Corrigendum to “Development and application of GIS-based analysis/synthesis modeling techniques for urban planning of Istanbul Metropolitan Area” [Adv. Softw. Eng. 40 (2) (2009) 128–140]

Baz, İbrahim; Geymen, Abdurrahman; Er, Semih Nogay

doi:10.1016/j.advengsoft.2009.10.013

Cited by 1 publication

(3 citation statements)

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“…The statistical unit of analysis for this study was the census tract, defined as a small, relatively permanent statistical subdivision of a county or equivalent entity established by the US Census Bureau 29 . We used Choropleth mapping with natural breaks (Jenks) classification 30 to visualize the geospatial distribution of the Latino/a/x population in each tract, an appropriate methodology when mapping unevenly distributed data such as population density 31 . Tracts were shaded proportionally to their assigned values on the map to allow the visualization of geospatial variation.…”

Section: Methodsmentioning

confidence: 99%

“…29 We used Choropleth mapping with natural breaks (Jenks) classification 30 to visualize the geospatial distribution of the Latino/a/x population in each tract, an appropriate methodology when mapping unevenly distributed data such as population density. 31 Tracts were shaded proportionally to their assigned values on the map to allow the visualization of geospatial variation. We mapped the following: The density of the Latino/a/x population in Tuscaloosa County by US census tract ( Appendix I , Figure 1 , [COMP: INSERT SDC1 URL HERE]).…”

Section: Methodsmentioning

confidence: 99%

“…29 We used Choropleth mapping with natural breaks (Jenks) classification 30 to visualize the geospatial distribution of the Latino/a/x population in each tract, an appropriate methodology when mapping unevenly distributed data such as population density. 31 Tracts were shaded proportionally to their assigned values on the map to allow the visualization of geospatial variation. We mapped the following: We manually collected and geocoded the primary care provider and transit route data into GIS 26 using ESRI software, ArcGIS 10.6.1 32 to map the distribution of primary healthcare providers alongside public transit accessibility.…”

Section: Geographic Information Systems (Gis) Analysesmentioning

confidence: 99%

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Geographic Access to Primary Healthcare Services among Latinos/as/x in Western Alabama

Morales-Alemán

Ferreti

et al. 2022

Southern Medical Journal

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Objectives: Alabama's Latino/a/x population grew 278% from 2000 to 2018. Tuscaloosa County, located in the largely rural region of western Alabama, also experienced a significant influx of Latino/as/x during this time frame. Geographic healthcare access (GHA) to primary care and hospitals is crucial for immigrant Latino/as/x to care for their health, but few studies have characterized it. The goals of this article were to describe the availability (defined as number of provider locations) and accessibility (defined as travel impedance between potential patients and provider locations) of primary healthcare services and to discuss potential strategies to address these healthcare access challenges.Methods: We drew data from the US Census Bureau, American Community Survey 5-year estimates, Blue Cross Blue Shield national doctor and hospital finder database, the Alabama Department of Public Health, and Tuscaloosa Transit Authority. We used geographic data, geographic information systems, and spatial analyses to characterize the availability and accessibility of primary care services and hospitals for Latinos/as/x in Tuscaloosa County using ESRI, ArcGIS 10.6.1. We showed the distribution of Latinos/as/x by census tract with choropleth mapping and mapped primary healthcare providers alongside public transit routes and hospital driving times to support our findings.Results: This work demonstrated that Latinos/as/x in Tuscaloosa County were concentrated in more rural areas surrounding the county's city center, presenting significant barriers to GHA. These areas had fewer primary care providers and limited public transit. Many Latinos/as/x in this county had to travel ≥45 minutes to a hospital.Conclusions: Outreach and technology-based approaches, including home visit programs, mobile health units, and telemedicine, may be particularly important in bridging the GHA gaps for this and other largely rural populations the southeastern United States. Some of this potential was unlocked during the coronavirus disease 2019 crisis. These gains should be leveraged toward sustainable healthcare access initiatives for rural Latino/a/x populations.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…29 We used Choropleth mapping with natural breaks (Jenks) classification 30 to visualize the geospatial distribution of the Latino/a/x population in each tract, an appropriate methodology when mapping unevenly distributed data such as population density. 31 Tracts were shaded proportionally to their assigned values on the map to allow the visualization of geospatial variation. We mapped the following: We manually collected and geocoded the primary care provider and transit route data into GIS 26 using ESRI software, ArcGIS 10.6.1 32 to map the distribution of primary healthcare providers alongside public transit accessibility.…”

Section: Geographic Information Systems (Gis) Analysesmentioning

confidence: 99%

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