Victims of resilience: an evaluation of social vulnerability’s applicability to disaster justice

Background U.S. vaccination rates fall short, with social vulnerabilities hindering access to preventive care. The influence of social determinants on vaccine uptake is a critical public health concern. This study explored the connection between the social vulnerability index (SVI), race, and vaccination rates for Influenza, SARS-CoV2, and RSV.Figure 1:Geospatial Distribution of Social Vulnerability Index and Vaccination Rates for Influenza, SARS-CoV-2, and RSV across Ohio Census Tracts with Patients to the University Hospital Healthcare Network. Geospatial representation of A) Public Social Vulnerability Index (SVI) for Ohio census tracts in 2020, B) Percentage of influenza vaccination, C) Percentage of SARS-CoV-2 vaccination, and D) Percentage of RSV vaccination for individuals aged 60 years and above. Figures B, C, and D show census tracts with a minimum of 10 patients presenting with mild to moderate respiratory infections to the University Hospital Healthcare network. The color scale for SVI ranges from 0 to 1, with the darkest red indicating the most vulnerable (SVI = 1) and the brightest cyan representing the least vulnerable (SVI = 0). The color scale for vaccination percentages spans from 0 to 100, with the darkest red denoting 0% vaccinated and the brightest cyan signifying 100% vaccinated. Methods We analyzed data from patients with acute respiratory infections treated at University Hospitals of Cleveland from October 2023 to April 2024. Patient demographics and vaccination statuses were collected from health records and matched with SVI census tract-level public data, which was geocoded and segmented into quartiles. We employed the Kruskal-Wallis and Pearson's Chi-squared tests for statistical analysis, and multivariate logistic regression adjusted for age and sex to assess vaccination odds. Results were depicted using geospatial methods to show the distribution of vaccinations and SVI across Ohio.Figure 2:Vaccinations Rates across race and social vulnerability index quantiles A comparison of vaccination rates for A) influenza, B) SARS-CoV-2, and C) RSV between White and Black populations across 10 quantiles of the Social Vulnerability Index (SVI). The SVI quantiles are represented on the x-axis, range from 0 to 1, with quantile 1 (SVI ≤ 0.2) representing the least vulnerable population and quantile 10 (SVI ≥ 0.8) representing the most vulnerable population. The y-axis shows the vaccination rates for each respective quantile. The color scheme used in the figure shows the White population in blue and the Black population in red. The summary statistics provide insights into the disparities in vaccination rates between White and Black individuals across varying levels of social vulnerability. Results The study analyzed a diverse population of 341,029 individuals, with 60% female and 38% male participants, and primarily consisted of white individuals (81%). Black individuals made up 14% of the population and were disproportionately represented in the highest vulnerability quartile (Q4) at 37%, which was significantly higher than the 3.2% in the lowest quartile (Q1). As the SVI quartile increased, vaccination rates decreased, particularly among Black individuals. Additionally, emergency visits for ARIs increased, while primary care visits decreased with higher SVI quartiles. The likelihood of vaccination decreased as the SVI quartile increased, especially among the Black group. The odds of receiving a flu vaccine were lower for Black individuals compared to White individuals in all SVI quartiles, with the greatest disparity in SVI Q5. Similarly, the odds of receiving the SARS-CoV-2 vaccine and the RSV vaccine were also lower for Black individuals compared to White individuals in all SVI quartiles. Detailed results are presented in the associated tables and figures.Table 1:Study Population Characteristics Across Social Vulnerability Index Quartiles Conclusion Socioeconomic vulnerability and race impact vaccination behaviors, emphasizing the need for tailored interventions to reduce disparities in vaccination rates among diverse populations.Table 2:Multivariate associations between Social Vulnerability Index (SVI) and Vaccination within White and Black Race Population Multivariate logistic regression models were used to evaluate the combined association between the SVI and race with the likelihood of vaccination for A) Influenza, B) SARS-CoV-2, and C) RSV. The models were adjusted for age and gender. The reference group for the combined race-SVI predictor was White individuals in the least vulnerable SVI quintile (Q1). Odds ratios, 95% confidence intervals, and p-values are presented for each race-SVI combination. Disclosures Elie Saade, MD, MPH, FIDSA, Janssen Global Services: Advisor/Consultant|Janssen Research and Development: Advisor/Consultant

Neighborhood-level Social Vulnerability and Prevalence of Cardiovascular Risk Factors and Coronary Heart Disease

Background The COVID-19 burden disproportionately affects communities with lower socioeconomic status and high social vulnerability, as well as minority racial groups. Disparities have also been described in nirmatrelvir/ritonavir (Paxlovid) prescription rates across socioeconomic strata. Differences in nirmatrelvir-ritonavir dispensing rates between SVI quartile groups from March 2022 – February 2023 Methods We performed an ecological analysis of associations between CDC social vulnerability index (SVI) and nirmatrelvir-ritonavir dispensing rates in Connecticut census tracts. SVI was categorized in four quartiles (low, low-medium, medium-high, and high). Nirmatrelvir/ritonavir dispensing locations were geocoded and dispensing rates per 1,000 population were calculated as the sum of courses dispensed per census tract during March 2022–February 2023. Independent-T tests were used to compare SVI in census tracts with and without medication dispensing sites. ANOVA with Tukey’s test was used to identify differences in dispensing rates by SVI quartile with paired t-test to identify significant differences before and after availability of the bivalent COVID-19 booster vaccine (March–August 2022 vs. September 2022–February 2023). Demographic and COVID-19 characteristics of census tracts with and without a nirmatrelvir/ritonavir dispensing site Results Mean SVI was higher in 367 census tracts with a dispensing site (mean 0.56) compared to 506 census tracts without a dispensing site (mean 0.45) (p < 0.01). Nirmatrelvir/ritonavir dispensing rates were lower in census tracts with high SVI (55.9 courses per 1000 people) compared to census tracts with low-medium SVI (93.1; difference -37.2 95% confidence interval (CI) [-68.5, -5.9]) and census tracts with medium-high SVI (96.6; difference -40.7, 95% CI [-69.9, -11.5]). Dispensing rates were higher after availability of the bivalent COVID-19 booster vaccine compared to before (p < 0.05), except in census tracts with high SVI where there was no statistically significant difference. Nirmatrelvir/ritonavir dispensing rates per 1,000 population by census tract SVI quartile before and after availability of the bivalent COVID-19 booster vaccine Conclusion Census tracts with high social vulnerability were less likely to have a dispensing site and had lower nirmatrelvir/ritonavir dispensing rates per 1,000 population. Observed differences in dispensing might signify inequities in healthcare access or medication prescribing. Findings highlight the importance of understanding and addressing barriers to accessing therapeutics in high vulnerability areas during public health emergencies. Disclosures Meghan Maloney, MPH, Pfizer Global R&D: Former employee, separated in 2009. I do have a retirement entitlement which I do not actively manage/no stock options. PGRD offers periodic buy outs

Purpose: To observe the geographic distribution of breast cancer (BC) mortality in Maryland by differences in neighborhood-level social determinants of health Background: Cancer surveillance efforts indicate that BC mortality is unevenly distributed geographically in Maryland; however, it is unknown how area-level socioenvironmental disadvantages might be driving these neighborhood-level disparities. Methods: Utilizing data from the Maryland Cancer Registry (MPCR), we identified women aged 18+ diagnosed with first primary, invasive BC between 2000-2019. We used census tract-level Social Vulnerability Index (SVI) as a proxy measure for neighborhood-level built and social environments. We calculated the 20-year average SVI percentile ranking and categorized each census tract as having low (least disadvantaged), low-medium, medium-high, or high (most disadvantaged) SVI. We computed age-adjusted (<50, 50+) standardized mortality ratios (SMRs) for each SVI level using the 2000 standard female population and BC-specific referent mortality rates for Maryland from 2018-2022 (age <50: 4.4 deaths/100k; age 50+ 60.8 deaths/100k). We used spatial epidemiology methods to estimate age-adjusted SMRs by census tracts among women of all ages (referent mortality rate: 20 deaths/100k). We mapped this data to visualize the geographic distribution of SVI and BC mortality. Results: Our study population included 79,145 women (n=17,027 [2.5%] aged <50; n=62,118 [78.5%] aged 50+), of which 13,005 (16%) died from their BC diagnosis. We observed the largest differences in SMRs by age at diagnosis. Across all SVI categories, BC mortality among women diagnosed at ages 50+ was higher than expected relative to older women in the general female population (SMR range: 19.1-22.1). Results were similar for women diagnosed at ages <50 (SMR range: 48.2-53.3). Census tracts with low-medium/medium-high SVI had higher SMRs (low-med: 50.2, med-high: 53.3) than low/high SVI areas. After calculating the SMRs by census tract for all ages, we observed that census tracts in the Eastern Shore and western Maryland showed a strong spatial correlation between higher SVI and higher SMRs. Similarly, most of the Capital region and central Maryland experienced low SVI and correspondingly lower SMRs, but there was considerable spatial variation in the distribution of SVI and BC mortality around Baltimore City/County and Greater Washington region. Conclusion: The uneven geographic distribution of BC mortality in Maryland may be due to the underlying heterogenic spatial distribution social vulnerability. Younger women diagnosed in census tracts with low-medium or medium-high SVI disproportionately experienced the highest SMRs. Our findings suggest a differential mortality impact of neighborhood-level conditions and socioenvironmental factors among younger vs. older women. Citation Format: Katherine L. Ho, Kassandra Alcaraz, Avonne Connor, Michael Desjardins. Exploring the impact of neighborhood-level conditions: Geographic disparities in breast cancer mortality in Maryland, 2000-2019 [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 4950.

Social Vulnerability Is a Clinically Important Predictor of Outcomes after Allogeneic Hematopoietic Cell Transplantation

Background: HbA1c has been associated with COVID-poor outcomes in diabetic and non-diabetic populations, while patients living in census tracts with high levels of social vulnerability [measured using the CDC’s Social Vulnerability Index (SVI) ] have experienced poorer outcomes. Objective: To examine associations between HbA1c, area level social vulnerability and poor COVID outcomes in patients who tested positive for COVID and were captured in the electronic medical record (EMR) at a large academic institution in the Southeastern United States. Methods: HbA1c and SVI, collected up to 3 years prior to a positive COVID test, were extracted from the EMR. HbA1c and SVI were compared by poor outcome status [hospitalization, intensive care unit (ICU) admission, and mortality]. Bayesian logistic regression was used to examine associations between HbA1c [≤5.7%; 5.7%-<6.5%; and ≥6.5%], SVI [living in high SVI census tract vs low SVI tract] and each COVID outcome separately. Multivariable models were adjusted for sex, age, race, body mass index and diabetes status. Results presented as odds ratios (OR) and 95% confidence intervals (95% CI) . Results: N=3,7patients were identified [mean age: 54 years (SD 16.3) , 60% female, 47% Black]. Patients with HbA1c ≥ 6.5% and those living in a high SVI census tract were more likely to experience a poor COVID outcome (p’s<0.0001) . In multivariable models, patients with HbA1c ≥ 6.5% had higher odds of hospitalization (OR 1.79, 95% CI 1.44-2.22) ; ICU admission (OR 2.13, 95% CI 1.78-2.55) ; and mortality (OR 1.60, 95% CI 1.12-2.28) . Patients living in a high SVI census tract had higher odds of hospitalization (OR 2.47, 95% CI 1.94-3.15) ; ICU admission (OR 2.58, 95% CI 2.12-3.14) ; and mortality (OR 2.07, 95% CI 1.39-3.09) . Conclusion: HbA1c ≥6.5% and living in a census tract with high social vulnerability were independently associated with poor COVID-outcomes. Findings highlight the need to assess HbA1c and area level social determinants in the context of COVID. Disclosure C.R.Howell: None. L.Zhang: None. S.Williams: None. N.Yi: None. W.Garvey: Other Relationship; Boehringer Ingelheim International GmbH, Eli Lilly and Company, Epitomee, JAZZ Pharmaceuticals, Novo Nordisk, Novo Nordisk, Pfizer Inc., Pfizer Inc. A.Cherrington: Consultant; Bayer AG, Other Relationship; Novo Nordisk. Funding This work was supported by funding from the National Institute on Minority Health and Health Disparities (U54MD008176) .

14 Living in an area with high social vulnerability during pregnancy is associated with preterm birth

Social Vulnerability Is Associated with Emergency Department Dependency in Pediatric Sickle Cell Disease Patients

The Impact of Social Vulnerability Index on Survival Following ASCT for Multiple Myeloma

The Effects of Social Vulnerability on the Prognosis and Outcomes of Hodgkin's Lymphoma in Adults across the United States

Preterm birth among pregnant women living in areas with high social vulnerability

Purpose The social vulnerability index (SVI) is a community-level scoring system based on US Census tract, designed to assess vulnerability during disasters. Here, we evaluate the relationship of CDC-defined SVI with office visit compliance in an urban oculoplastic surgery clinic. Methods In this single-center retrospective study, age, gender, race/ethnicity, electronic accessibility status, residential address, and number of completed and no-show visits were collected of individuals treated at an oculoplastic clinic from Sept 2020 to Sept 2023. The 2020 Census Tract SVI scores were obtained using the residential addresses for the overall SVI, four thematic SVIs, and 16 social factors’ SVIs. A greater SVI (range 0–1) indicates higher social vulnerability. Categorical, numerical, and logistic regression statistical tests were performed to determine factors predictive of unreliable visit attendance, defined as failure to attend >25% of scheduled appointments. Results The final analysis included 3,287 patients with a mean age of 52 ± 21 years, 61% of whom were female. In the study period, 787 patients (24%) were found to have unreliable attendance at their scheduled appointments. Having an overall SVI of 0.75 or higher was associated with an increased likelihood of unreliable visit attendance (OR 2.7, 95% CI 2.1–3.5, p < 0.001). Additionally, a thematic SVI of 0.75 or higher regarding racial and ethnic minority status resulted in an increased likelihood of unreliable attendance (OR 2.1, 95% CI 1.2–3.4, p = 0.008). Conclusions This is the first study showing that living in communities with high SVI scores is associated with poor oculoplastic surgery office visit attendance.

#1402660: Association of Social Vulnerability Index Themes and Pre-Diabetes in Chicago Neighborhoods

Geospatial Analysis of Social Vulnerability, Race, and Firearm Violence in Chicago

Background: Hurricane Sandy caused widespread health and economic impacts in the greater New York City (NYC) area. While these impacts may vary across different communities, analyses understanding and identifying community-level vulnerability are lacking. We compared resilience measures and Hurricane Sandy flooding data to quantify the extent of community-level disparities. Methods: The 2010 Social Vulnerability Index (SVI) was downloaded from the Centers for Disease Control and Prevention to provide a resilience measure at the census tract level across NYC, Long Island and Westchester Counties. The overall SVI captures four dimensions: Socioeconomic, Household Composition, Minority Status/Language, and Housing/Transportation, resulting in a summed percentile ranking for each census tract, where a higher score indicates a greater social vulnerability. Flooding for the same census tracts were obtained from the Federal Emergency Management Agency Modeling Task Force Hurricane Sandy Impact Analysis. Results: 771 census tracts (26.3%) experienced flooding due to Hurricane Sandy, and 533 (69%) of these tract were located in NYC. The overall SVI index (mean±SD) was higher (7.70 ± 1.94) in NYC tracts than non-NYC tracts (5.32 ± 1.80), and higher in tracts experiencing flooding in NYC (7.2 ± 2.10) compared to non-NYC tracts that experienced flooding (5.05 ± 1.74). In NYC, 23.0% of census tracts were &gt;75th percentile of both overall SVI and mean flood height, while 30.6% of tracts met this criteria in non-NYC. Conclusion: The social vulnerability and resilience of communities affected by Hurricane Sandy differed across NYC and Long Island, with a clear division among NYC and non-NYC study areas, and again among flooded areas in NYC and flooded areas outside NYC. There exists an urban population with high SVI and flood exposure at the highest risk, and actions must be taken to reduce disparities in social vulnerability and bolster community-level resilience.