Spatial inequities in access to medications for treatment of opioid use disorder highlight scarcity of methadone providers under counterfactual scenarios.

Access to treatment and medication for opioid use disorder (MOUD) is essential in reducing opioid use and associated behavioral risks, such as syringe sharing among persons who inject drugs (PWID). Syringe sharing among PWID carries high risk of transmission of serious infections such as hepatitis C and HIV. MOUD resources, such as methadone provider clinics, however, are often unavailable to PWID due to barriers like long travel distance to the nearest methadone provider and the required frequency of clinic visits. The goal of this study is to examine the uncertainty in the effects of travel distance in initiating and continuing methadone treatment and how these interact with different spatial distributions of methadone providers to impact co-injection (syringe sharing) risks. A baseline scenario of spatial access was established using the existing locations of methadone providers in a geographical area of metropolitan Chicago, Illinois, USA. Next, different counterfactual scenarios redistributed the locations of methadone providers in this geographic area according to the densities of both the general adult population and according to the PWID population per zip code. We define different reasonable methadone access assumptions as the combinations of short, medium, and long travel distance preferences combined with three urban/suburban travel distance preference. Our modeling results show that when there is a low travel distance preference for accessing methadone providers, distributing providers near areas that have the greatest need (defined by density of PWID) is best at reducing syringe sharing behaviors. However, this strategy also decreases access across suburban locales, posing even greater difficulty in regions with fewer transit options and providers. As such, without an adequate number of providers to give equitable coverage across the region, spatial distribution cannot be optimized to provide equitable access to all PWID. Our study has important implications for increasing interest in methadone as a resurgent treatment for MOUD in the United States and for guiding policy toward improving access to MOUD among PWID.

Dimensions of Uncertainty: A spatiotemporal review of five COVID-19 datasets.

COVID-19 surveillance across the U.S. is essential to tracking and mitigating the pandemic, but data representing cases and deaths may be impacted by attribute, spatial, and temporal uncertainties. COVID-19 case and death data are essential to understanding the pandemic and serve as key inputs for prediction models that inform policy-decisions; consistent information across datasets is critical to ensuring coherent findings. We implement an exploratory data analytic approach to characterize, synthesize, and visualize spatial-temporal dimensions of uncertainty across commonly used datasets for case and death metrics (Johns Hopkins University, the New York Times, USAFacts, and 1Point3Acres). We scrutinize data consistency to assess where and when disagreements occur, potentially indicating underlying uncertainty. We observe differences in cumulative case and death rates to highlight discrepancies and identify spatial patterns. Data are assessed using pairwise agreement (Cohen's kappa) and agreement across all datasets (Fleiss' kappa) to summarize changes over time. Findings suggest highest agreements between CDC, JHU, and NYT datasets. We find nine discrete type-components of information uncertainty for COVID-19 datasets reflecting various complex processes. Understanding processes and indicators of uncertainty in COVID-19 data reporting is especially relevant to public health professionals and policymakers to accurately understand and communicate information about the pandemic.

Supermarket Proximity and Risk of Hypertension, Diabetes, and CKD: A Retrospective Cohort Study.

RATIONALE & OBJECTIVE: Living in environments with low access to food may increase the risk of chronic diseases. We investigated the association of household distance to the nearest supermarket (as a measure of food access) with the incidence of hypertension, diabetes, and chronic kidney disease (CKD) in a metropolitan area of the United States. STUDY DESIGN: Retrospective cohort study. SETTING & PARTICIPANTS: 777,994 individuals without hypertension, diabetes, or CKD at baseline within the HealthLNK Data Repository, which contains electronic health records from 7 health care institutions in Chicago, Illinois. EXPOSURE: Zip code-level average distance between households and nearest supermarket. OUTCOME: Incidence of hypertension, diabetes, and CKD based on presence of ICD-9 code and/or blood pressure≥140/90mm Hg, hemoglobin A1c≥6.5%, and eGFR<60mL/min/1.73m2, respectively. ANALYTICAL APPROACH: Average distance to nearest supermarket was aggregated from street-level metrics for 56 Chicagoland zip codes. The cumulative incidence of hypertension, diabetes, and CKD from 2007-2012 was calculated for each zip code in patients free of these diseases in 2006. Spatial analysis of food access and disease incidence was performed using bivariate local indicator of spatial association (BiLISA) maps and bivariate local Moran I statistics. The relationship between supermarket access and outcomes was analyzed using logistic regression. RESULTS: Of 777,994 participants, 408,608 developed hypertension, 51,380 developed diabetes, and 56,365 developed CKD. There was significant spatial overlap between average distance to supermarket and incidence of hypertension and diabetes but not CKD. Zip codes with large average supermarket distances and high incidence of hypertension and diabetes were clustered in southern and western neighborhoods. Models adjusted only for neighborhood factors (zip code-level racial composition, access to vehicles, median income) revealed significant associations between zip code-level average distance to supermarket and chronic disease incidence. Relative to tertile 1 (shortest distance), ORs in tertiles 2 and 3, respectively, were 1.27 (95% CI, 1.23-1.30) and 1.38 (95% CI, 1.33-1.43) for diabetes, 1.03 (95% CI, 1.02-1.05) and 1.04 (95% CI, 1.02-1.06) for hypertension, and 1.18 (95% CI, 1.15-1.21) and 1.33 (95% CI, 1.29-1.37) for CKD. Models adjusted for demographic factors and health insurance showed significant and positive association with greater odds of incident diabetes (tertile 2: 1.29 [95% CI, 1.26-1.33]; tertile 3: 1.35 [95% CI, 1.31-1.39]) but lesser odds of hypertension (tertile 2: 0.95 [95% CI, 0.94-0.97]; tertile 3: 0.91 [95% CI, 0.89-0.92]) and CKD (tertile 2: 0.80 [95% CI, 0.78-0.82]; tertile 3: 0.73 [95% CI, 0.72-0.76]). After adjusting for both neighborhood and individual covariates, supermarket distance remained significantly associated with greater odds of diabetes and lesser odds of hypertension, but there was no significant association with CKD. LIMITATIONS: Unmeasured neighborhood and social confounding variables, zip code-level analysis, and limited individual-level information. CONCLUSIONS: There are significant disparities in supermarket proximity and incidence of hypertension, diabetes, and CKD in Chicago, Illinois. The relationship between supermarket access and chronic disease is largely explained by individual- and neighborhood-level factors.

Creation and Validation of a New Socio-built Environment Index Measure of Opioid Overdose Risk for Use in Both Non-urban and Urban Settings.

A great deal of literature has examined features of the physical built environment as predictors of opioid overdose and other substance use-related outcomes. Other literature suggests that social characteristics of settings are important predictors of substance use outcomes. However, there is a dearth of literature simultaneously measuring both physical and social characteristics of settings in an effort to better predict opioid overdose. There is also a dearth of literature examining built environment as a predictor of overdose in non-urban settings. The present study presents a novel socio-built environment index measure of opioid overdose risk comprised of indicators measuring both social and physical characteristics of settings - and developed for use in both urban and non-urban settings - and assesses its validity among 565 urban, suburban, and rural New Jersey municipalities. We found that this novel measure had good convergent validity, based on significant positive associations with a social vulnerability index and crime rates, and significant negative associations with a municipal revitalization index and high school graduation rates. The index measure had good discriminant validity, based on lack of association with three different racial isolation indices. Finally, our index measure had good health outcome-based criterion validity, based on significant positive associations with recent overdose mortality. There were no major differences between rural, suburban, and urban municipalities in validity analysis findings. This promising new socio-built environment risk index measure could improve ability to target and allocate resources to settings with the greatest risk, in order to improve their impact on overdose outcomes.

Conceptualizing the Socio-Built Environment: An Expanded Theoretical Framework to Promote a Better Understanding of Risk for Nonmedical Opioid Overdose Outcomes in Urban and Non-Urban Settings.

Nonmedical opioid (NMO) use has been linked to significant increases in rates of NMO morbidity and mortality in non-urban areas. While there has been a great deal of empirical evidence suggesting that physical features of built environments represent strong predictors of drug use and mental health outcomes in urban settings, there is a dearth of research assessing the physical, built environment features of non-urban settings in order to predict risk for NMO overdose outcomes. Likewise, there is strong extant literature suggesting that social characteristics of environments also predict NMO overdoses and other NMO use outcomes, but limited research that considers the combined effects of both physical and social characteristics of environments on NMO outcomes. As a result, important gaps in the scientific literature currently limit our understanding of how both physical and social features of environments shape risk for NMO overdose in rural and suburban settings and therefore limit our ability to intervene effectively. In order to foster a more holistic understanding of environmental features predicting the emerging epidemic of NMO overdose, this article presents a novel, expanded theoretical framework that conceptualizes "socio-built environments" as comprised of (a) environmental characteristics that are applicable to both non-urban and urban settings and (b) not only traditional features of environments as conceptualized by the extant built environment framework, but also social features of environments. This novel framework can help improve our ability to identify settings at highest risk for high rates of NMO overdose, in order to improve resource allocation, targeting, and implementation for interventions such as opioid treatment services, mental health services, and care and harm reduction services for people who use drugs.

Neighbourhoods, networks and pre-exposure prophylaxis awareness: a multilevel analysis of a sample of young black men who have sex with men.

OBJECTIVE: Young black men who have sex with men (YBMSM) in the USA represent a subgroup that has the highest HIV incidence among the overall population. In the USA, pre-exposure prophylaxis (PrEP) is an effective prevention intervention to prevent HIV acquisition when taken regularly. Neighbourhood and network factors may relate to PrEP awareness, but have not been studied in YBMSM. This study aimed to examine the relationship of neighbourhood and network characteristics with PrEP awareness among YBMSM. METHODS: We used data collected from a sample of 618 YBMSM in Chicago (2013-2014). Home addresses were collected for participants and enumerated network members. Administrative data (eg, 2014 American Community Survey, Chicago Department of Public Health) were used to describe residence characteristics. Network member characteristics were also collected (eg, sexual partners' sex-drug use, confidant network members who were also MSM). Multilevel analysis was performed to examine the relationships of neighbourhood and network characteristics to PrEP awareness. RESULTS: Higher neighbourhood-level educational attainment (adjusted odds ratio (aOR) 1.02, p=0.03) and greater primary care density (aOR 1.38, p=0.01) were associated with greater PrEP awareness; greater neighbourhood alcohol outlet density (aOR 0.52, p=0.004) was associated with less PrEP awareness. Sexual network members residing in the same neighbourhood as the participants (aOR 2.58, p=0.03) and discussions around avoiding HIV acquisition with confidants (aOR 2.26, p=0.04) were associated with greater PrEP awareness. CONCLUSIONS: The results suggest that neighbourhood and network characteristics can influence PrEP awareness in YBMSM. Additional studies are needed to understand the influences of neighbourhood (eg, MSM serving venues) and network (eg, peer to peer communication) characteristics on dissemination of PrEP information, uptake and adherence and the related mechanisms behind the associations.

Oral cancer incidence rate is associated with access to dental care: City and statewide analyses.

INTRODUCTION: Access to dental care may affect diagnosis of oral squamous cell carcinoma (OSCC). We tested whether the incidence rate of OSCC is higher in regions with less dental care access in the city of Chicago and state of Illinois. STUDY DESIGN: Ecological cohort. SETTING: Population, outpatients, and inpatients. METHODS: We extracted 5-year averages of the state-wide county-level and city-level OSCC incidence rates from 2015 to 2019 from the Illinois Department of Public Health. Dental care access information was also collected for each county for the same period, as well as the percentage of people that had ≥1 visit to a dentist in the previous year in Chicago. Multivariate Poisson regression was used to investigate the relationship between county-level access to dental care (and city-level dentist visits) and OSCC incidence rate, controlling for confounders, with additional flexible semiparametric models for confirmatory sensitivity analysis. RESULTS: In Illinois, higher 5-year incidence rate of OSCC was significantly associated with low access to dental care by county (IRR = 0.96, 95% CI 0.91, 0.98). Southern/southwestern counties had higher incidence rates of OSCC (15.5%-28.4%) and the lowest rates of dental care access (47.5%-69.2%) compared to northern counties (10.3%-15% and 55.4%-80.6%, respectively). In Chicago, people with more dentist visits had a reduced chance of being diagnosed with OSCC (IRR = 0.97, 95% CI 0.91, 0.99), consistent with state-wide analyses. CONCLUSION: OSCC incidence rate is closely associated with poor local dental healthcare access in a major state and urban city. Increasing dental access could improve cancer outcomes via improved oral health and earlier detection.

Methadone prescribing by addiction specialists likely to leave communities without available methadone treatment.

Methadone treatment for opioid use disorder is not available in most suburban and rural US communities. We examined 2 options to expand methadone availability: (1) addiction specialty physician or (2) all clinician prescribing. Using 2022 Health Resources and Services Administration data, we used mental health professional shortage areas to indicate the potential of addiction specialty physician prescribing and the location of federally qualified health centers (ie, federally certified primary care clinics) to indicate the potential of all clinician prescribing. We examined how many census tracts without an available opioid treatment program (ie, methadone clinic) are (1) located within a mental health professional shortage area and (2) are also without an available federally qualified health center. Methadone was available in 49% of tracts under current regulations, 63% of tracts in the case of specialist physician prescribing, and 86% of tracts in the case of all clinician prescribing. Specialist physician prescribing would expand availability to an additional 12% of urban, 18% of suburban, and 16% of rural tracts, while clinician prescribing would expand to an additional 30% of urban, 53% of suburban, and 58% of rural tracts relative to current availability. Results support enabling broader methadone prescribing privileges to ensure equitable treatment access, particularly for rural communities.

Social-spatial network structures among young urban and suburban persons who inject drugs in a large metropolitan area.

Background: It is estimated that there are 1.5% US adult population who inject drugs in 2018, with young adults aged 18-39 showing the highest prevalence. PWID are at a high risk of many blood-borne infections. Recent studies have highlight the importance of employing the syndemic approach to study opioid misuse, overdose, HCV and HIV, along with the social and environmental contexts where these interrelated epidemics occur in already marginalized communities. Social interactions and spatial contexts are important structural factors that are understudied. Methods: Egocentric injection network and geographic activity spaces for young (aged 18-30) PWID and their injection, sexual, and social support network members (i.e., where reside, inject drugs, purchase drugs, and meet sex partners) were examined using baseline data from an ongoing longitudinal study (n=258). Participants were stratified based on the location of all place(s) of residence in the past year i.e., urban, suburban, and transient (both urban and suburban) to i) elucidate geospatial concentration of risk activities within multi-dimensional risk environments based on kernel density estimates; and ii) examine spatialized social networks for each residential group. Results: Participants were mostly non-Hispanic white (59%); 42% were urban residents, 28% suburban, and 30% transient. We identified a spatial area with concentrated risky activities for each residence group on the West side of Chicago where a large outdoor drug market area is located. The urban group (80%) reported a smaller concentrated area (14 census tracts) compared to the transient (93%) and suburban (91%) with 30 and 51 tracts, respectively. Compared to other areas in Chicago, the identified area had significantly higher neighborhood disadvantages (e.g., higher poverty rate, p <0.001). Significant ( p <0.01 for all) differences were observed in social network structures: suburban had the most homogenous network in terms of age and residence, transient participants had the largest network (degree) and more non-redundant connections. Conclusion: We identified concentrated risk activity spaces among PWID from urban, suburban, and transient groups in a large outdoor urban drug market area, which highlights the need for considering the role of risk spaces and social networks in addressing the syndemics in PWID populations.

Social-spatial network structures among young urban and suburban persons who inject drugs in a large metropolitan area.

BACKGROUND: Recent studies underscore the significance of adopting a syndemics approach to study opioid misuse, overdose, hepatitis C (HCV) and HIV infections, within the broader context of social and environmental contexts in already marginalized communities. Social interactions and spatial contexts are crucial structural factors that remain relatively underexplored. This study examines the intersections of social interactions and spatial contexts around injection drug use. More specifically, we investigate the experiences of different residential groups among young (aged 18-30) people who inject drugs (PWID) regarding their social interactions, travel behaviors, and locations connected to their risk behaviors. By doing so, we aim to achieve a more comprehensive understanding of the multidimensional risk environment, thereby facilitating the development of informed policies. METHODS: We collected and examined data regarding young PWID's egocentric injection network and geographic activity spaces (i.e., where they reside, inject drugs, purchase drugs, and meet sex partners). Participants were stratified based on the location of all place(s) of residence in the past year i.e., urban, suburban, and transient (both urban and suburban) to i) elucidate geospatial concentration of risk activities within multidimensional risk environments based on kernel density estimates; and ii) examine spatialized social networks for each residential group. RESULTS: Participants were mostly non-Hispanic white (59%); 42% were urban residents, 28% suburban, and 30% transient. We identified a spatial area with concentrated risky activities for each residential group on the West side of Chicago in Illinois where a large outdoor drug market area is located. The urban group (80%) reported a smaller concentrated area (14 census tracts) compared to the transient (93%) and suburban (91%) with 30 and 51 tracts, respectively. Compared to other areas in Chicago, the identified area had significantly higher neighborhood disadvantages. Significant differences were observed in social network structures and travel behaviors: suburban participants had the most homogenous network in terms of age and residence, transient participants had the largest network (degree) and more non-redundant connections, while the urban group had the shortest travel distance for all types of risk activities. CONCLUSION: Distinct residential groups exhibit varying patterns of network interaction, travel behaviors, and geographical contexts related to their risk behaviors. Nonetheless, these groups share common concentrated risk activity spaces in a large outdoor urban drug market area, underscoring the significance of accounting for risk spaces and social networks in addressing syndemics within PWID populations.

Spatial inequities in access to medications for treatment of opioid use disorder highlight scarcity of methadone providers under counterfactual scenarios.

Access to treatment and medication for opioid use disorder (MOUD) is essential in reducing opioid use and associated behavioral risks, such as syringe sharing among persons who inject drugs (PWID). Syringe sharing among PWID carries high risk of transmission of serious infections such as hepatitis C and HIV. MOUD resources, such as methadone provider clinics, however, are often unavailable to PWID due to barriers like long travel distance to the nearest methadone provider and the required frequency of clinic visits. The goal of this study is to examine the uncertainty in the effects of travel distance in initiating and continuing methadone treatment and how these interact with different spatial distributions of methadone providers to impact co-injection (syringe sharing) risks. A baseline scenario of spatial access was established using the existing locations of methadone providers in a geographical area of metropolitan Chicago, Illinois, USA. Next, different counterfactual scenarios redistributed the locations of methadone providers in this geographic area according to the densities of both the general adult population and according to the PWID population per zip code. We define different reasonable methadone access assumptions as the combinations of short, medium, and long travel distance preferences combined with three urban/suburban travel distance preference. Our modeling results show that when there is a low travel distance preference for accessing methadone providers, distributing providers near areas that have the greatest need (defined by density of PWID) is best at reducing syringe sharing behaviors. However, this strategy also decreases access across suburban locales, posing even greater difficulty in regions with fewer transit options and providers. As such, without an adequate number of providers to give equitable coverage across the region, spatial distribution cannot be optimized to provide equitable access to all PWID. Our study has important implications for increasing interest in methadone as a resurgent treatment for MOUD in the United States and for guiding policy toward improving access to MOUD among PWID.

Assessment of Structural Barriers and Racial Group Disparities of COVID-19 Mortality With Spatial Analysis.

IMPORTANCE: Although social determinants of health (SDOH) are important factors in health inequities, they have not been explicitly associated with COVID-19 mortality rates across racial and ethnic groups and rural, suburban, and urban contexts. OBJECTIVES: To explore the spatial and racial disparities in county-level COVID-19 mortality rates during the first year of the pandemic. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study analyzed data for all US counties in 50 states and the District of Columbia for the first full year of the COVID-19 pandemic (January 22, 2020, to February 28, 2021). Counties with a high concentration of a single racial and ethnic population and a high level of COVID-19 mortality rate were identified as concentrated longitudinal-impact counties. The SDOH that may be associated with mortality rate across these counties and in urban, suburban, and rural contexts were examined. The 3 largest racial and ethnic groups in the US were selected: Black or African American, Hispanic or Latinx, and non-Hispanic White populations. EXPOSURES: County-level characteristics and community health factors (eg, income inequality, uninsured rate, primary care physicians, preventable hospital stays, severe housing problems rate, and access to broadband internet) associated with COVID-19 mortality. MAIN OUTCOMES AND MEASURES: Data on county-level COVID-19 mortality rates (deaths per 100 000 population) reported by the US Centers for Disease Control and Prevention were analyzed. Four indexes were used to measure multiple dimensions of SDOH: socioeconomic advantage index, limited mobility index, urban core opportunity index, and mixed immigrant cohesion and accessibility index. Spatial regression models were used to examine the associations between SDOH and county-level COVID-19 mortality rate. RESULTS: Of the 3142 counties included in the study, 531 were identified as concentrated longitudinal-impact counties. Of these counties, 347 (11.0%) had a large Black or African American population compared with other counties, 198 (6.3%) had a large Hispanic or Latinx population compared with other counties, and 33 (1.1%) had a large non-Hispanic White population compared with other counties. A total of 489 254 COVID-19-related deaths were reported. Most concentrated longitudinal-impact counties with a large Black or African American population compared with other counties were spread across urban, suburban, and rural areas and experienced numerous disadvantages, including higher income inequality (297 of 347 [85.6%]) and more preventable hospital stays (281 of 347 [81.0%]). Most concentrated longitudinal-impact counties with a large Hispanic or Latinx population compared with other counties were located in urban areas (114 of 198 [57.6%]), and 130 (65.7%) of these counties had a high percentage of people who lacked health insurance. Most concentrated longitudinal-impact counties with a large non-Hispanic White population compared with other counties were in rural areas (23 of 33 [69.7%]), included a large group of older adults (26 of 33 [78.8%]), and had limited access to quality health care (24 of 33 [72.7%]). In urban areas, the mixed immigrant cohesion and accessibility index was inversely associated with COVID-19 mortality (coefficient [SE], -23.38 [6.06]; P < .001), indicating that mortality rates in urban areas were associated with immigrant communities with traditional family structures, multiple accessibility stressors, and housing overcrowding. Higher COVID-19 mortality rates were also associated with preventable hospital stays in rural areas (coefficient [SE], 0.008 [0.002]; P < .001) and higher socioeconomic status vulnerability in suburban areas (coefficient [SE], -21.60 [3.55]; P < .001). Across all community types, places with limited internet access had higher mortality rates, especially in urban areas (coefficient [SE], 5.83 [0.81]; P < .001). CONCLUSIONS AND RELEVANCE: This cross-sectional study found an association between different SDOH measures and COVID-19 mortality that varied across racial and ethnic groups and community types. Future research is needed that explores the different dimensions and regional patterns of SDOH to address health inequity and guide policies and programs.

Individual, interpersonal, and neighborhood measures associated with opioid use stigma: Evidence from a nationally representative survey.

Despite growing awareness of opioid use disorder (OUD), fatal overdoses and downstream health conditions (e.g., hepatitis C and HIV) continue to rise in some populations. Various interrelated structural forces, together with social and economic determinants, contribute to this ongoing crisis; among these, access to medications for opioid use disorder (MOUD) and stigma towards people with OUD remain understudied. We combined data on methadone, buprenorphine, and naltrexone providers from SAMHSA's 2019 directory, additional naltrexone providers from Vivitrol's location finder service, with a nationally representative survey called "The AmeriSpeak survey on stigma toward people with OUD." Integrating the social-ecological framework, we focus on individual characteristics, personal and family members' experience with OUD, and spatial access to MOUD at the community level. We use nationally representative survey data from 3008 respondents who completed their survey in 2020. Recognizing that stigma is a multifaceted construct, we also examine how the process varies for different types of stigma, specifically perceived dangerousness and untrustworthiness, as well as social distancing measures under different scenarios. We found a significant association between stigma and spatial access to MOUD - more resources are related to weaker stigma. Respondents had a stronger stigma towards people experiencing current OUD (versus past OUD), and they were more concerned about OUD if the person would marry into their family (versus being their coworkers). Additionally, respondents' age, sex, education, and personal experience with OUD were also associated with their stigma, and the association can vary depending on the specific type of stigma. Overall, stigma towards people with OUD was associated with both personal experiences and environmental measures.

Assessment of Community-Level Vulnerability and Access to Medications for Opioid Use Disorder.

Importance: Given that COVID-19 and recent natural disasters exacerbated the shortage of medication for opioid use disorder (MOUD) services and were associated with increased opioid overdose mortality, it is important to examine how a community's ability to respond to natural disasters and infectious disease outbreaks is associated with MOUD access. Objective: To examine the association of community vulnerability to disasters and pandemics with geographic access to each of the 3 MOUDs and whether this association differs by urban, suburban, or rural classification. Design, Setting, and Participants: This cross-sectional study of zip code tabulation areas (ZCTAs) in the continental United States excluding Washington, DC, conducted a geospatial analysis of 2020 treatment location data. Exposures: Social vulnerability index (US Centers for Disease Control and Prevention measure of vulnerability to disasters or pandemics). Main Outcomes and Measures: Drive time in minutes from the population-weighted center of the ZCTA to the ZCTA of the nearest treatment location for each treatment type (buprenorphine, methadone, and extended-release naltrexone). Results: Among 32 604 ZCTAs within the continental US, 170 within Washington, DC, and 20 without an urban-rural classification were excluded, resulting in a final sample of 32 434 ZCTAs. Greater social vulnerability was correlated with longer drive times for methadone (correlation, 0.10; 95% CI, 0.09 to 0.11), but it was not correlated with access to other MOUDs. Among rural ZCTAs, increasing social vulnerability was correlated with shorter drive times to buprenorphine (correlation, -0.10; 95% CI, -0.12 to -0.08) but vulnerability was not correlated with other measures of access. Among suburban ZCTAs, greater vulnerability was correlated with both longer drive times to methadone (correlation, 0.22; 95% CI, 0.20 to 0.24) and extended-release naltrexone (correlation, 0.15; 95% CI, 0.13 to 0.17). Conclusions and Relevance: In this study, communities with greater vulnerability did not have greater geographic access to MOUD, and the mismatch between vulnerability and medication access was greatest in suburban communities. Rural communities had poor geographic access regardless of vulnerability status. Future disaster preparedness planning should match the location of services to communities with greater vulnerability to prevent inequities in overdose deaths.

Association Between Acute Exposure to Crime and Individual Systolic Blood Pressure.

INTRODUCTION: Hypertension is associated with adverse cardiovascular outcomes and is geographically concentrated in urban underserved neighborhoods. This study examines the temporal-spatial association between individual exposure to violent crime and blood pressure. METHODS: A retrospective observational cohort study analyzed 39,211 patients with 227,595 blood pressure measurements from 2014 to 2016 at 3 outpatient clinics at an academic medical center in Chicago. Patients were included in the study if they had documentation of blood pressure in the medical record and resided in census tracts with >1,000 observations. Geocoded violent crime events were obtained from the Chicago Police Department. Individual-level exposure was defined on the basis of spatial and temporal buffers around each patient's home. Spatial buffers included 100-, 250-, 500-, and 1,000-meter disc radii, and temporal buffers included 7, 30, and 60 days preceding each outpatient appointment. Systolic blood pressure measurements (mmHg) were abstracted from the electronic health record. Analysis was performed in 2019-2020. RESULTS: For each violent crime event within 100 meters from home, systolic blood pressure increased by 0.14 mmHg within 7 days of exposure compared with 0.08 mmHg at 30 days of exposure. In analyses stratified by neighborhood cluster, systolic blood pressure increased by 0.37 mmHg among patients in the suburban affluent cluster relative to that among those in an extreme poverty cluster for the same spatial and temporal buffer. CONCLUSIONS: Exposure to a violent crime event was associated with increased blood pressure, with gradient effects by both distance and time from exposure.

Associations of four indexes of social determinants of health and two community typologies with new onset type 2 diabetes across a diverse geography in Pennsylvania.

Evaluation of geographic disparities in type 2 diabetes (T2D) onset requires multidimensional approaches at a relevant spatial scale to characterize community types and features that could influence this health outcome. Using Geisinger electronic health records (2008-2016), we conducted a nested case-control study of new onset T2D in a 37-county area of Pennsylvania. The study included 15,888 incident T2D cases and 79,435 controls without diabetes, frequency-matched 1:5 on age, sex, and year of diagnosis or encounter. We characterized patients' residential census tracts by four dimensions of social determinants of health (SDOH) and into a 7-category SDOH census tract typology previously generated for the entire United States by dimension reduction techniques. Finally, because the SDOH census tract typology classified 83% of the study region's census tracts into two heterogeneous categories, termed rural affordable-like and suburban affluent-like, to further delineate geographies relevant to T2D, we subdivided these two typology categories by administrative community types (U.S. Census Bureau minor civil divisions of township, borough, city). We used generalized estimating equations to examine associations of 1) four SDOH indexes, 2) SDOH census tract typology, and 3) modified typology, with odds of new onset T2D, controlling for individual-level confounding variables. Two SDOH dimensions, higher socioeconomic advantage and higher mobility (tracts with fewer seniors and disabled adults) were independently associated with lower odds of T2D. Compared to rural affordable-like as the reference group, residence in tracts categorized as extreme poverty (odds ratio [95% confidence interval] = 1.11 [1.02, 1.21]) or multilingual working (1.07 [1.03, 1.23]) were associated with higher odds of new onset T2D. Suburban affluent-like was associated with lower odds of T2D (0.92 [0.87, 0.97]). With the modified typology, the strongest association (1.37 [1.15, 1.63]) was observed in cities in the suburban affluent-like category (vs. rural affordable-like-township), followed by cities in the rural affordable-like category (1.20 [1.05, 1.36]). We conclude that in evaluating geographic disparities in T2D onset, it is beneficial to conduct simultaneous evaluation of SDOH in multiple dimensions. Associations with the modified typology showed the importance of incorporating governmentally, behaviorally, and experientially relevant community definitions when evaluating geographic health disparities.

Social-spatial network structures and community ties of egocentric sex and confidant networks: A Chicago case study.

Exploring how sexual and confidant networks overlap spatially and socially could facilitate a better understanding of sexually transmitted infection risk, as well as help identify areas for interventions. This study aims to examine how a sexual and peer-affiliate network is impacted or shaped by interconnected social relationships and spatial patterns. We used data collected from a sample of 618 young black men who have sex with men (YBMSM) and transgender women in Chicago (2013-2014) that includes partner and confidant links, geolocations, and pre-exposure prophylaxis (PrEP) awareness. We spatialize different types of social networks and examine joint social-spatial community ties to both identify and differentiate social-spatial behavioral patterns. We explore the spatial structures of the social network by comparing ego-alter network residence patterns, visualizing ego-alter community ties in aggregate, and grouping different types of dyad relationships based on their spatial structure. Findings showed overlapping social and sexual networks. Egos with partners residing in more resourced communities furthest away, with wider alter-ego power differentials, also tended to be at greatest risk. Identifying the social-spatial structures of community ties is critical to enhance our understanding of the spatial context of social relationships, and further distill risk heterogeneity in vulnerable populations within an equitable health framework.

The US COVID Atlas: A dynamic cyberinfrastructure surveillance system for interactive exploration of the pandemic.

Distributed spatial infrastructures leveraging cloud computing technologies can tackle issues of disparate data sources and address the need for data-driven knowledge discovery and more sophisticated spatial analysis central to the COVID-19 pandemic. We implement a new, open source spatial middleware component (libgeoda) and system design to scale development quickly to effectively meet the need for surveilling county-level metrics in a rapidly changing pandemic landscape. We incorporate, wrangle, and analyze multiple data streams from volunteered and crowdsourced environments to leverage multiple data perspectives. We integrate explorative spatial data analysis (ESDA) and statistical hotspot standards to detect infectious disease clusters in real time, building on decades of research in GIScience and spatial statistics. We scale the computational infrastructure to provide equitable access to data and insights across the entire USA, demanding a basic but high-quality standard of ESDA techniques. Finally, we engage a research coalition and incorporate principles of user-centered design to ground the direction and design of Atlas application development.

A Vulnerability Assessment for a Future HIV Outbreak Associated With Injection Drug Use in Illinois, 2017-2018.

The current opioid crisis and the increase in injection drug use (IDU) have led to outbreaks of HIV in communities across the country. These outbreaks have prompted country and statewide examination into identifying factors to determine areas at risk of a future HIV outbreak. Based on methodology used in a prior nationwide county-level analysis by the US Centers for Disease Control and Prevention (CDC), we examined Illinois at the ZIP code level (n = 1,383). Combined acute and chronic hepatitis C virus (HCV) infection among persons <40 years of age was used as an outcome proxy measure for IDU. Local and statewide data sources were used to identify variables that are potentially predictive of high risk for HIV/HCV transmission that fell within three main groups: health outcomes, access/resources, and the social/economic/physical environment. A multivariable negative binomial regression was performed with population as an offset. The vulnerability score for each ZIP code was created using the final regression model that consisted of 11 factors, six risk factors, and five protective factors. ZIP codes identified with the highest vulnerability ranking (top 10%) were distributed across the state yet focused in the rural southern region. The most populous county, Cook County, had only one vulnerable ZIP code. This analysis reveals more areas vulnerable to future outbreaks compared to past national analyses and provides more precise indications of vulnerability at the ZIP code level. The ability to assess the risk at sub-county level allows local jurisdictions to more finely tune surveillance and preventive measures and target activities in these high-risk areas. The final model contained a mix of protective and risk factors revealing a heightened level of complexity underlying the relationship between characteristics that impact HCV risk. Following this analysis, Illinois prioritized recommendations to include increasing access to harm reduction services, specifically sterile syringe services, naloxone access, infectious disease screening and increased linkage to care for HCV and opioid use disorder.