Mapping and visualizing the location HIV service providers: An exploratory spatial analysis of Toronto neighborhoods

AIDS Care ◽  
2005 ◽  
Vol 17 (3) ◽  
pp. 386-396 ◽  
Author(s):  
Christopher Fulcher ◽  
Catherine Kaukinen
2019 ◽  
Vol 4 (Suppl 5) ◽  
pp. e000832 ◽  
Author(s):  
T A Robin ◽  
Marufa Aziz Khan ◽  
Nazmul Kabir ◽  
Sk Towhidur Rahaman ◽  
Afsana Karim ◽  
...  

The application of a geographic information system (GIS) in public health is relatively common in Bangladesh. However, the use of GIS for planning, monitoring and decision-making by local-level managers has not been well documented. This assessment explored how effectively local government health managers used maps with spatial data for planning, resource allocation and programme monitoring. The United States Agency for International Development-funded MaMoni Health Systems Strengthening project supported the introduction of the maps into district planning processes in 2015 and 2016. GIS maps were used to support the prioritisation of underserved unions (the lowest administrative units) and clusters of disadvantaged communities for the allocation of funds. Additional resources from local government budgets were allocated to the lowest performing unions for improving health facility service readiness and supervision. Using a mixed-methods approach, the project evaluated the outputs of this planning process. District planning reports, population-based surveys, local government annual expenditure reports and service availability and utilisation data were reviewed. The goal was to determine the degree to which district planning teams were able to use the maps for their intended purpose. Key informant interviews were conducted with upazila (subdistrict) managers, elected government representatives and service providers to understand how the maps were used, as well as to identify potential institutionalisation scopes. The project observed improvements in health service availability and utilisation in the highest priority unions in 2016. Quick processing of maps during planning sessions was challenging. Nevertheless, managers and participants expressed their satisfaction with the use of spatial analysis, and there was an expressed need for more web-based GIS both for improving community-level service delivery and for reviewing performance in monthly meetings. Despite some limitations, the use of GIS maps helped local health managers identify health service gaps, prioritise underserved unions and monitor results.


AIDS Care ◽  
2016 ◽  
Vol 28 (9) ◽  
pp. 1119-1123 ◽  
Author(s):  
Christopher O. Obong'o ◽  
Latrice C. Pichon ◽  
Terrinieka W. Powell ◽  
Andrea L. Williams

2016 ◽  
Vol 58 (2) ◽  
pp. S101-S102
Author(s):  
Nicole Liddon ◽  
Lisa Carver ◽  
Leah Robin ◽  
Christopher Harper ◽  
Andrew Herbert ◽  
...  

2018 ◽  
Vol 32 (11) ◽  
pp. 468-476 ◽  
Author(s):  
Lauren B. Beach ◽  
George J. Greene ◽  
Peter Lindeman ◽  
Amy K. Johnson ◽  
Christian N. Adames ◽  
...  

2020 ◽  
Author(s):  
Rob Stephenson ◽  
Alison Walsh ◽  
Tanaka Chavanduka ◽  
Gregory Sallabank ◽  
Keith Horvath ◽  
...  

BACKGROUND Central to measuring the impact of the COVID-19 epidemic on HIV is understanding the role of loss of access to essential HIV prevention and care services created by clinic and community-based organization closures. OBJECTIVE In this paper, we use data from a large, randomized controlled trial for adolescent GBMSM aged 13-18 to map HIV prevention services in four corridors of the US heavily impacted by HIV METHODS We identified and mapped LGBTQ+ friendly services offering at least one of the following HIV-related services: HIV testing; STI testing, PrEP/PEP; HIV treatment and care; other HIV-related services in 109 counties across four major interstate corridors heavily affected by HIV (US Census regions: Pacific (San Francisco, CA to San Diego, CA; 14 counties); South-Atlantic (Washington, DC to Atlanta, GA; 57 counties). RESULTS There were a total of 831 LGBTQ+ youth-friendly HIV service providers across the 109 counties. There was a range of LGBTQ+ youth-friendly HIV-service provider availability across counties (range: 0-14.33 per 10,000 youth aged 13-24 (IQR: 2.13), median: 1.09); 9 (8.26%) analyzed counties did not have any LGBTQ+ youth-friendly HIV service providers. The Pearson correlation coefficient for the correlation between county HIV prevalence and LGBTQ+ youth-friendly HIV service provider density was 0.16 (p=0.09), suggesting only a small, non-statistically significant linear relationship between a county’s available LGBTQ+ youth-friendly HIV service providers and their HIV burden. CONCLUSIONS As the COVID-19 epidemic continues, we must find novel, affordable ways to continue to provide sexual health, mental health and support services to LGBTQ+ youth. CLINICALTRIAL NA


PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0249740
Author(s):  
Rob Stephenson ◽  
Alison R. Walsh ◽  
Tanaka M. D. Chavanduka ◽  
Gregory Sallabank ◽  
Keith J. Horvath ◽  
...  

Background Central to measuring the impact of the COVID-19 pandemic on HIV is understanding the role of loss of access to essential HIV prevention and care services created by clinic and community-based organization closures. In this paper, we use a comprehensive list of HIV prevention services in four corridors of the US heavily impacted by HIV, developed as part of a large RCT, to illustrate the potential impact of service closure on LGBTQ+ youth. Methods We identified and mapped LGBTQ+ friendly services offering at least one of the following HIV-related services: HIV testing; STI testing; PrEP/PEP; HIV treatment and care; and other HIV-related services in 109 counties across four major interstate corridors heavily affected by HIV US Census regions: Pacific (San Francisco, CA to San Diego, CA); South-Atlantic (Washington, DC to Atlanta, GA); East-North-Central (Chicago, IL to Detroit, MI); and East-South-Central (Memphis, TN to New Orleans, LA). Results There were a total of 831 LGBTQ+ youth-friendly HIV service providers across the 109 counties. There was a range of LGBTQ+ youth-friendly HIV-service provider availability across counties (range: 0–14.33 per 10,000 youth aged 13–24 (IQR: 2.13), median: 1.09); 9 (8.26%) analyzed counties did not have any LGBTQ+ youth-friendly HIV service providers. The Pearson correlation coefficient for the correlation between county HIV prevalence and LGBTQ+ youth-friendly HIV service provider density was 0.16 (p = 0.09), suggesting only a small, non-statistically significant linear relationship between a county’s available LGBTQ+ youth-friendly HIV service providers and their HIV burden. Conclusions As the COVID-19 pandemic continues, we must find novel, affordable ways to continue to provide sexual health, mental health and other support services to LGBTQ+ youth.


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