaccines for highly vulnerable communities, our model can optimize location choices for vaccination sites to provide effective coverage for residents at large while prioritizing disadvantaged groups of people. A series of sensitivity analyses have been performed to evaluate the impact of parameters such as site capacity and distance threshold. The model has the potential to guide the future allocation of critical medical resources in the U.S. and other countries.

Errors in Converting Principles to Protocols: Where the Bioethics of U.S. Covid-19 Vaccine Allocation Went Wrong

For much of 2021, allocating the scarce supply of Covid-19 vaccines was the world's most pressing bioethical challenge, and similar challenges may recur for novel therapies and future vaccines. In the United States, the Centers for Disease Control and Prevention's Advisory Committee on Immunization Practices (ACIP) identified three fundamental ethical principles to guide the process: maximize benefits, promote justice, and mitigate health inequities. We argue that critical components of the recommended protocol were internally inconsistent with these principles. Specifically, the ACIP violated its principles by recommending overly broad health care worker priority in phase 1a, using being at least seventy-five years of age as the only criterion to identify individuals at high risk of death from Covid-19 during phase 1b, failing to recommend place-based vaccine distribution, and implicitly endorsing first-come, first-served allocation. More rigorous empirical work and the development of a complete ethical framework that recognizes trade-offs between principles may have prevented these mistakes and saved lives.

COVID-19 Vaccine Mandates for Healthcare Professionals in the United States

Healthcare workers (HCWs) need to be vaccinated against COVID-19 because they care for vulnerable patients. Hesitation to receiving the COVID-19 vaccine stems from the argument of bodily autonomy, novel mRNA vaccine technology, and conspiracy theories. However, vaccinations may prevent thousands of hospitalizations and deaths. HCWs have previously complied with other required vaccinations to care for children, elderly, and immunocompromised patients. Yet, COVID-19 vaccination mandates in the healthcare setting have been faced with resistance and subsequent staffing shortages. As HCWs display their hesitation to the vaccine, the community loses trust in its efficacy and safety. Speculation on pharmaceutical profiteering has also contributed to vaccine mistrust. As the pandemic continues, the healthcare field must decide on a course of action: adhere to vaccination mandates and cope with decreased staffing, repeal vaccination mandates to recover staff, rely on personal protective equipment (PPE) alone for protection, or do nothing and expect survival through herd immunity. To date, the United States has chosen to mandate COVID-19 vaccinations for any healthcare worker employed by Medicare and/or Medicaid-accepting facilities, allowing allergy and religious exemptions. This COVID-19 vaccination mandate for HCWs ethically protects the vulnerable people who HCWs vow to care for.

Ensuring Equitable COVID-19 Vaccine Allocation in New Hampshire: The First Eight Months toward a New Era

The global coronavirus disease 2019 (COVID-19) pandemic has been exacerbated by social vulnerabilities and racial disparities, resulting in disproportionate morbidity and mortality that require continued attention to strategies that ensure equitable vaccine allocation. The State of New Hampshire (NH) developed a transparent framework to guide COVID-19 vaccine allocation plans, of which one key component was the allocation of 10% of vaccine supply to disproportionately impacted and highly vulnerable populations, predominantly identified through a national vulnerability index. The process, operational approaches, ethical challenges, and unanticipated consequences resulted in many valuable lessons learned. Equitable allocation of this limited and critical pandemic countermeasure required public understanding and engagement, which was achieved through a publicly available framework that was flexible, resourced using public funds, and widely communicated. Broad partnerships were also critical to addressing disparities in the delivery of vaccine. The lessons learned and described here will facilitate more nimble and equitable jurisdictional responses in future public health emergencies.

Strategic COVID-19 vaccine distribution can simultaneously elevate social utility and equity

Balancing social utility and equity in distributing limited vaccines is a critical policy concern for protecting against the prolonged COVID-19 pandemic and future health emergencies. What is the nature of the trade-off between maximizing collective welfare and minimizing disparities between more and less privileged communities? To evaluate vaccination strategies, we propose an epidemic model that explicitly accounts for both demographic and mobility differences among communities and their associations with heterogeneous COVID-19 risks, then calibrate it with large-scale data. Using this model, we find that social utility and equity can be simultaneously improved when vaccine access is prioritized for the most disadvantaged communities, which holds even when such communities manifest considerable vaccine reluctance. Nevertheless, equity among distinct demographic features may conflict; for example, low-income neighbourhoods might have fewer elder citizens. We design two behaviour-and-demography-aware indices, community risk and societal risk, which capture the risks communities face and those they impose on society from not being vaccinated, to inform the design of comprehensive vaccine distribution strategies. Our study provides a framework for uniting utility and equity-based considerations in vaccine distribution and sheds light on how to balance multiple ethical values in complex settings for epidemic control.

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

Differences in vaccination coverage can perpetuate coronavirus disease 2019 (COVID-19) disparities. We explored the association between neighborhood-level social vulnerability and COVID-19 vaccination coverage in 16 large US cities from the beginning of the vaccination campaign in December 2020 through September 2021. We calculated the proportion of fully vaccinated adults in 866 zip code tabulation areas (ZCTAs) of 16 large US cities: Long Beach, Los Angeles, Oakland, San Diego, San Francisco, and San Jose, all in California; Chicago, Illinois; Indianapolis, Indiana; Minneapolis, Minnesota; New York, New York; Philadelphia, Pennsylvania; and Austin, Dallas, Fort Worth, Houston, and San Antonio, all in Texas. We computed absolute and relative total and Social Vulnerability Index-related inequities by city. COVID-19 vaccination coverage was 0.75 times (95% confidence interval: 0.69, 0.81) or 16 percentage points (95% confidence interval: 12.1, 20.3) lower in neighborhoods with the highest social vulnerability as compared with those with the lowest. These inequities were heterogeneous, with cities in the West generally displaying narrower inequities in both the absolute and relative scales. The Social Vulnerability Index domains of socioeconomic status and of household composition and disability showed the strongest associations with vaccination coverage. Inequities in COVID-19 vaccinations hamper efforts to achieve health equity, as they mirror and could lead to even wider inequities in other COVID-19 outcomes.

Quantifying inequities in COVID-19 vaccine distribution over time by social vulnerability, race and ethnicity, and location: A population-level analysis in St. Louis and Kansas City, Missouri

BACKGROUND

Equity in vaccination coverage is a cornerstone for a successful public health response to COVID-19. To deepen understanding of the extent to which vaccination coverage compares with initial strategies for equitable vaccination, we explore primary vaccine series and booster rollout over time and by race/ethnicity, social vulnerability, and geography.

METHODS AND FINDINGS

We analyzed data from the Missouri Department of Health and Senior Services on all COVID-19 vaccinations administered across 7 counties in the St. Louis region and 4 counties in the Kansas City region. We compared rates of receiving the primary COVID-19 vaccine series and boosters relative to time, race/ethnicity, zip-code-level Social Vulnerability Index (SVI), vaccine location type, and COVID-19 disease burden. We adapted a well-established tool for measuring inequity-the Lorenz curve-to quantify inequities in COVID-19 vaccination relative to these key metrics. Between 15 December 2020 and 15 February 2022, 1,763,036 individuals completed the primary series and 872,324 received a booster. During early phases of the primary series rollout, Black and Hispanic individuals from high SVI zip codes were vaccinated at less than half the rate of White individuals from low SVI zip codes, but rates increased over time until they were higher than rates in White individuals after June 2021; Asian individuals maintained high levels of vaccination throughout. Increasing vaccination rates in Black and Hispanic communities corresponded with periods when more vaccinations were offered at small community-based sites such as pharmacies rather than larger health systems and mass vaccination sites. Using Lorenz curves, zip codes in the quartile with the lowest rates of primary series completion accounted for 19.3%, 18.1%, 10.8%, and 8.8% of vaccinations while representing 25% of the total population, cases, deaths, or population-level SVI, respectively. When tracking Gini coefficients, these disparities were greatest earlier during rollout, but improvements were slow and modest and vaccine disparities remained across all metrics even after 1 year. Patterns of disparities for boosters were similar but often of much greater magnitude during rollout in fall 2021. Study limitations include inherent limitations in the vaccine registry dataset such as missing and misclassified race/ethnicity and zip code variables and potential changes in zip code population sizes since census enumeration.

CONCLUSIONS

Inequities in the initial COVID-19 vaccination and booster rollout in 2 large US metropolitan areas were apparent across racial/ethnic communities, across levels of social vulnerability, over time, and across types of vaccination administration sites. Disparities in receipt of the primary vaccine series attenuated over time during a period in which sites of vaccination administration diversified, but were recapitulated during booster rollout. These findings highlight how public health strategies from the outset must directly target these deeply embedded structural and systemic determinants of disparities and track equity metrics over time to avoid perpetuating inequities in healthcare access.

Hierarchical Multi-agent Model for Reinforced MedicalResource Allocation with Imperfect Information

Facing the outbreak of COVID-19, shortage in medical resources becomes increasingly outstanding. Therefore, efficient strategies for medical resource allocation are urgently called for. However, conventional rule-based methods from public health experts have limited capability in dealing with the complex and dynamic pandemic spreading situation. Besides, model-based optimization methods such as dynamic programming (DP) fails to work since we cannot obtain a precise model in the real-world situation most of the time. On the other hand, model-free reinforcement learning (RL) is powerful for decision making, but three key challenges exist in solving this problem via RL: (1) complex situation and countless choices for decision making in the real world; (2) only imperfect information are available due to the latency of pandemic spreading; (3) limitations on conducting experiments in real-world since we cannot set pandemic outbreaks arbitrarily. In this paper, we propose a hierarchical reinforcement learning framework with several specially designed components. We design a decomposed action space with a corresponding training algorithm to deal with the countless choices and ensure efficient and real time strategies. We design an recurrent neural network based framework to utilize the imperfect information obtained from the environment. We also design a multi-agents voting method, which modifies the decision making process considering the randomness during model training and thus improves the performance. We build a pandemic spreading simulator based on real world data, serving as the experimental platform. We conduct extensive experiments and the results show that our method outperforms all the baselines, which reduces infections and deaths by 14.25% on average without the multi-agents voting method and up to 15.44% with it.

Using the Points of Distribution Site Model for Timely and Safe Administration of COVID-19 Vaccinations During the Pandemic

The Georgia Department of Public Health-East Central District and its local partners implemented an open, drive-through point of distribution site to administer the COVID-19 vaccine to eligible populations. The site was in Augusta, Georgia, from mid-December 2020 through mid-May 2021. The target population for this intervention was individuals eligible for the COVID-19 vaccine to prevent and slow transmission of severe acute respiratory syndrome coronavirus 2 infection. The point of distribution site successfully provided 42 342 vaccines. (Am J Public Health. 2022;112(S3):S279-S283. https://doi.org/10.2105/AJPH.2022.306820).

COVID-19 needs no passport: the interrelationship of the COVID-19 pandemic along the U.S.-Mexico border

OBJECTIVES

To investigate the impact of the COVID-19 pandemic along the U.S.-Mexico border region and evaluate the relationship of COVID-19 related mortality, socioeconomic status, and vaccination.

METHODS

We used indirect standardization to age-adjust mortality rates and calculate standardized mortality ratios [SMR] in both countries. To examine the impact of socioeconomic factors, we calculated the Human Development Index (HDI) by county/municipality. We performed linear regression to understand the relationship between mortality, vaccination, and HDI. We used choropleth maps to visualize the trends seen in the region.

RESULTS

Between January 22nd, 2020 and December 1st, 2021, surges of cases and deaths were similar in dyad cities along the U.S.-Mexico border visualizing the interconnectedness of the region. Mortality was higher in U.S. counties along the border compared to the national average (SMR 1.17, 95% CI 1.15-1.19). In Mexico, border counties had a slightly lower mortality to the national average (SMR 0.94, 95% CI 0.93-0.95). In U.S. border states, SMR was shown to negatively correlate with human development index (HDI), a socioeconomic proxy, resulting in a higher SMR in the border region compared to the rest of the counties. Conversely in Mexican border states, there was no association between SMR and HDI. Related to vaccination, U.S. counties along the border were vaccinated at a greater percentage than non-border counties and vaccination was negatively correlated with HDI. In Mexico, states along the border had a higher ratio of vaccinations per person than non-border states.

CONCLUSIONS

The U.S.-Mexico border is a divide of incredible importance not only to immigration but as a region with unique social, economic, environmental, and epidemiological factors that impact disease transmission. We investigated how the COVID-19 pandemic followed trends of previously studied diseases in the corridor such as tuberculosis, HIV, and influenza H1N1. These data state how targeted intervention along the U.S.-Mexico border region is a necessity when confronting COVID-19 and have implications for future control of infectious diseases in the region.

Evaluating the complex association between Social Vulnerability Index and trauma mortality

INTRODUCTION

Social determinants of health are known to impact patient-level outcomes, but they are often difficult to measure. The Social Vulnerability Index was created by the Centers for Disease Control to identify vulnerable communities using population-based measures. However, the relationship between SVI and trauma outcomes is poorly understood.

METHODS

In this retrospective study, we merged SVI data with a statewide trauma registry and used three analytic models to evaluate the association between SVI quartile and inpatient trauma mortality: (1) an unadjusted model, (2) a claims-based model using only covariates available to claims datasets, and (3) a registry-based model incorporating robust clinical variables collected in accordance with the National Trauma Data Standard.

RESULTS

We identified 83,607 adult trauma admissions from January 1, 2017, to September 30, 2020. Higher SVI was associated with worse mortality in the unadjusted model (odds ratio, 1.72 [95% confidence interval, 1.30-2.29] for highest vs. lowest SVI quintile). A weaker association between SVI and mortality was identified after adjusting for covariates common to claims data. Finally, there was no significant association between SVI and inpatient mortality after adjusting for covariates common to robust trauma registries (adjusted odds ratio, 1.10 [95% confidence interval, 0.80-1.53] for highest vs. lowest SVI quintile). Higher SVI was also associated with a higher likelihood of presenting with penetrating injuries, a shock index of >0.9, any Abbreviated Injury Scale score of >5, or in need of a blood transfusion (p < 0.05 for all).

CONCLUSION

Patients living in communities with greater social vulnerability are more likely to die after trauma admission. However, after risk adjustment with robust clinical covariates, this association was no longer significant. Our findings suggest that the inequitable burden of trauma mortality is not driven by variation in quality of treatment, but rather in the lethality of injuries. As such, improving trauma survival among high-risk communities will require interventions and policies that target social and structural inequities upstream of trauma center admission.

LEVEL OF EVIDENCE

Prognostic / Epidemiologic, Level IV.

Contribution of Individual- and Neighborhood-Level Social, Demographic, and Health Factors to COVID-19 Hospitalization Outcomes

BACKGROUND

Although disparities in COVID-19 outcomes have been observed, factors contributing to these differences are not well understood.

OBJECTIVE

To determine whether COVID-19 hospitalization outcomes are related to neighborhood-level social vulnerability, independent of patient-level clinical factors.

DESIGN

Pooled cross-sectional study of prospectively collected data.

SETTING

38 Michigan hospitals.

PATIENTS

Adults older than 18 years hospitalized for COVID-19 in a participating site between March and December 2020.

MEASUREMENTS

COVID-19 outcomes included acute organ dysfunction, organ failure, invasive mechanical ventilation, intensive care unit stay, death, and discharge disposition. Social vulnerability was measured by the social vulnerability index (SVI), a composite measure of social disadvantage.

RESULTS

Compared with patients in low-vulnerability ZIP codes, those living in high-vulnerability ZIP codes were more frequently treated in the intensive care unit (29.0% vs. 24.5%); more frequently received mechanical ventilation (19.3% vs. 14.2%); and experienced higher rates of organ dysfunction (51.9% vs. 48.6%), organ failure (54.7% vs. 51.6%), and in-hospital death (19.4% vs. 16.7%). In mixed-effects regression analyses accounting for age, sex, and comorbid conditions, an increase in a patient's neighborhood SVI by 0.25 (1 quartile) was associated with greater likelihood of mechanical ventilation (increase of 2.1 percentage points), acute organ dysfunction (increase of 2.8 percentage points), and acute organ failure (increase of 2.8 percentage points) but was not associated with intensive care unit stay, mortality, or discharge disposition.

LIMITATION

Observational data focused on hospitalizations in a single state.

CONCLUSION

Hospitalized patients with COVID-19 from socially vulnerable neighborhoods presented with greater illness severity and required more intensive treatment, but once hospitalized they did not experience differences in hospital mortality or discharge disposition. Policies that target socially vulnerable neighborhoods and access to COVID-19 care may help ameliorate health disparities.

PRIMARY FUNDING SOURCE

Blue Cross Blue Shield of Michigan (BCBSM) and Blue Care Network as part of the BCBSM Value Partnerships Program, the Michigan Public Health Institute, and the Michigan Department of Health & Human Services.

COVID-19 vaccine hesitancy among marginalized populations in the U.S. and Canada: Protocol for a scoping review

Introduction

Despite the development of safe and highly efficacious COVID-19 vaccines, extensive barriers to vaccine deployment and uptake threaten the effectiveness of vaccines in controlling the pandemic. Notably, marginalization produces structural and social inequalities that render certain populations disproportionately vulnerable to COVID-19 incidence, morbidity, and mortality, and less likely to be vaccinated. The purpose of this scoping review is to provide a comprehensive overview of definitions/conceptualizations, elements, and determinants of COVID-19 vaccine hesitancy among marginalized populations in the U.S. and Canada.

Materials and methods

The proposed scoping review follows the framework outlined by Arksey and O’Malley, and further developed by the Joanna Briggs Institute. It will comply with reporting guidelines from the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR). The overall research question is: What are the definitions/conceptualizations and factors associated with vaccine hesitancy in the context of COVID-19 vaccines among adults from marginalized populations in the U.S. and Canada. Search strategies will be developed using controlled vocabulary and selected keywords, and customized for relevant databases, in collaboration with a research librarian. The results will be analyzed and synthesized quantitatively (i.e., frequencies) and qualitatively (i.e., thematic analysis) in relation to the research questions, guided by a revised WHO Vaccine Hesitancy Matrix.

Discussion

This scoping review will contribute to honing and advancing the conceptualization of COVID-19 vaccine hesitancy and broader elements and determinants of underutilization of COVID-19 vaccination among marginalized populations, identify evidence gaps, and support recommendations for research and practice moving forward.

How to Pay Primary Care Physicians for SARS-CoV-2 Vaccinations: An analysis of 43 EU and OECD Countries

Vaccinations are crucial to fighting SARS-CoV-2, and high coverage rates can in most countries probably only be achieved with the involvement of primary care physicians (PCPs). We aimed to explore how SARS-CoV-2 vaccination payment schemes in 43 countries differ with regard to the (i) type of payment scheme, (ii) amount paid, (iii) degree of bundling, and (iv) use of pay-for-performance elements.

We collected information on payments and health system characteristics, such as PCP income and employment status, in all EU and OECD countries over time. We regressed the payment amount on the income of PCPs for countries with activity-dependent schemes using a linear regression (OLS), and we interpreted the residuals of this regression as a vaccination payment index.

The majority of countries (30/43) had chosen payment schemes that reward PCPs for the activity they perform. Seventeen countries paid less per vaccination than the income-adjusted average, whereas 13 countries paid more. Twelve countries used pay-for-performance elements.

COVID-19 Vaccination Dynamics in the US: Coverage Velocity and Carrying Capacity Based on Socio-demographic Vulnerability Indices in California

Coronavirus disease 2019 (COVID-19) disparities among vulnerable populations are of paramount concern that extend to vaccine administration. With recent uptick in infection rates, dominance of the delta variant, and authorization of a third booster shot, understanding the population-level vaccine coverage dynamics and underlying sociodemographic factors is critical for achieving equity in public health outcomes. This study aimed to characterize the scope of vaccine inequity in California counties through modeling the trends of vaccination using the Social Vulnerability Index (SVI). Overall SVI, its four themes, and 9228 data points of daily vaccination numbers from December 15, 2020, to May 23, 2021, across all 58 California counties were used to model the growth velocity and anticipated maximum proportion of population vaccinated, defined as having received at least one dose of vaccine. Based on the overall SVI, the vaccination coverage velocity was lower in counties in the high vulnerability category (v = 0.0346, 95% CI 0.0334, 0.0358) compared to moderate (v = 0.0396, 95% CI 0.0385, 0.0408) and low (v = 0.0414, 95% CI 0.0403, 0.0425) vulnerability categories. SVI Theme 3 (minority status and language) yielded the largest disparity in coverage velocity between low and high-vulnerable counties (v = 0.0423 versus v = 0.035, P < 0.001). Based on the current trajectory, while counties in low-vulnerability category of overall SVI are estimated to achieve a higher proportion of vaccinated individuals, our models yielded a higher asymptotic maximum for highly vulnerable counties of Theme 3 (K = 0.544, 95% CI 0.527, 0.561) compared to low-vulnerability counterparts (K = 0.441, 95% CI 0.432, 0.450). The largest disparity in asymptotic proportion vaccinated between the low and high-vulnerability categories was observed in Theme 2 describing the household composition and disability (K = 0.602, 95% CI 0.592, 0.612; versus K = 0.425, 95% CI 0.413, 0.436). Overall, the large initial disparities in vaccination rates by SVI status attenuated over time, particularly based on Theme 3 status which yielded a large decrease in cumulative vaccination rate ratio of low to high-vulnerability categories from 1.42 to 0.95 (P = 0.002). This study provides insight into the problem of COVID-19 vaccine disparity across California which can help promote equity during the current pandemic and guide the allocation of future vaccines such as COVID-19 booster shots.

Cardiovascular risk factors and outcomes in COVID-19: A hospital-based study in India

BACKGROUND & OBJECTIVES

Presence of cardiovascular (CV) risk factors enhance adverse outcomes in COVID-19. To determine association of risk factors with clinical outcomes in India we performed a study.

METHODS

Successive virologically confirmed adult patients of COVID-19 at a government hospital were recruited at admission and data on clinical presentation and in-hospital outcomes were obtained. The cohort was classified according to age, sex, hypertension, diabetes and tobacco use. In-hospital death was the primary outcome. Logistic regression was performed to compared outcomes in different groups.

RESULTS

From April to September 2020 we recruited 4645 (men 3386, women 1259) out of 5103 virologically confirmed COVID-19 patients (91.0%). Mean age was 46±18y, hypertension was in 17.8%, diabetes in 16.6% and any tobacco-use in 29.5%. Duration of hospital stay was 6.8±3.7 days, supplemental oxygen was in 18.4%, non-invasive ventilation in 7.1%, mechanical ventilation in 3.6% and 7.3% died. Unadjusted and age-sex adjusted odds ratio(OR) and 95% confidence intervals(CI) for in-hospital mortality, respectively, were: age ≥60y vs <40y, OR 8.47(95% CI 5.87-12.21) and 8.49(5.88-12.25), age 40-59y vs <40y 3.69(2.53-5.38) and 3.66(2.50-5.33), men vs women 1.88(1.41-2.51) and 1.26(0.91-1.48); hypertension 2.22(1.74-2.83) and 1.32(1.02-1.70), diabetes 1.88(1.46-2.43) and 1.16(0.89-1.52); and tobacco 1.29(1.02-1.63) and 1.28(1.00-1.63). Need for invasive and non-invasive ventilation was greater among patients in age-groups 40-49 and ≥60y and hypertension. Multivariate adjustment for social factors, clinical features and biochemical tests attenuated significance of all risk factors.

CONCLUSION

Cardiovascular risk factors, age, male sex, hypertension, diabetes and tobacco-use, are associated with greater risk of in-hospital death among COVID-19 patients.

A sustainable-resilience healthcare network for handling COVID-19 pandemic

In this paper, a new production, allocation, location, inventory holding, distribution, and flow problems for a new sustainable-resilient health care network related to the COVID-19 pandemic under uncertainty is developed that also integrated sustainability aspects and resiliency concepts. Then, a multi-period, multi-product, multi-objective, and multi-echelon mixed-integer linear programming model for the current network is formulated and designed. Formulating a new MILP model to design a sustainable-resilience healthcare network during the COVID-19 pandemic and developing three hybrid meta-heuristic algorithms are among the most important contributions of this research. In order to estimate the values of the required demand for medicines, the simulation approach is employed. To cope with uncertain parameters, stochastic chance-constraint programming is proposed. This paper also proposed three meta-heuristic methods including Multi-Objective Teaching-learning-based optimization (TLBO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) to find Pareto solutions. Since heuristic approaches are sensitive to input parameters, the Taguchi approach is suggested to control and tune the parameters. A comparison is performed by using eight assessment metrics to validate the quality of the obtained Pareto frontier by the heuristic methods on the experiment problems. To validate the current model, a set of sensitivity analysis on important parameters and a real case study in the United States are provided. Based on the empirical experimental results, computational time and eight assessment metrics proposed methodology seems to work well for the considered problems. The results show that by raising the transportation costs, the total cost and the environmental impacts of sustainability increased steadily and the trend of the social responsibility of staff rose gradually between - 20 and 0%, but, dropped suddenly from 0 to + 20%. Also in terms of the on-resiliency of the proposed network, the trends climbed slightly and steadily. Applications of this paper can be useful for hospitals, pharmacies, distributors, medicine manufacturers and the Ministry of Health.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s10479-021-04238-2.

Neighborhood Socioeconomic Disadvantage Associated With Increased 90-Day Mortality Following Radical Cystectomy

OBJECTIVE

To examine relationships between neighborhood socioeconomic disadvantage and outcomes following radical cystectomy (RC).

MATERIALS AND METHODS

A retrospective single institution study of consecutive RCs performed for bladder cancer between 2011 and 2019. Major complications, mortality and survival outcomes were compared using Cochran-Armitage or Kruskal-Wallis tests. Cox proportional hazards models were used for time-to-event analyses.

RESULTS

A total of 906 patients were included in analysis. Overall 90-day mortality was 2.98% (27/906). Ninety-day mortality rates observed in the least (first) and most (fourth) disadvantaged ADI quartiles were 0% (0/115) and 6.5% (12/185), respectively. Patients from the fourth quartile demonstrated worse overall survival and recurrence free survival than those in the first quartile. ADI quartile was positively associated with muscle invasive (P = .0006) and node positive (P = .042) disease. ADI percentile was an independent predictor for 90-day mortality (adjusted OR: 1.022, CI: 1.004-1.04, P = .015).

CONCLUSION

Higher rates of mortality and worse oncologic outcomes were observed for patients residing in the most disadvantaged quartile. ADI was associated with higher likelihood of 90-day mortality and may therefore be useful in patient counseling, risk stratification, and post-discharge management.