Vulnerability Index Research Articles

Early transition markers, opportunities, and limitations that define pathways into the labour market from adolescence to adulthood in South Africa

AbstractMotivationThe transition from adolescence to adulthood encompasses key social changes. NEET status (Not in Education, Employment or Training) during this period disrupts this transition and alters an adolescent's life course. This is of particular concern in South Africa, a middle‐income country with one of the world's highest rates of youth unemployment.PurposeThe pathway to becoming NEET emerges over time by accumulating risks in early life and adolescence. Early‐life adversities can increase the probability of events associated with becoming NEET. We aim to identify early‐life and adolescent predictors of events associated with becoming NEET, as well as predictors of NEET status itself.Methods and approachWe analyse four rounds of longitudinal data from a sample of 1,174 adolescents growing up in peri‐urban KwaZulu‐Natal, South Africa. Using a socioecological life‐course model, we create two overlapping analytic cohorts and two NEET vulnerability indices to evaluate whether risks for vulnerability in schooling (early outcomes) are similar to those affecting post‐schooling education and labour‐market outcomes (later outcomes). We use a linear probability model to analyse the relationship between the vulnerability indices and the range of risk factors in the socioecological life‐course model.FindingsA strong predictor of both NEET vulnerability indices includes reporting feeling hopeless about the future. Other significant predictors include behavioural factors (getting pregnant or impregnating someone during adolescence, and drinking alcohol before age 16), family structure (residing with one's biological mother in early adolescence was protective) and demographics (age).Policy implicationsBy deepening our understanding of how individual and contextual characteristics shape the transition into productive adulthood through a life‐course approach, we can identify possible early intervention points lost once young people become NEET.

Development of a Block-Scale Spatial Flood Vulnerability Index—Case Study: Morelia, Mexico

The study of urban floods is increasingly crucial due to their growing frequency and impact on densely populated areas, often characterized by inadequate drainage and located in flood-prone zones. The consequences extend beyond physical damage, significantly affecting economies and livelihoods, necessitating substantial economic resources for recovery and infrastructure rebuilding. Urban planning now must integrate flood risk management, emphasizing not only infrastructural resilience but also comprehensive policies that address environmental and social vulnerabilities to better prepare and protect urban environments against future flood risks. This study addresses the critical issue of urban flood vulnerability through a focused analysis of Morelia, a city known for its susceptibility to flooding due to its geographical and hydrological characteristics and accelerated urban growth. Employing a multifaceted approach that integrates hydrological, socio-economic, and land use data within a Geographic Information Systems (GIS) framework, the research develops a Spatial Flood Vulnerability Index (SFVI). This index is meticulously applied at the urban block level, offering a precise mapping of flood risks across the city. By correlating the SFVI results with historical flood data, the study identifies the most vulnerable areas in Morelia, which are primarily impacted due to their proximity to water bodies, economic density, and infrastructural settings. The methodology not only highlights immediate flood risks but also aids in strategic urban planning to enhance resilience against future flooding events. This paper contributes a novel approach to flood risk assessment, providing a replicable model for similarly affected cities worldwide, aiming to balance structural measures with strategic planning tailored to local needs.

ANALYSIS OF THE IMPACT OF NATURAL HAZARDS ON TOURISM ON THE LEFT BANK OF LAKE IZVORU MUNTELUI (NORTH-EASTERN ROMANIA)

One of the areas with great touristic potential in Romania’s mountains is Izvoru Muntelui Lake (Neamt county) from the western slopes of the Stânișoara Mountains in the Eastern Carpathians. The area is remarkably picturesque in terms of both the natural surroundings and history, including traditions, folklore, and ethnography. Nevertheless, the region is exposed to natural risk phenomena such as floods, landslides, crumbling, etc., which can affect different economic fields, including tourism. The present study aims to analyze the relationship between this zone's natural hazards and tourism activities and their impact. Our approach is based on quantitative and qualitative analysis, interview and questionnaire techniques, but also on literature review, field research, statistics, overlay and spatial mapping of data using GIS techniques and critical interpretation of results through mathematical statistics using Covariance Product of Deviations from the mean and the Bravais-Pearson linear correlation coefficient to measure the intensity of the interdependence between the degree of damage to the road infrastructure and the tourist infrastructure. The results show that the landslides significantly impact the public infrastructures between Poiana Teiului and Bicaz, heavily affecting the national road DN15. A total of 73 impact points were inventoried, representing sections of roads and road infrastructure elements affected by landslides. At the same time, the analysis of the responses to the questionnaire revealed that natural hazards, especially landslides and floods, are perceived as a threat by most tourism operators in the area. The classification of the vulnerability of tourism infrastructure into four categories (low, medium, high, and very high), based on susceptibility maps, has led to the determination of vulnerability to landslides, revealing the following findings: four accommodation units have a medium vulnerability index, two have a high vulnerability index, and one records a very high vulnerability index. It is highlighted that an accurate perception of natural hazards can contribute to increasing the awareness and preparedness of vulnerable people, thus increasing the resilience of present and future generations.

Receipt of respiratory vaccines among patients with heart failure in a multicenter health system registry.

Heart failure affects people of all ages and is a leading cause of death for both men and women in most racial and ethnic groups in the United States. Infections are common causes of hospitalizations in heart failure, with respiratory infections as the most frequent diagnosis. Vaccinations provide significant protection against preventable respiratory infections. Despite being an easily accessible intervention, prior studies suggest vaccines are underused in patients with heart failure. An observational study of 5089 adults with heart failure was conducted using data from an integrated, multicenter, academic health system in Southern California from 2019 to 2022. Logistic regression models were used to determine the rates of influenza, pneumococcal, and COVID-19 vaccination among a population of patients with heart failure (heart failure preserved ejection fraction [HFpEF], heart failure mildly reduced ejection fraction [HFmrEF], and heart failure reduced ejection fraction [HFrEF], and identify whether heart failure phenotype is associated with vaccination status. Vaccination rates varied between influenza, pneumococcal, and COVID-19 vaccines. Of the three respiratory vaccines, 58.0% of patients had received an influenza vaccine, 76.2% had received a pneumococcal vaccine, and 83.3% had received a COVID-19 vaccine. There were no sex-based differences by vaccination status. Differences were seen within age, race/ethnicity, insurance type, whether the patient was a member of an Accountable Care Organization (ACO), primary language, Social Vulnerability Index (SVI) score, clinician type, and number of comorbidities. Patients with HFpEF and HFmrEF had higher vaccination rates than HFrEF. In adjusted models, patients with HFrEF had lower odds of being vaccinated for influenza (aOR=0.75, 95% CI=0.66-0.86), pneumococcal (aOR=0.65, 95% CI=0.55-0.75), and COVID (aOR=0.74, 95% CI=0.62-0.89) compared to patients with HFpEF. Patients with HFrEF had the lowest levels of respiratory vaccination compared to other specified heart failure categories. Interventions are needed to increase vaccination education and offerings, especially to patients with HFrEF.

Decoding obsessive-compulsive disorder: Regional Vulnerability Index and its Association with Clinical Symptoms

Decoding obsessive-compulsive disorder: Regional Vulnerability Index and its Association with Clinical Symptoms

Development of Machine Learning Algorithms for Identifying Patients With Limited Health Literacy.

Limited health literacy (HL) leads to poor health outcomes, psychological stress, and misutilization of medical resources. Although interventions aimed at improving HL may be effective, identifying patients at risk of limited HL in the clinical workflow is challenging. With machine learning (ML) algorithms based on readily available data, healthcare professionals would be enabled to incorporate HL screening without the need for administering in-person HL screening tools. Develop ML algorithms to identify patients at risk for limited HL in spine patients. Between December 2021 and February 2023, consecutive English-speaking patients over the age of 18 and new to an urban academic outpatient spine clinic were approached for participation in a cross-sectional survey study. HL was assessed using the Newest Vital Sign and the scores were divided into limited (0-3) and adequate (4-6) HL. Additional patient characteristics were extracted through a sociodemographic survey and electronic health records. Subsequently, feature selection was performed by random forest algorithms with recursive feature selection and five ML models (stochastic gradient boosting, random forest, Bayes point machine, elastic-net penalized logistic regression, support vector machine) were developed to predict limited HL. Seven hundred and fifty-three patients were included for model development, of whom 259 (34.4%) had limited HL. Variables identified for predicting limited HL were age, Area Deprivation Index-national, Social Vulnerability Index, insurance category, Body Mass Index, race, college education, and employment status. The Elastic-Net Penalized Logistic Regression algorithm achieved the best performance with a c-statistic of 0.766, calibration slope/intercept of 1.044/-0.037, and Brier score of 0.179. Elastic-Net Penalized Logistic Regression had the best performance when compared with other ML algorithms with a c-statistic of 0.766, calibration slope/intercept of 1.044/-0.037, and a Brier score of 0.179. Over one-third of patients presenting to an outpatient spine center were found to have limited HL. While this algorithm is far from being used in clinical practice, ML algorithms offer a potential opportunity for identifying patients at risk for limited HL without administering in-person HL assessments. This could possibly enable screening and early intervention to mitigate the potential negative consequences of limited HL without taxing the existing clinical workflow.

770 Utilization of nasoalveolar molding stratified by social vulnerability index, race, and urbanicity

770 Utilization of nasoalveolar molding stratified by social vulnerability index, race, and urbanicity

Examining the Association Between Public Health Accreditation and COVID-19 Outcomes.

To examine the association between local health department (LHD) accreditation and COVID-19 community outcomes, including rates of adult vaccination, hospitalization, and death. We examined county level rates of adult vaccination, hospitalization, and death by LHD accreditation status over the course of the COVID pandemic. Additional independent variables included time period, COVID-19 Community Vulnerability Index (CCVI), state public health governance structure, and state policy environment. We used hierarchal linear mixed modeling with random intercept for county level data to account for repeated observations and fixed effects for all other variables. This study examined all communities in the United States of America. LHDs and the communities they serve. Rates of adult vaccination, hospitalization, and death due to COVID-19. Among accredited LHDs, the adult population was more likely to be fully vaccinated when compared to unaccredited LHDs ( P <.01). Additional variables in the model, which were also significant, included time period, CCVI, state policy environment, and state public health governance structure. There were no significant differences in the hospitalization rates in jurisdictions with an accredited LHD compared to jurisdictions where the LHD is not accredited. Death rates in jurisdictions with an accredited LHD were statistically significantly lower than death rates in jurisdictions where the health department was not accredited ( P <.001). This relationship was significant with other key variables in the model, including time, CCVI, state policy environment, and state public health governance structure. This study demonstrates that there is an association between LHD accreditation and community health outcomes. Furthermore, we found that other factors, such as social determinants of health, state policy environment, and state public health governance structure impact community health outcomes.

Ethnic and racial differences in children and young people withrespiratory and neurological post-acute sequelae of SARS-CoV-2: an electronic health record-based cohort study from the RECOVER Initiative.

Children from racial and ethnic minority groups are at greater risk for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but it is unclear whether they have increased risk for post-acute sequelae of SARS-CoV-2 (PASC). Our objectives were to assess whether the risk of respiratory and neurologic PASC differs by race/ethnicity and social drivers of health. We conducted a retrospective cohort study of individuals <21 years seeking care at 24 health systems across the U.S, using electronic health record (EHR) data. Our cohort included those with a positive SARS-CoV-2 molecular, serology or antigen test, or with a COVID-19, multisystem inflammatory disease in children, or PASC diagnosis from February 29, 2020 to August 1, 2022. We identified children/youth with at least 2 codes associated with respiratory and neurologic PASC. We measured associations between sociodemographic and clinical characteristics and respiratory and neurologic PASC using odds ratios and 95% confidence intervals estimated from multivariable logistic regression models adjusted for other sociodemographic characteristics, social vulnerability index or area deprivation index, time period of cohort entry, presence and complexity of chronic respiratory (respectively, neurologic) condition and healthcare utilization. Among 771,725 children in the cohort, 203,365 (26.3%) had SARS-CoV-2 infection. Among children with documented infection, 3217 children had respiratory PASC and 2009 children/youth had neurologic PASC. In logistic regression models, children <5 years (Odds Ratio [OR] 1.78, 95% CI 1.62-1.97), and of Hispanic White descent (OR 1.19, 95% CI 1.05-1.35) had higher odds of having respiratory PASC. Children/youth living in regions with higher area deprivation indices (OR 1.25, 95% CI 1.10-1.420 for 60-79th percentile) and with chronic complex respiratory conditions (OR 3.28, 95% CI 2.91-3.70) also had higher odds of respiratory PASC. In contrast, older (OR 1.57, 95% CI 1.40-1.77 for those aged 12-17 years), non-Hispanic White individuals and those with chronic pre-existing neurologic conditions (OR 2.04, 95% CI 1.78-2.35) were more likely to have a neurologic PASC diagnosis. Racial and ethnic differences in healthcare utilization for neurologic and respiratory PASC may reflect social drivers of health and inequities in access to care. National Institutes of Health.

Analysis of Health Determinants in Cleft Palate Patients.

This study aims to analyze health determinants affecting patients with cleft palate, specifically examining the relationships between the Social Vulnerability Index (SVI), failure to thrive (FTT), and healthcare utilization within the initial 30 days and first year of life. A retrospective analysis was conducted on patients with a cleft palate at a tertiary care center over an 11-year period. Data included demographics, weight percentile trends, pediatric emergency department (PED) visits, hospital admissions, SVI scores, cleft palate type, and FTT diagnoses. Statistical analyses were performed using SPSS. Social Vulnerability Index was not significantly correlated with health outcomes in cleft palate. Patients with FTT exhibited lower gestational age (P = .002) and birth (P = .005), one-month (P = .001), and one-year (P = .001) weight percentiles. FTT diagnosis was associated with increased PED visits (P = .000) and hospital admission (P = .000) in the first year of life. Early presentation to the PED was associated with increased PED visits (P = .000) and hospital admissions (P = .004) within the first year of life. No direct link was found between SVI and FTT. Early hospital readmission emerged as a significant outcome, indicating increased healthcare utilization in patients that require early medical intervention. Failure to thrive significantly impacted healthcare utilization, emphasizing the importance of addressing feeding issues early in this patient population. This study contributes to understanding health disparities in cleft palate patients and highlights the need for nuanced exploration of regional factors influencing outcomes.

Social vulnerability and genetic service utilization among unaffected BRIDGE trial patients with inherited cancer susceptibility

BackgroundResearch on social determinants of genetic testing uptake is limited, particularly among unaffected patients with inherited cancer susceptibility.MethodsWe conducted a secondary analysis of the Broadening the Reach, Impact, and Delivery of Genetic Services (BRIDGE) trial at University of Utah Health and NYU Langone Health, involving 2,760 unaffected patients meeting genetic testing criteria for inherited cancer susceptibility and who were initially randomized to either an automated chatbot or an enhanced standard of care (SOC) genetic services delivery model. We used encounters from the electronic health record (EHR) to measure the uptake of genetic counseling and testing, including dichotomous measures of (1) whether participants initiated pre-test cancer genetic services, (2) completed pre-test cancer genetic services, (3) had genetic testing ordered, and (4) completed genetic testing. We merged zip codes from the EHR to construct census tract-weighted social measures of the Social Vulnerability Index. Multilevel models estimated associations between social vulnerability and genetic services utilization. We tested whether intervention condition (i.e., chatbot vs. SOC) moderated the association of social vulnerability with genetic service utilization. Covariates included study arm, study site, age, sex, race/ethnicity, language preference, rural residence, having a recorded primary care provider, and number of algorithm criteria met.ResultsPatients living in areas of medium socioeconomic status (SES) vulnerability had lower odds of initiating pre-test genetic services (adjusted OR [aOR] = 0.81, 95% CI: 0.67, 0.98) compared to patients living in low SES vulnerability areas. Patients in medium household vulnerability areas had a lower likelihood of completing pre-test genetic services (aOR = 0.80, 95% CI: 0.66–0.97) and having genetic testing ordered (aOR = 0.79, 95% CI: 0.63–0.99) relative to patients in low household vulnerability areas. We did not find that social vulnerability associations varied by intervention condition.ConclusionsThese results underscore the importance of investigating social and structural mechanisms as potential pathways to increasing genetic testing uptake among patients with increased inherited risk of cancer. Census information is publicly available but seldom used to assess social determinants of genetic testing uptake among unaffected populations. Existing and future cohort studies can incorporate census data to derive analytic insights for clinical scientists.Trial registrationBRIDGE was registered as NCT03985852 on June 6, 2019 at clinicaltrials.gov.

2624 Exploring the experience of older people in care homes with the Administration of Oral Medication

Abstract Introduction Residents of care homes for older people experience multi-factorial problems when being given oral medication. A systematic integrated mixed-methods review of the literature revealed that practices of modifying tablets, crushing and mixing with food, in attempts to administer medication, remain widespread internationally. There is a high prevalence of swallowing problems. Care home routines are time pressured, and there are incidences of disempowering practices and language associated with processes of medication administration. The literature presented very little from the residents’ experience, largely representing them as passive recipients in the activity. Objective The aim of this study was to explore the experience of residents of care homes for older people who need help from care staff to take their medication. Its purpose was to answer a single research question, ‘What is the experience of residents of care homes when oral medication is administered?’ Methods Observation of an episode of medication administration and semi-structured interviewing were conducted with eight residents between the ages of 84 and 95 from care homes in Scotland. Data was analysed in accordance with a Gadamerian philosophy of hermeneutics, with a commitment to understanding and representing the participants’ experience. Results Four themes emerged from the data, ‘Being in control/relinquishing control’, ‘Being comfortable in routine’, ‘Trusting’, and ‘Swallowing’. Interpretive exploration of these themes revealed the importance of facilitating individual routines when taking medication, and that a trusting relationship with staff and with the medication can be an indicator of vulnerability. The risks to autonomy in relation to taking medication, and an imbalance of power for care home residents who are given medication to take emerged as an overarching concept. Conclusion Recommendations focus on the potential for empowering practices in relation to taking medication, both for those who provide care, and for those who prescribe medication.

Charlson comorbidity index has no incremental value for mortality risk prediction in nursing home residents with COVID-19 disease.

During the COVID-19 pandemic, nursing home (NH) residents faced the highest risk of severe COVID-19 disease and mortality. Due to their frailty status, comorbidity burden can serve as a useful predictive indicator of vulnerability in this frail population. However, the prognostic value of these cumulative comorbidity scores like the Charlson comorbidity index (CCI) remained unclear in this population. We evaluated the incremental predictive value of the CCI for predicting 28-day mortality in NH residents with COVID-19, compared to prediction using age and sex only. We included older individuals of ≥ 70years of age in a large retrospective observational cohort across NHs in the Netherlands. Individuals with PCR-confirmed COVID-19 diagnosis from 1 March 2020 to 31 December 2021 were included. The CCI score was computed by searching for the comorbidities recorded in the electronic patient records. All-cause mortality within 28days was predicted using logistic regression based on age and sex only (base model) and by adding the CCI to the base model (CCI model). The predictive performance of the base model and the CCI model were compared visually by the distribution of predicted risks and area under the receiver operator characteristic curve (AUROC), scaled Brier score, and calibration slope. A total of 4318 older NH residents were included in this study with a median age of 88years [IQR: 83-93] and a median CCI score of 6 [IQR: 5-7]. 1357 (31%) residents died within 28days after COVID-19 diagnosis. The base model, with age and sex as predictors, had an AUROC of 0.61 (CI: 0.60 to 0.63), a scaled brier score of 0.03 (CI: 0.02 to 0.04), and a calibration slope of 0.97 (CI: 0.83 to 1.13). The addition of CCI did not improve these predictive performance measures. The addition of the CCI as a vulnerability indicator did not improve short-term mortality prediction in NH residents. Similar (high) age and number of comorbidities in the NH population could reduce the effectiveness of these predictors, emphasizing the need for other population-specific predictors that can be utilized in the frail NH residents.

Optimizing a multimodal hub and spoke network for vaccine distribution using regional vulnerability index during healthcare emergencies

Purpose A vaccination strategy to cover the susceptible population is key to containing the spread of any virus during a healthcare emergency. This study quantifies the susceptibility of a region based on initial infection rates to prioritize optimal vaccine distribution strategies. The authors propose a metric, the regional vulnerability index (RVI), that identifies the degree of susceptibility/vulnerability of a region to virus infections for strategically locating hubs for vaccine storage and distribution. Design/methodology/approach A two-phase methodology is used to address this problem. Phase 1 uses a modified Susceptible-Infected-Recovered (SIR) model, ModSIR, to estimate the RVI. Phase 2 leverages this index to model a P-Center problem, prioritizing vulnerable regions through a Mixed Integer Quadratically Constrained Programming model, along with three variations that incorporate the RVI. Findings Results indicate a weighting scheme based on the population-to-RVI ratio fosters fair distribution and equitable coverage of vulnerable regions. Comparisons with the public distribution strategy outlined by the Government of India reveal similar zonal segregations. Additionally, the network generated by our model outperforms the actual distribution network, corroborated by network metrics such as degree centrality, weighted degree centrality and closeness centrality. Originality/value This research presents a novel approach to prioritizing vaccine distribution during pandemics by applying epidemiological predictions to an integer-programming framework, optimizing COVID-19 vaccine allocation based on historical infection data. The study highlights the importance of strategic planning in public health response to effectively manage resources in emergencies.

Impact of crop site geographic altitude on drought indices of field crops in Hungary

Growth and development of field crops is highly influenced by the water availability of the crop site. In an assessment study at the MATE University, the magnitude of aridity in relation with the geographic location of the crop site has been evaluated. Six field crop species (Sugar beet Beta vulgaris, winter barley Hordeum vulgare, winter wheat Triticum aestivum, maize Zea mays, potato Solanum tuberosum, and alfalfa Medicago sativa) were involved in the research. Data bases of twelve meteorological stations (Békéscsaba, Budapest, Debrecen, Miskolc, Mosonmagyaróvár, Nagykanizsa, Nyíregyháza, Pécs, Siófok, Szeged, Szolnok, Szombathely) representing major geographic areas of Hungary were used in the evaluation. PAI indices of the stations involved were combined with vulnerability indices of the field crops studied. Upon the results of the study cereals proved to be the most tolerant, while potato and maize were highly influenced by aridity x vulnerability interactions. Considerable impact could be seen in the case of alfalfa and sugar beet. The geographic altitude of the crop site was in negative correlation with the magnitude of drought indices.

Planning for a Warmer Future: Heat Risk Assessment and Mitigation in Lahti, Finland

With global climate change causing temperature increases, even cooler regions like Finland are facing increasing heat risks. The city of Lahti is expected to experience a higher-than-average temperature increase, making heat risk mitigation essential. This study aims to assess present and future heat risks in Lahti using exposure and social vulnerability indicators to identify heat risk hotspots and provide strategies for mitigation within the city’s urban planning framework. The method utilizes a combination of Land Surface Temperature (LST) data (2014–2024), climate projections, and microclimate analysis to identify heat risk in the city. Geographic Information Systems (GIS) and ENVI-met modeling were employed to assess the relationship between land surface temperatures (LST), urban structure, and green infrastructure. Risk assessments were conducted using social and environmental vulnerability indicators, and future projections were based on a combined SSP2-4.5 scenario. The results show a significant increase in high-risk areas by 2040, rising from 9.79% to 23.65% of Lahti’s core urban area. Although the current urban planning framework of the city (Masterplan 2035) is effective in terms of maintaining exposure levels, the continued increase in projected air temperatures, as modeled based on outputs of the EC-Earth3-veg GCM, remains a concern. Microclimate modeling confirmed that urban greenery significantly reduces heat stress and improves thermal comfort. To address future heat risks, Lahti must integrate more green infrastructure into its urban design and identify seasonal heat mitigation methodologies. Additionally, the findings emphasize the need for adaptive planning strategies to mitigate rising temperatures and ensure urban resilience.

P-1639. Assessing Disparities in Inappropriate Outpatient Antibiotic Prescriptions in Tennessee

Abstract Background The Centers for Disease Control and Prevention (CDC) estimates almost 47 million antibiotics are prescribed each year for indications that do not warrant antibiotic use. Identifying populations that are inappropriately prescribed antibiotics is imperative to address health inequities and prevent antimicrobial resistance. Tennessee Department of Health (TDH) evaluated disparities in outpatient antibiotic prescriptions in patients of different age groups, gender, geographical location, and insurance type. Methods The IQVIA Medical Claims and Longitudinal Prescription Claims databases were used to perform a cross-sectional study to evaluate the appropriateness of all outpatient antibiotics dispensed from retail pharmacies in TN from January 1–December 31, 2022. Data were categorized using a tiered system utilizing ICD-10 codes. Logistic regression was performed to predict whether age, gender, insurance type, and residence were associated with receiving an antibiotic in encounters for which antibiotics are rarely indicated (tier 3). Results In 2022, 2,017,863 prescribed antibiotics were linked to the medical claims database. Over half of these antibiotics were classified as a tier 3 encounter. Females were prescribed more antibiotics (62.0%). For tier 3 encounters specifically: 41.0% of antibiotics were prescribed to patients 65 and older. Residence in low and high socially vulnerable index (SVI) counties accounted for 27.9% and 24.9% of antibiotics, respectively. 37.2%, 16.5%, and 44.5% of antibiotics prescribed were billed to third-party payers (e.g., private health insurance), Medicaid, and Medicare Part D, respectively. Logistic regression showed female gender, younger age, and residence in low SVI had significantly higher odds of receiving an antibiotic for a tier 3 encounter; whereas prescriptions filled with Medicaid and Medicare were less likely to be associated with tier 3 encounters. Conclusion Previously TDH had not explored outpatient antibiotic use through a health equity lens. While the study provided basic demographic information about patients, there is a need to continue exploring disparities within various populations to aid in targeting inventions that drive appropriate antimicrobial use in ambulatory clinical settings. Disclosures All Authors: No reported disclosures

P-1425. Paxlovid Utilization and Social Vulnerability: Trends in Connecticut from 2022-2023

Abstract 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 &amp;lt; 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 &amp;lt; 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&amp;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

368. Impact of Social Determinants of Health (SDOH) on Outcomes of OPAT (Outpatient Parenteral Antimicrobial Therapy)

Abstract Background Complex infections may warrant extended antibiotics traditionally reserved for inpatient settings. OPAT is safe and cost effective, allowing return to regular activities and decreased risk of hospitalization. Understanding of SDOH-sensitive risk parameters and impact on adverse events is needed to guide safety and adherence interventions.Figure 1.Most Common OPAT Antibiotics and Indications in Study Cohort Methods Records of patients treated 7/15-10/31/2023 by URMC OPAT program, exclusive of concurrent Transitions of Care Program, were retrospectively reviewed for race, social vulnerability index, insurance type, substance use, needs insecurity, household composition, and outcomes such as OPAT-related orders errors, intravascular device (IVAD) complications, emergency utilization, organ system adverse events, and clinical outcome. A composite Undesirable OPAT Outcome was derived. The impact of SDOH was assessed by chi-square, univariate and multivariate logistic regression using R v4.3 3, rstatix v0.7.2, and sjPlotv2.8.15.Table 1.Proportion and Rates of Errors, Complications, and OPAT Treatment Outcomes in Study Cohort Results Total 116 patients received 3573 OPAT days for varying indications (Fig 1). High rates of discharge order errors, ED utilization, IVAD complications, adverse events, and composite Undesirable Outcomes were noted (Table 1). Those with public insurance (OR=13.6, CI: 1.95-322) or who used cannabis (OR=5.23 CI: 1.1- 27.2) were more likely to incur a laboratory order error on discharge. Patients of color were more likely to experience IVAD complications (OR=3.61, CI: 1.1-12.6) and multiple organ system adverse events (OR= 6.55, CI: 1.45-34.9). High-risk tobacco use was associated with shortened OPAT duration due to adverse event (OR=28.47, CI: 1.72-1299) (Fig 2). OPAT patients with public insurance were least likely to follow up with the ID clinic (OR=7.65, CI: 1.27-152). Time to ID follow-up correlated with multiple SDOH parameters, with publicly insured and persons of color experiencing significantly longer time to follow-up appointments (Fig 3). Incurring a non-IVAD adverse event correlated to composite undesirable outcome in multivariate analysis.Figure 2.Odds Ratios in Univariate Analysis of OPAT Complications Based on Social Determinants of Health Conclusion Social determinants may be predictors in OPAT-related unwanted events. A dedicated focus of evaluating SDOH as contributing drivers of adverse OPAT outcomes may assist creating interventions to support marginalized patient groups.Figure 3:Time-to-event probability analysis for timing of post-discharge ID clinic follow up among OPAT patients by Insurance Type (3A), Race (3B), and All Patients (3C) Disclosures All Authors: No reported disclosures

375. Back to School Unequal: Neighborhood Disadvantage and Asthma-related Emergency Department Visits in School-Aged Children

Abstract Background Asthma-related emergency department (ED) visit rates among children in a typical year closely follow the school calendar, with a sharp increase in rates when students return to school. The well-known increase in asthma exacerbations at the start of the school year is largely attributable to increases in respiratory viral infection. Because neighborhood disadvantage is strongly tied to asthma exacerbations, we hypothesized that greater neighborhood disadvantage would be associated with a greater increase in the rate of asthma exacerbations after the start of school. Methods We summarized Texas Health Care Information Collective data (2016-2019) on asthma-related ED visits among children (ages 5-17) in four Texas metropolitan statistical areas (Houston, Dallas, Austin, and San Antonio) by week and census tract. Neighborhood disadvantage was characterized at the census-tract level using tertiles of Social Vulnerability Index (SVI), percent uninsured, and percent living below the federal poverty line. Within each tertile, we described population-based incidence rates of asthma-related ED visits per 100,000 person-years in the 6 weeks before and after the week that school started. We also modeled weekly incidence rates and pointwise 95% confidence intervals by week using a locally weighted smoothing model. Results Comparing the 6-week periods before and after the week that school started, the incidence rate of asthma-related ED visits in high-, medium-, and low-SVI census tracts increased by 60, 39, and 20 cases per 100,000 person-years, respectively, representing a 3-fold difference between high- and low-SVI census tracts. Census tracts with high SVI had the greatest modeled increase in weekly rates of asthma-related ED visits after the start of school (Figure 1). Results were qualitatively similar for the percent of the population uninsured and below the federal poverty line (Figures 2-3). Conclusion Greater neighborhood disadvantage was associated with a greater increase in the rate of asthma related ED visits after the start of school, suggesting that neighborhood disadvantage may contribute to exacerbation risk by increasing the risk of respiratory virus infection. Disclosures Paul Rathouz, PhD, Sunovion Pharmaceuticals: DSMB Member