Spatial Patterns of COVID-19 Vaccination Coverage by Social Vulnerability Index and Designated COVID-19 Vaccine Sites in Texas

Towards optimization of community vulnerability indices for COVID-19 prevalence

BACKGROUND

The Centers for Disease Control and Prevention (CDC)'s social vulnerability index (SVI) for exploring social and health disparities in the United States may not be suitable for assessing COVID-19 risk in specific communities and subpopulations. This study aims to develop the community vulnerability index (CVI) optimized for demographic-specific COVID-19 prevalence at the census tract level and apply it to Clark County, Nevada, which includes the vibrant Las Vegas metropolitan area.

METHODS

We constructed the CVI using fifteen social condition variables from the CDC's SVI along with eight additional community variables measuring inactive commuting, park deprivation, retail density, low-income homeowner or renter severe housing cost burden, housing inadequacy, segregation, and population density. Deploying weighted quantile sum (WQS) regression through a bootstrapping technique, the CVI was optimized by linking the 23 community variables to cumulative confirmed cases of COVID-19 from January 2020 to November 2021, excluding reinfections. This study resulted in whole-population and 13 demographic-specific CVIs representative of various age (0-4, 5-17, 18-24, 25-49, 50-64, and 65 +), race (White, Black, Hispanic, Asian/Pacific Islander, and others), and sex (male and female) groups.

RESULTS

All WQS regressions revealed significant associations between the CVIs and corresponding COVID-19 prevalence. The most influential variables to the whole-population CVI included minority status, park deprivation, aged 17 and younger, inactive commuting, and housing inadequacy, which also contributed significantly to several CVIs corresponding to COVID-19 prevalence in subpopulations. Other influential community variables to the CVIs in general varied by subpopulation. The distributions of the subpopulation CVIs showed different levels of spatial disparities, with the largest disparities observed in female, White, and age 50-64 groups.

CONCLUSIONS

This study established a practical approach to optimize CVI for assessing COVID-19 risk. The incorporation of additional variables, specificity for subpopulations, and adaptability through the WQS regression collectively contribute to its value in informing evidence-based policy decisions and guiding targeted interventions to mitigate the impact of COVID-19 on vulnerable communities.

Modern approaches to predicting vaccine hesitancy: A scoping review

Introduction

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

Methods

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

Results

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

Conclusion

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

A Study Examining the Impact of County-Level Demographic, Socioeconomic, and Political Affiliation Characteristics on COVID-19 Vaccination Patterns in Indiana

The COVID-19 vaccination campaign resulted in uneven vaccine uptake throughout the United States, particularly in rural areas, areas with socially and economically disadvantaged groups, and populations that exhibited vaccine hesitancy behaviors. This study examines how county-level sociodemographic and political affiliation characteristics differentially affected patterns of COVID-19 vaccinations in the state of Indiana every month in 2021. We linked county-level demographics from the 2016-2020 American Community Survey Five-Year Estimates and the Indiana Elections Results Database with county-level COVID-19 vaccination counts from the Indiana State Department of Health. We then created twelve monthly linear regression models to assess which variables were consistently being selected, based on the Akaike Information Criterion (AIC) and adjusted R-squared values. The vaccination models showed a positive association with proportions of Bachelor's degree-holding residents, of 40-59 year-old residents, proportions of Democratic-voting residents, and a negative association with uninsured and unemployed residents, persons living below the poverty line, residents without access to the Internet, and persons of Other Race. Overall, after April, the variables selected were consistent, with the model's high adjusted R2 values for COVID-19 cumulative vaccinations demonstrating that the county sociodemographic and political affiliation characteristics can explain most of the variation in vaccinations. Linking county-level sociodemographic and political affiliation characteristics with Indiana's COVID-19 vaccinations revealed inherent inequalities in vaccine coverage among different sociodemographic groups. Increased vaccine uptake could be improved in the future through targeted messaging, which provides culturally relevant advertising campaigns for groups less likely to receive a vaccine, and increasing access to vaccines for rural, under-resourced, and underserved populations.

Vaccine Uptake and Intentions: Insights from a Texas Survey on Factors Influencing COVID-19 Vaccination Decisions

The effectiveness of COVID-19 vaccines depends on widespread vaccine uptake. Employing a telephone-administered weighted survey with 19,502 participants, we examined the determinants of COVID-19 vaccine acceptance among adults in Texas. We used multiple regression analysis with LASSO-selected variables to identify factors associated with COVID-19 vaccine uptake and intentions to receive the vaccine among the unvaccinated. The prevalence of unvaccinated individuals (22%) was higher among those aged 18-39, males, White respondents, English speakers, uninsured individuals, those facing financial challenges, and individuals expressing no concern about contracting the illness. In a fully adjusted regression model, higher odds of being unvaccinated were observed among males (aOR 1.11), the uninsured (aOR 1.38), smokers (aOR 1.56), and those facing financial struggles (aOR 1.62). Conversely, Asians, Blacks, and Hispanics were less likely to be unvaccinated compared to Whites. Among the unvaccinated, factors associated with stronger intent to receive the vaccine included age (over 65 years), Black and Hispanic ethnicity, and perceived risk of infection. Hispanic individuals, the uninsured, those covered by public insurance, and those facing financial challenges were more likely to encounter barriers to vaccine receipt. These findings underscore the importance of devising tailored strategies, emphasizing nuanced approaches that account for demographic, socioeconomic, and attitudinal factors in vaccine distribution and public health interventions.

Investigating the Spatial Accessibility and Coverage of the Pediatric COVID-19 Vaccine: An Ecologic Study of Regional Health Data

The COVID-19 pandemic presented the unique challenge of having to deliver novel vaccines during a public health crisis. For pediatric patients, it was further complicated by the delayed timeline for authorizing the vaccine and the differences in dosing/products depending on the patient's age. This paper investigates the relationship between the spatial accessibility and uptake of the COVID-19 vaccine in King County, WA, USA. Public data for COVID-19 vaccine sites were used to calculate spatial accessibility using an enhanced two-step floating catchment area (E2SFCA) technique. Spatial regression analyses were performed to look at the relationship between spatial accessibility and ZIP-code-level vaccination rates. The relationships of these data with other socioeconomic and demographic variables were calculated as well. Higher rates of vaccine accessibility and vaccine coverage were found in adolescent (12- to 17-year-old) individuals relative to school-age (5- to 11-year-old) individuals. Vaccine accessibility was positively associated with coverage in both age groups in the univariable analysis. This relationship was affected by neighborhood educational attainment. This paper demonstrates how measures such as E2SFCA can be used to calculate the accessibility of the COVID-19 vaccine in a region and provides insight into some of the ecological factors that affect COVID-19 vaccination rates.

Factors Associated with COVID-19 Vaccine Uptake Among High School Students in a Large, Diverse Metropolitan Area

BACKGROUND

Because previous studies on adolescent COVID-19 attitudes focused on intent to get vaccinated, this study examined attitudinal factors and racial/ethnic differences associated with vaccine uptake.

METHODS

In a cross-sectional survey of a metropolitan high school district, students were asked about their COVID-19 attitudes, information sources, and whether they had been vaccinated. Logistic regression predicted vaccination status and adjusted odds ratios (aOR) controlled for race/ethnicity.

RESULTS

Being unvaccinated was associated with themes of distrust with concerns about vaccine newness (aOR: 0.10; 95% confidence intervals [CI]: 0.06-0.15), side effects (aOR: 0.22; 95% CI: 0.15-0.33), efficacy (aOR: 0.25; 95% CI: 0.17-0.38), distrust of vaccines (aOR: 0.16; 95% CI: 0.09-0.27), government oversight (aOR: 0.19; 95% CI: 0.13-0.30), and politicization (aOR: 0.60; 95% CI: 0.41-0.88). Vaccine uptake was influenced by official information sources, school closures, and vaccine availability. The majority of vaccinated and unvaccinated students trusted primary care professionals as a source for COVID-19 information, but their influence varied across race/ethnic groups.

CONCLUSIONS

Trust and distrust were the main themes of vaccinated and unvaccinated students, respectively. Incorporating trusted information sources (primary care professionals) in information dissemination efforts may improve vaccine uptake.

The Brazilian vaccine divide: How some municipalities were left behind in the Covid-19 vaccine coverage

This study aims to assess the progress of geographic, socioeconomic, and demographic disparities in Covid-19 vaccination coverage in Brazil over the first two years of the vaccination campaign. Data from the National Immunization Program Information System were used to estimate covid-19 vaccine coverage. Brazilian municipalities were divided into two groups based on their vaccine coverage for the booster dose. The first group comprised 20% of municipalities with the lowest coverage, while the second group (80% of municipalities) had higher coverage. The analysis was conducted separately for four age groups: 5-11, 12-17, 18-59, and 60+. Explanatory variables included socioeconomic and health services indicators. Crude and adjusted logistic regression models were used to estimate the probability of a municipality being among those with the worst vaccination coverage according to the categories of exploratory variables. Between January/2021 and December/2022, Brazil administered 448.2 million doses of the covid-19 vaccine. The booster vaccination coverage varied from 24.8% among adolescents to 79.7% among the elderly. The difference between the group with the highest and lowest coverage increased during the national vaccination campaign. Municipalities with lower education levels, higher proportion of Black population, higher Gini index, and worse health service indicators had a greater likelihood of having lower vaccination coverage. High and increasing levels of inequality in Covid-19 vaccination were observed in Brazil across all age groups during the vaccination campaign in 2021-2022.

Examining spatial variation for immunisation coverage in pregnant women: A nationwide and geospatial retrospective cohort study in Aotearoa New Zealand

BACKGROUND

Maternal influenza and pertussis immunisation is crucial for protecting mothers during pregnancy and their babies in the first weeks of life against severe disease. We examined geospatial variation in maternal immunisation coverage among pregnant women in Aotearoa New Zealand and its health equity implications.

METHOD

We constructed a retrospective cohort including all pregnant women who delivered between 01 January 2013 and 31 December 2020 using administrative health datasets. Our outcomes were receipt of influenza or pertussis vaccine in any one of three relevant national databases (e.g. National Immunisation Register, Proclaims, or Pharmaceutical collection) during the eligible pregnancy.

RESULTS

Data from our retrospective cohort study show significant regional variation in maternal immunisation coverage for both influenza and pertussis from 2013 to 2020. Maximal coverage was around 50% in the best performing regions, which means that half of the women who were pregnant (183,737 women) were not protected. In addition, we found significant spatio-temporal variation and clustering of immunisation coverage. Our findings are interactively available to explore here: https://geohealthlab.shinyapps.io/hapumama/ CONCLUSION: Our study is one of the first to examine spatial variation in maternal vaccination coverage in pregnant women at a national level over space and time. This provides powerful tools to measure the impact of interventions to improve coverage at national and regional levels, with specific reference to inequities between ethnic groups, likely applicable to similar settings internationally.

Incorporating resilience when assessing pandemic risk in the Arctic: a case study of Alaska

The discourse on vulnerability to COVID-19 or any other pandemic is about the susceptibility to the effects of disease outbreaks. Over time, vulnerability has been assessed through various indices calculated using a confluence of societal factors. However, categorising Arctic communities, without considering their socioeconomic, cultural and demographic uniqueness, into the high and low continuum of vulnerability using universal indicators will undoubtedly result in the underestimation of the communities' capacity to withstand and recover from pandemic exposure. By recognising vulnerability and resilience as two separate but interrelated dimensions, this study reviews the Arctic communities' ability to cope with pandemic risks. In particular, we have developed a pandemic vulnerability-resilience framework for Alaska to examine the potential community-level risks of COVID-19 or future pandemics. Based on the combined assessment of the vulnerability and resilience indices, we found that not all highly vulnerable census areas and boroughs had experienced COVID-19 epidemiological outcomes with similar severity. The more resilient a census area or borough is, the lower the cumulative death per 100 000 and case fatality ratio in that area. The insight that pandemic risks are the result of the interaction between vulnerability and resilience could help public officials and concerned parties to accurately identify the populations and communities at most risk or with the greatest need, which, in turn, helps in the efficient allocation of resources and services before, during and after a pandemic. A resilience-vulnerability-focused approach described in this paper can be applied to assess the potential effect of COVID-19 and similar future health crises in remote regions or regions with large Indigenous populations in other parts of the world.

COVID-19 vaccine coverage disparities in rural and farm children

BACKGROUND

The risks of severe outcomes associated with SARS-CoV-2 (COVID-19) are elevated in unvaccinated individuals. It remains crucial to understand patterns of COVID-19 vaccination, particularly in younger and remote populations where coverage often lags. This study examined disparities in COVID-19 vaccine coverage in farm children and adolescents.

METHODS

A cross-sectional analysis was conducted in patients of the Marshfield Clinic Health System (MCHS) in Wisconsin. The sample included children/adolescents age 5-17 years who were eligible for COVID-19 vaccine initiation for ≥ 90 days (as of September 30, 2022), stratified by those who lived vs did not live on a farm. Outcomes included COVID-19 vaccine initiation, series completion, and booster receipt. Multivariable regression was used to examine associations between COVID-19 vaccination and farm, as well as rural and non-rural, residence.

RESULTS

There were 47,104 individuals (5% farm residents) in the sample. Overall, 33% of participants initiated and 31% completed the COVID-19 vaccine series. After adjustment, farm residence was associated with significantly lower odds of COVID-19 vaccine initiation (aOR [95% CI] = 0.68 [0.61, 0.75], p < 0.001), series completion (aOR = 0.67 [0.60, 0.75], p < 0.001), and booster receipt (aOR = 0.73 [0.61, 0.88], p = 0.001). Secondary analyses found COVID-19 vaccine coverage was lowest in young children who lived on dairy farms.

CONCLUSIONS

COVID-19 vaccine coverage is low in north-central Wisconsin children and adolescents. Those who live on farms have significantly lower likelihood of COVID-19 vaccine initiation, series completion, and booster receipt compared to non-farm counterparts. Farm families are an underserved group and require more effective public health interventions designed to prevent COVID-19.

What Makes Urban Communities More Resilient to COVID-19? A Systematic Review of Current Evidence

It has been more than two years since the outbreak of the COVID-19 epidemic at the end of 2019. Many scholars have introduced the "resilience" concept into COVID-19 prevention and control to make up for the deficiencies in traditional community governance. This study analyzed the progress in research on social resilience, which is an important component of community resilience, focusing on the current literature on the impact of social resilience on COVID-19, and proposed a generalized dimension to integrated previous relevant literature. Then, VOSviewer was used to visualize and analyze the current progress of research on social resilience. The PRISMA method was used to collate studies on social resilience to the pandemic. The result showed that many current policies are effective in controlling COVID-19, but some key factors, such as vulnerable groups, social assistance, and socioeconomics, affect proper social functioning. Some scholars have proposed effective solutions to improve social resilience, such as establishing an assessment framework, identifying priority inoculation groups, and improving access to technology and cultural communication. Social resilience to COVID-19 can be enhanced by both external interventions and internal regulation. Social resilience requires these two aspects to be coordinated to strengthen community and urban pandemic resilience.