Exploring the Spatial Determinants of Late HIV Diagnosis in Texas

Access to Federally Qualified Health Centers and HIV Outcomes in the U.S. South

INTRODUCTION

Federally Qualified Health Centers may increase access to HIV prevention, care, and treatment for at-risk populations.

METHODS

A pooled cross section of ZIP Code Tabulation Areas from cites in the U.S. South with high HIV diagnoses were used to examine Federally Qualified Health Center density and indicators of HIV epidemic control. The explanatory variable was Federally Qualified Health Center density-number of Federally Qualified Health Centers in a ZIP Code Tabulation Areas' Primary Care Service Area per low-income population-high versus medium/low (2019). Outcomes were 5-year (2015-2019 or 2014-2018) (1) number of new HIV diagnoses, (2) percentage late diagnosis, (3) percentage linked to care, and (4) percentage virally suppressed, which was assessed over 1 year (2018 or 2019). Multiple linear regression was used to examine the relationship, including ZIP Code Tabulation Area-level sociodemographic and city-level HIV funding variables, with state-fixed effects, and data analysis was completed in 2022-2023. Sensitivity analyses included (1) examining ZIP Code Tabulation Areas with fewer non-Federally Qualified Health Center primary care providers, (2) controlling for county-level primary care provider density, (3) excluding the highest HIV prevalence ZIP Code Tabulation Areas, and (4) excluding Florida ZIP Code Tabulation Areas.

RESULTS

High-density ZIP Code Tabulation Areas had a lower percentage of late diagnosis and virally suppressed, a higher percentage linked to care, and no differences in new HIV diagnoses (p<0.05). In adjusted analysis, high density was associated with a greater number of new diagnoses (number or percentage=5.65; 95% CI=2.81, 8.49), lower percentage of late diagnosis (-3.71%; 95% CI= -5.99, -1.42), higher percentage linked to care (2.13%; 95% CI=0.20, 4.06), and higher percentage virally suppressed (1.87%; 95% CI=0.53, 2.74) than medium/low density.

CONCLUSIONS

Results suggest that access to Federally Qualified Health Centers may benefit community-level HIV epidemic indicators.

Geographic disparities in late HIV diagnoses in Tennessee: Opportunities for interventions in the rural Southeast

PURPOSE

Incident HIV remains an important public health issue in the US South, the region leading the nation in HIV incidence, rural HIV cases, and HIV-related deaths. Late diagnoses drive incident HIV and understanding factors driving late diagnoses is critical for developing locally relevant HIV testing and prevention interventions, decreasing HIV transmission, and ending the HIV epidemic.

METHODS

Retrospective cohort study utilizing Tennessee Department of Health (TDH) surveillance data and US Census Bureau data. Adults of ≥18-year old with a new HIV diagnosis between January 1, 2015 and December 31, 2019 identified in the TDH electronic HIV/AIDS Reporting System were included. Individuals were followed from initial HIV diagnosis until death, 90 days of follow-up for outcome assessment, or administrative censoring 90 days after study enrollment closed.

FINDINGS

We included 3652 newly HIV-diagnosed individuals; median age was 31 years (IQR: 25, 42), 2909 (79.7%) were male, 2057 (56.3%) were Black, 246 (6.7%) were Hispanic, 408 (11.2%) were residing in majority-rural areas at diagnosis, and 642 (17.6%) individuals received a late HIV diagnosis. Residents of majority-rural counties (adjusted risk ratios [aRR] = 1.39, 95% confidence intervals [CI]: 1.16-1.67) and Hispanic individuals (aRR = 1.87, 95% CI: 1.50-2.33) had an increased likelihood of receiving a late diagnosis after controlling for race/ethnicity, age, and year of HIV diagnosis.

CONCLUSIONS

Rural residence and Hispanic ethnicity were associated with an increased risk of receiving a late HIV diagnosis in Tennessee. Future HIV testing and prevention efforts should be adapted to the needs of these vulnerable populations.

Global and local drivers of Echinococcus multilocularis infection in the western Balkan region

The cestode, Echinococcus multilocularis, is one of the most threatening parasitic challenges in the European Union. Despite the warming climate, the parasite intensively spread in Europe's colder and warmer regions. Little is known about the expansion of E. multilocularis in the Balkan region. Ordinary least squares, geographically weighted and multi-scale geographically weighted regressions were used to detect global and local drivers that influenced the prevalence in red foxes and golden jackals in the southwestern part of Hungary. Based on the study of 391 animals, the overall prevalence exceeded 18% (in fox 15.2%, in jackal 21.1%). The regression models revealed that the wetland had a global effect (β = 0.391, p = 0.006). In contrast, on the local scale, the mean annual precipitation (β = 0.285, p = 0.008) and the precipitation seasonality (β = - 0.211, p = 0.014) had statistically significant effects on the infection level. The geospatial models suggested that microclimatic effects might compensate for the disadvantages of a warmer Mediterranean climate. This study calls attention to fine-scale analysis and locally acting environmental factors, which can delay the expected epidemic fade-out. The findings of our study are suggested to consider in surveillance strategies.

Analysis of spatial characteristics and geographic weighted regression of tuberculosis prevalence in Kashgar, China

Number of cases of tuberculosis (TB) was higher than that of the national level in Kashgar, China. This study aimed to analyze the spatial and temporal distribution of TB and the relationship between TB and social factors, which can provide a reference for the prevention and control of TB. We applied spatial autocorrelation analysis to study the distribution of tuberculosis in Kashgar. We used a geographically weighted regression (GWR) model to analyze the relationship between TB and social factors. A total of 100,330 cases of TB in Kashgar from 2016 to 2021 were analyzed. The number of TB cases in Kashgar was higher in the east, lower in the west, and most elevated in the center. The highest cumulative number of cases was found in Shache county. Global Moran's I ranged from -0.212 to -0.549, and local spatial autocorrelation analysis identified four clusters. According to our analysis, the incidence of tuberculosis was negatively correlated among the regions of Kashgar, and the related causes need to be analyzed in depth in future studies. Per capita gross domestic product (GDP), number of medical institutions per capita, and total population influenced the incidence of tuberculosis in Kashgar. Based on our findings, we suggest some effective measures to reduce the risk of TB infection, such as improving the living standard, developing the regional economy, and distributing health resources rationally.

Spatial Modeling of COVID-19 Vaccine Hesitancy in the United States

Vaccine hesitancy refers to delay in acceptance or refusal of vaccines despite the availability of vaccine services. Despite the efforts of United States healthcare providers to vaccinate the bulk of its population, vaccine hesitancy is still a severe challenge that has led to the resurgence of COVID-19 cases to over 100,000 people during early August 2021. To our knowledge, there are limited nationwide studies that examined the spatial distribution of vaccination rates, mainly based on the social vulnerability index (SVI). In this study, we compiled a database of the percentage of fully vaccinated people at the county scale across the continental United States as of 29 July 2021, along with SVI data as potential significant covariates. We further employed multiscale geographically weighted regression to model spatial nonstationarity of vaccination rates. Our findings indicated that the model could explain over 79% of the variance of vaccination rate based on Per capita income and Minority (%) (with positive impacts), and Age 17 and younger (%), Mobile homes (%), and Uninsured people (%) (with negative effects). However, the impact of each covariate varied for different counties due to using separate optimal bandwidths. This timely study can serve as a geospatial reference to support public health decision-makers in forming region-specific policies in monitoring vaccination programs from a geographic perspective.