Racial/Ethnic Inequity in Transit-Based Spatial Accessibility to COVID-19 Vaccination Sites

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.

A Driver in Health Outcomes: Developing Discrete Categories of Transportation Insecurity

Research suggests that transportation is an important social determinant of health, because the ability to get around is consequential for accessing health care and nutritious food and for making social connections. We used an inductive mixed-methods approach and a quantitative k-means clustering approach to identify 5 categories of transportation insecurity using the validated 16-item Transportation Security Index. The resulting 5-category measure distinguished among respondents with qualitatively different experiences of transportation insecurity. Analyzing data from 2018 that were representative of the US adult population aged 25 years or older, we demonstrated a nonparametric association between transportation insecurity and 2 different health measures (self-rated health and depressive symptoms). There was a threshold relationship between self-rated health and any level of transportation insecurity. High transportation insecurity had a very strong relationship with depressive symptoms. The categorical Transportation Security Index will be useful for clinicians who wish to screen for transportation-related barriers to health care. It will also facilitate research investigating the influence of transportation insecurity on health outcomes and provide the basis for interventions designed to address health disparities.

Disparities in Travel-Related Barriers to Accessing Health Care From the 2017 National Household Travel Survey

Importance

Geographic access, including mode of transportation, to health care facilities remains understudied.

Objective

To identify sociodemographic factors associated with public vs private transportation use to access health care and identify the respondent, trip, and community factors associated with longer distance and time traveled for health care visits.

Design, Setting, and Participants

This cross-sectional study used data from the 2017 National Household Travel Survey, including 16 760 trips or a nationally weighted estimate of 5 550 527 364 trips to seek care in the United States. Households that completed the recruitment and retrieval survey for all members aged 5 years and older were included. Data were analyzed between June and August 2022.

Exposures

Mode of transportation (private vs public transportation) used to seek care.

Main Outcomes and Measures

Survey-weighted multivariable logistic regression models were used to identify factors associated with public vs private transportation and self-reported distance and travel time. Then, for each income category, an interaction term of race and ethnicity with type of transportation was used to estimate the specific increase in travel burden associated with using public transportation compared a private vehicle for each race category.

Results

The sample included 12 092 households and 15 063 respondents (8500 respondents [56.4%] aged 51-75 years; 8930 [59.3%] females) who had trips for medical care, of whom 1028 respondents (6.9%) were Hispanic, 1164 respondents (7.8%) were non-Hispanic Black, and 11 957 respondents (79.7%) were non-Hispanic White. Factors associated with public transportation use included non-Hispanic Black race (compared with non-Hispanic White: adjusted odds ratio [aOR], 3.54 [95% CI, 1.90-6.61]; P < .001) and household income less than $25 000 (compared with ≥$100 000: aOR, 7.16 [95% CI, 3.50-14.68]; P < .001). The additional travel time associated with use of public transportation compared with private vehicle use varied by race and household income, with non-Hispanic Black respondents with income of $25 000 to $49 999 experiencing higher burden associated with public transportation (mean difference, 81.9 [95% CI, 48.5-115.3] minutes) than non-Hispanic White respondents with similar income (mean difference, 25.5 [95% CI, 17.5-33.5] minutes; P < .001).

Conclusions and Relevance

These findings suggest that certain racial, ethnic, and socioeconomically disadvantaged populations rely on public transportation to seek health care and that reducing delays associated with public transportation could improve care for these patients.

Understanding the spatial heterogeneity of COVID-19 vaccination uptake in England

BACKGROUND

Mass vaccination has been a key strategy in effectively containing global COVID-19 pandemic that posed unprecedented social and economic challenges to many countries. However, vaccination rates vary across space and socio-economic factors, and are likely to depend on the accessibility to vaccination services, which is under-researched in literature. This study aims to empirically identify the spatially heterogeneous relationship between COVID-19 vaccination rates and socio-economic factors in England.

METHODS

We investigated the percentage of over-18 fully vaccinated people at the small-area level across England up to 18 November 2021. We used multiscale geographically weighted regression (MGWR) to model the spatially heterogeneous relationship between vaccination rates and socio-economic determinants, including ethnic, age, economic, and accessibility factors.

RESULTS

This study indicates that the selected MGWR model can explain 83.2% of the total variance of vaccination rates. The variables exhibiting a positive association with vaccination rates in most areas include proportion of population over 40, car ownership, average household income, and spatial accessibility to vaccination. In contrast, population under 40, less deprived population, and black or mixed ethnicity are negatively associated with the vaccination rates.

CONCLUSIONS

Our findings indicate the importance of improving the spatial accessibility to vaccinations in developing regions and among specific population groups in order to promote COVID-19 vaccination.

Assessing the spatial distribution of and inequality in 15-minute PCR test site accessibility in Beijing and Guangzhou, China

China has been planning to construct SARS-CoV-2 antigen testing sites within a 15-min walk in most major cities to timely identify asymptomatic cases and stop the transmission of COVID-19. However, little is known about the spatial distribution of 15-min accessibility to PCR test sites. In this study, we analyze the spatial distribution of and inequality in 15-min accessibility to PCR test sites in two major Chinese cities (Beijing and Guangzhou) based on the cumulative-opportunity model. The results indicate that the current distribution of 15-min accessibility to PCR test sites is satisfactory when normal commuting is not disrupted. However, disruptions of normal commuting (e.g., due to work-from-home restrictions) can negatively influence 15-min accessibility to PCR test sites and increase its inequality. Our study provides policymakers with up-to-date knowledge about the spatial distribution of 15-min accessibility to PCR test sites, identifies the disadvantaged neighborhoods in terms of test site accessibility, and highlights the changes in accessibility and inequality because of travel disruptions.

Spatial accessibility modeling to healthcare facilities in the case of health shocks of Midnapore municipality, India

This research aims to identify the accessibility of the entire population, especially the slum population to existing healthcare facilities (HCF) as well as the slum neighborhoods having low geographic accessibility, and finally, to provide an analytical model for the people living in areas that are outside the coverage range of existing healthcare facilities (HCF) across the study area. Spatial data has been collected and used based on the road network, elevation, location of HCF, municipal boundary, slum point, and satellite images from various sources. Also, non-spatial data such as socioeconomic variables are collected from questionnaires survey within a particular period. The spatial analysis tool like as near, network analysis, and predictive analysis in the ArcGIS platform was used to examine geographic accessibility. The results of the spatial analysis show that the distribution of public healthcare facility centers in the study area has not been uniformly distributed. Across 84% of areas in the study area have sound spatial accessibility with traveling time coverage is about 12 min. However, 16% of areas have a traveling time of 12 to 30 min under low accessibility with existing slum neighborhoods. Therefore, the low spatial accessibility areas are demanding new healthcare facilities in the study area. The Analytical Hierarchy Process (AHP) is employed to find the most optimal and efficient locational suitability for building new healthcare facility centers. The finding of AHP analysis for site suitability of healthcare facilities revealed five major classes as most suitable (2%), suitable (5%), moderate (35%), poor (54%), and very poor (4%) in the study area. Moreover, the realistic framework of this study helps to measure geographic accessibility and suitability in any geographical area.

Syndemic aspects between COVID-19 pandemic and social inequalities

Although the coronavirus disease 2019 (COVID-19) pandemic has reached all over the world population, it has demonstrated a heterogeneous impact on different populations. The most vulnerable communities which coexist daily with the social inequalities like low access to hygiene and personal protection products, crowded residences, and higher levels of chronic diseases have a higher risk of contact and the spread of infection, beyond unfavorable clinical outcomes. The elevation of the risk of infection exposure can be related to gender due to the presence of a larger contingent of women in essential services, as well as frontline and cleaning professionals who regardless of gender have the greatest exposure to the virus. Such exposures can contribute to the development of fear of contaminating themselves or their family members associated also with the work stress, both of which are related to the emergence of mental disturbances in these populations. Furthermore, conditions of unsanitary living and low socioeconomic status, populations at war, pre-existing social barriers, and ethnicity have contributed to more impact of the pandemic both in the exposure to the virus and access to health services, COVID-19 management, and management of other pathologies. At the same time, factors such as the closing of non-essential services, the loss of jobs, and the increase in household spending aggravated the social vulnerabilities and impacted the family economy. Lastly, the COVID-19 pandemic contributed still more to the impact on women's health since it propitiated a favorable environment for increasing domestic violence rates, through the segregation of women from social life, and increasing the time of the victims with their aggressors.