Census characteristics of Illinois sober living homes: A geographic information systems study

Callahan, Sarah; Hwang, Sungsoon; Isler, Brandon; Wiedbusch, Elzbieta; Jason, Leonard A.

doi:10.1080/10852352.2019.1633067

Cited by 3 publications

(1 citation statement)

References 13 publications

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“…These same studies also used different statistical modeling approaches to identify the correlation between different variables and homelessness. Beyond the mapping and visualization, hotspot analysis using the kernel density functions is the most prominently used spatial analysis techniques in the reviewed articles 9,10,18,22,24,28-30,34,36 . However, a few studies also used global and local Moran’s I to identify the spatial autocorrelation between the locations and distribution 9,12 .…”

Section: Discussionmentioning

confidence: 99%

Applications of geospatial analyses in health research among homeless people: A systematic scoping review of available evidence

Ahasan

Alam

Chakraborty

et al. 2021

Preprint

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BackgroundThe coronavirus pandemic visualized the inequality in the community living standards and how housing is a fundamental requirement to ensure a livable environment. However, even before the pandemic, unequal housing access resulted in more than 150 million homeless people worldwide, and more than 22 million new people were added to this inventory for climate-related issues. This homeless population has a counterproductive effect on the social, psychological integration efforts by the community and exposure to other severe health-related issues.MethodsWe systematically identified and reviewed 24 articles which met all three requirements we set forth-i. samples include homeless people, ii. focused on public health-related issues among the same group of people, and iii. used geospatial analysis tools and techniques in conducting the research.ResultOur review findings indicated a major disparity in the geographic distribution of the case study locations-all the articles are from six (6) countries-USA (n = 16), Canada (n = 3), UK (n = 2), and one study each from Brazil, Ireland, and South Africa. Majority of the studies used spatial analysis tools to identify the hotspots, clustering and spatial patterns of patient location and distribution. ArcGIS is the most frequently used GIS application, however, studies also used other statistical applications with spatial analysis capabilities. These studies reported relationship between the location of homeless shelters and substance use, discarded needles, different infectious and non-infectious disease clusters.ConclusionAlthough, most studies were restricted in analyzing and visualizing the trends, patterns, and disease clusters, geospatial analyses techniques can be used to assess health problems such as disease distributions and associated factors across communities. Moreover, health and services and accessibility concerns could be well addressed by integrating spatial analysis into homelessness-related research. This may facilitate policymaking for health-issues among the homeless people and address health inequities in this vulnerable population.

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