USING SPATIAL METHODS TO BETTER UNDERSTAND FOOD INSECURITY AND SNAP UNDER-PARTICIPATION IN TEXAS

The overall objective of this research is to use spatial methods to better understand food insecurity and SNAP under-participation in Texas. Paper 1 assesses whether a sample of community dwelling Medicare and Medicaid beneficiaries, who screen positive for food insecurity at healthcare locations in Harris County, exhibit a spatial pattern in terms of where they live. In other words, it tests whether or not there are statistically significant neighborhood hot spots or cold spots of food insecurity against a null hypothesis of complete spatial randomness. This approach is novel because it uses address-level data on patients who report being food insecure to test for statistically significant neighborhood hot spots or cold spots, instead of relying on extant factors like neighborhood poverty rates, or the presence of grocery stores. Using address-level food insecurity screening data is often difficult because few organizations screen for food insecurity, and even fewer are willing to share their data due to privacy concerns. Paper 2 utilizes geographical information systems (GIS) to map census tract-level clusters and outliers of households that are eligible but not enrolled (EBNE) in the SNAP program. The implications of this analysis are vast. Knowing the locations of neighborhood-level clusters and outliers of SNAP EBNE households can inform interventions to address the “SNAP GAP” more effectively. Additionally, this method of identifying neighborhood-level clusters and outliers of SNAP EBNE households can be applied to other safety net programs including Medicaid, the Children’s Health Insurance Program (CHIP), Healthy Texas Women, and the Women, Infant, and Children (WIC) Program

The Kiloparsec Scale Influence of the AGN in NGC 1068 with SALT RSS Fabry-P\'erot Spectroscopy

We present Fabry-P\'erot (FP) imaging and longslit spectroscopy of the nearby Seyfert II galaxy NGC 1068 using the Robert Stobie Spectrograph (RSS) on the Southern African Large Telescope (SALT) to observe the impact of the central Active Galactic Nucleus (AGN) on the ionized gas in the galaxy on kiloparsec scales. With SALT RSS FP we are able to observe the H$\alpha$+[N II] emission line complex over a $\sim$2.6 arcmin$^2$ field of view. Combined with the longslit observation, we demonstrate the efficacy of FP spectroscopy for studying nearby Type II Seyfert galaxies and investigate the kiloparsec-scale ionized gas in NGC 1068. We confirm the results of previous work from the TYPHOON/Progressive Integral Step Method (PrISM) survey that the kiloparsec-scale ionized features in NGC 1068 are driven by AGN photoionization. We analyze the spatial variation of the AGN intensity to put forward an explanation for the shape and structure of the kiloparsec-scale ionization features. Using a toy model, we suggest the ionization features may be understood as a light-echo from a burst of enhanced AGN activity $\sim$2000 years in the past.Comment: 18 pages, 9 figures. Accepted for publication in The Astronomical Journa

Social Determinants of Health Predict Readmission Following Covid-19 Hospitalization: a Health information Exchange-Based Retrospective Cohort Study

INTRODUCTION: Since February 2020, over 104 million people in the United States have been diagnosed with SARS-CoV-2 infection, or COVID-19, with over 8.5 million reported in the state of Texas. This study analyzed social determinants of health as predictors for readmission among COVID-19 patients in Southeast Texas, United States. METHODS: A retrospective cohort study was conducted investigating demographic and clinical risk factors for 30, 60, and 90-day readmission outcomes among adult patients with a COVID-19-associated inpatient hospitalization encounter within a regional health information exchange between February 1, 2020, to December 1, 2022. RESULTS AND DISCUSSION: In this cohort of 91,007 adult patients with a COVID-19-associated hospitalization, over 21% were readmitted to the hospital within 90  days

Examining Social Vulnerability and the association With Covid-19 incidence in Harris County, Texas

Studies have investigated the association between social vulnerability and SARS-CoV-2 incidence. However, few studies have examined small geographic units such as census tracts, examined geographic regions with large numbers of Hispanic and Black populations, controlled for testing rates, and incorporated stay-at-home measures into their analyses. Understanding the relationship between social vulnerability and SARS-CoV-2 incidence is critical to understanding the interplay between social determinants and implementing risk mitigation guidelines to curtail the spread of infectious diseases. The objective of this study was to examine the relationship between CDC\u27s Social Vulnerability Index (SVI) and SARS-CoV-2 incidence while controlling for testing rates and the proportion of those who stayed completely at home among 783 Harris County, Texas census tracts. SARS-CoV-2 incidence data were collected between May 15 and October 1, 2020. The SVI and its themes were the primary exposures. Median percent time at home was used as a covariate to measure the effect of staying at home on the association between social vulnerability and SARS-CoV-2 incidence. Data were analyzed using Kruskal Wallis and negative binomial regressions (NBR) controlling for testing rates and staying at home. Results showed that a unit increase in the SVI score and the SVI themes were associated with significant increases in SARS-CoV-2 incidence. The incidence risk ratio (IRR) was 1.090 (95% CI, 1.082, 1.098) for the overall SVI; 1.107 (95% CI, 1.098, 1.115) for minority status/language; 1.090 (95% CI, 1.083, 1.098) for socioeconomic; 1.060 (95% CI, 1.050, 1.071) for household composition/disability, and 1.057 (95% CI, 1.047, 1.066) for housing type/transportation. When controlling for stay-at-home, the association between SVI themes and SARS-CoV-2 incidence remained significant. In the NBR model that included all four SVI themes, only the socioeconomic and minority status/language themes remained significantly associated with SARS-CoV-2 incidence. Community-level infections were not explained by a communities\u27 inability to stay at home. These findings suggest that community-level social vulnerability, such as socioeconomic status, language barriers, use of public transportation, and housing density may play a role in the risk of SARS-CoV-2 infection regardless of the ability of some communities to stay at home because of the need to work or other reasons

An analysis of ways to maximize the efficiency of the NEPA environmental process at the Texas Department of Housing and Community Affairs

textIn light of the substantial sums of money that the Texas Department of Housing and Community Affairs (TDHCA) was awarded through the American Recovery and Reinvestment Act of 2009, ways to maximize the efficiency of the agency’s various processes are highly sought after. The TDHCA environmental review process, which is required by the National Environmental Policy Act (NEPA), is one of the longest processes that people applying for federal funding through TDHCA must face. It is, therefore, a process that would substantially benefit the agency by being made more efficient. In this report, areas where applicants find the TDHCA environmental process to be difficult are illustrated by a systematic tabulation of the deficiency reviews sent to a sample of applicants from 2009. Additionally, survey data collected from people who submit environmental applications, and also people who review environmental applications, provides quantitative data about specific areas of the process where applicants meet with difficulty; and also qualitative data about where survey-takers feel the process could be made easier and more efficient. The data seems to indicate that applicants have significant difficulty knowing how to start the environmental process, the documents necessary, and how to fill out the necessary documents. In terms of suggestions, the results indicate that a more elaborate, user-friendly environmental webpage, complete with examples of required documents, and examples of how to fill them out, would make the environmental process exponentially easier for applicants. With the process being easier for applicants, TDHCA Environmental Specialists will hopefully not need to send out as many deficiency reviews to applicants, and will instead be able to review applications faster and issue environmental clearance quicker; thus making the process more efficient.Community and Regional Plannin

Examining neighborhood-level hot and cold spots of food insecurity in relation to social vulnerability in Houston, Texas.

Food insecurity is prevalent and associated with poor health outcomes, but little is known about its geographical nature. The aim of this study is to utilize geospatial modeling of individual-level food insecurity screening data ascertained in health care settings to test for neighborhood hot and cold spots of food insecurity in a large metropolitan area, and then compare these hot spot neighborhoods to cold spot neighborhoods in terms of the CDC's Social Vulnerability Index. In this cross-sectional secondary data analysis, we geocoded the home addresses of 6,749 unique participants screened for food insecurity at health care locations participating in CMS's Accountable Health Communities (AHC) Model, as implemented in Houston, TX. Next, we created census-tract level incidence profiles of positive food insecurity screens per 1,000 people. We used Anselin's Local Moran's I statistic to test for statistically significant census tract-level hot/cold spots of food insecurity. Finally, we utilized a Mann-Whitney-U test to compare hot spot tracts to cold spot tracts in relation to the CDC's Social Vulnerability Index. We found that hot spot tracts had higher overall social vulnerability index scores (P <0.001), higher subdomain scores, and higher percentages of individual variables like poverty (P <0.001), unemployment (P <0.001), limited English proficiency (P <0.001), and more. The combination of robust food insecurity screening data, geospatial modeling, and the CDC's Social Vulnerability Index offers a solid method to understand neighborhood food insecurity

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

Equitable access to the COVID-19 vaccine remains a public health priority. This study explores the association between ZIP Code–Tabulation Area level Social Vulnerability Indices (SVI) and COVID-19 vaccine coverage in Texas. A mixed-effects, multivariable, random-intercept negative binomial model was used to explore the association between ZIP Code–Tabulation Area level SVI and COVID-19 vaccination coverage stratified by the availability of a designated vaccine access site. Lower COVID-19 vaccine coverage was observed in ZIP codes with the highest overall SVIs (adjusted mean difference (aMD) = −13, 95% CI, −23.8 to −2.1, p p = 0.01) and housing and transportation theme (aMD = −18.3, 95% CI, −29.6 to −7.1, p p = 0.04) and Blacks (aMD = −3.7, 95% CI, −6.4 to −1, p = 0.01). SVI negatively impacted COVID-19 vaccine coverage in Texas. Access to vaccine sites did not address disparities related to vaccine coverage among minority populations. These findings are relevant to guide the distribution of COVID-19 vaccines in regions with similar demographic and geospatial characteristics

Assessment of a SARS-CoV-2 wastewater monitoring program in El Paso, Texas, from November 2020 to June 2022

The border city of El Paso, Texas, and its water utility, El Paso Water, initiated a SARS-CoV-2 wastewater monitoring program to assess virus trends and the appropriateness of a wastewater monitoring program for the community. Nearly weekly sample collection at four wastewater treatment facilities (WWTFs), serving distinct regions of the city, was analyzed for SARS-CoV-2 genes using the CDC 2019-Novel coronavirus Real-Time RT-PCR diagnostic panel. Virus concentrations ranged from 86.7 to 268,000 gc/L, varying across time and at each WWTF. The lag time between virus concentrations in wastewater and reported COVID-19 case rates (per 100,00 population) ranged from 4–24 days for the four WWTFs, with the strongest trend occurring from November 2021 - June 2022. This study is an assessment of the utility of a geographically refined SARS-CoV-2 wastewater monitoring program to supplement public health efforts that will manage the virus as it becomes endemic in El Paso.</p

Leveraging a health information exchange for analyses of COVID-19 outcomes including an example application using smoking history and mortality.

Understanding sociodemographic, behavioral, clinical, and laboratory risk factors in patients diagnosed with COVID-19 is critically important, and requires building large and diverse COVID-19 cohorts with both retrospective information and prospective follow-up. A large Health Information Exchange (HIE) in Southeast Texas, which assembles and shares electronic health information among providers to facilitate patient care, was leveraged to identify COVID-19 patients, create a cohort, and identify risk factors for both favorable and unfavorable outcomes. The initial sample consists of 8,874 COVID-19 patients ascertained from the pandemic's onset to June 12th, 2020 and was created for the analyses shown here. We gathered demographic, lifestyle, laboratory, and clinical data from patient's encounters across the healthcare system. Tobacco use history was examined as a potential risk factor for COVID-19 fatality along with age, gender, race/ethnicity, body mass index (BMI), and number of comorbidities. Of the 8,874 patients included in the cohort, 475 died from COVID-19. Of the 5,356 patients who had information on history of tobacco use, over 26% were current or former tobacco users. Multivariable logistic regression showed that the odds of COVID-19 fatality increased among those who were older (odds ratio = 1.07, 95% CI 1.06, 1.08), male (1.91, 95% CI 1.58, 2.31), and had a history of tobacco use (2.45, 95% CI 1.93, 3.11). History of tobacco use remained significantly associated (1.65, 95% CI 1.27, 2.13) with COVID-19 fatality after adjusting for age, gender, and race/ethnicity. This effort demonstrates the impact of having an HIE to rapidly identify a cohort, aggregate sociodemographic, behavioral, clinical and laboratory data across disparate healthcare providers electronic health record (HER) systems, and follow the cohort over time. These HIE capabilities enable clinical specialists and epidemiologists to conduct outcomes analyses during the current COVID-19 pandemic and beyond. Tobacco use appears to be an important risk factor for COVID-19 related death