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Spatial video geonarratives and health: case studies in post-disaster recovery, crime, mosquito control and tuberculosis in the homeless.

Curtis A, Curtis JW, Shook E, Smith S, Jefferis E, Porter L, Schuch L, Felix C, Kerndt PR - Int J Health Geogr (2015)

Bottom Line: SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses.SVG can also be used to gain near-real time insight therefore supporting applied interventions.Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, GIS Health and Hazards Lab, Kent State University, #413 McGilvrey Hall, Kent, OH, 44242, USA. acurti13@kent.edu.

ABSTRACT

Background: A call has recently been made by the public health and medical communities to understand the neighborhood context of a patient's life in order to improve education and treatment. To do this, methods are required that can collect "contextual" characteristics while complementing the spatial analysis of more traditional data. This also needs to happen within a standardized, transferable, easy-to-implement framework.

Methods: The Spatial Video Geonarrative (SVG) is an environmentally-cued narrative where place is used to stimulate discussion about fine-scale geographic characteristics of an area and the context of their occurrence. It is a simple yet powerful approach to enable collection and spatial analysis of expert and resident health-related perceptions and experiences of places. Participants comment about where they live or work while guiding a driver through the area. Four GPS-enabled cameras are attached to the vehicle to capture the places that are observed and discussed by the participant. Audio recording of this narrative is linked to the video via time stamp. A program (G-Code) is then used to geotag each word as a point in a geographic information system (GIS). Querying and density analysis can then be performed on the narrative text to identify spatial patterns within one narrative or across multiple narratives. This approach is illustrated using case studies on post-disaster psychopathology, crime, mosquito control, and TB in homeless populations.

Results: SVG can be used to map individual, group, or contested group context for an environment. The method can also gather data for cohorts where traditional spatial data are absent. In addition, SVG provides a means to spatially capture, map and archive institutional knowledge.

Conclusions: SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses. SVG can also be used to gain near-real time insight therefore supporting applied interventions. Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

No MeSH data available.


A literal pin map showing the application of Narcan medication located in a non-profit medical facility in skid row. The map which was photographed on the wall of the facility shows the scale of the problem, but none of the other attribute information about each victim is recorded.
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Fig6: A literal pin map showing the application of Narcan medication located in a non-profit medical facility in skid row. The map which was photographed on the wall of the facility shows the scale of the problem, but none of the other attribute information about each victim is recorded.

Mentions: One of the biggest geospatial health challenges in the United States is how to capture health compromised cohorts with no typical address [36, 37]. Two examples are the “homeless”m and sex workers. The former by definition have no address, while for many sex workers there is no constant abode, often moving between temporary locations. Both groups have high health risk factors and we would expect them to show as hotspots if these cohorts are captured in normal surveillance data. As reliable spatial data are not available, we are left with three challenges: it is hard to know where spatially high concentrations of a disease occur, and who are at risk in primary proximate locations. Secondly, we have no idea as to the activity patterns and daily mobility paths that might help explain or predict disease spread. Linked to this issue, we have only a limited understanding of how and where best to intervene. Tuberculosis and sexually transmitted diseases are perpetual health concerns associated with the homeless and sex workers in Los Angeles, and yet there is a dearth of understanding about these cohorts, especially from a spatial perspective (Fig. 6).Fig. 6


Spatial video geonarratives and health: case studies in post-disaster recovery, crime, mosquito control and tuberculosis in the homeless.

Curtis A, Curtis JW, Shook E, Smith S, Jefferis E, Porter L, Schuch L, Felix C, Kerndt PR - Int J Health Geogr (2015)

A literal pin map showing the application of Narcan medication located in a non-profit medical facility in skid row. The map which was photographed on the wall of the facility shows the scale of the problem, but none of the other attribute information about each victim is recorded.
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4528811&req=5

Fig6: A literal pin map showing the application of Narcan medication located in a non-profit medical facility in skid row. The map which was photographed on the wall of the facility shows the scale of the problem, but none of the other attribute information about each victim is recorded.
Mentions: One of the biggest geospatial health challenges in the United States is how to capture health compromised cohorts with no typical address [36, 37]. Two examples are the “homeless”m and sex workers. The former by definition have no address, while for many sex workers there is no constant abode, often moving between temporary locations. Both groups have high health risk factors and we would expect them to show as hotspots if these cohorts are captured in normal surveillance data. As reliable spatial data are not available, we are left with three challenges: it is hard to know where spatially high concentrations of a disease occur, and who are at risk in primary proximate locations. Secondly, we have no idea as to the activity patterns and daily mobility paths that might help explain or predict disease spread. Linked to this issue, we have only a limited understanding of how and where best to intervene. Tuberculosis and sexually transmitted diseases are perpetual health concerns associated with the homeless and sex workers in Los Angeles, and yet there is a dearth of understanding about these cohorts, especially from a spatial perspective (Fig. 6).Fig. 6

Bottom Line: SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses.SVG can also be used to gain near-real time insight therefore supporting applied interventions.Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

View Article: PubMed Central - PubMed

Affiliation: Department of Geography, GIS Health and Hazards Lab, Kent State University, #413 McGilvrey Hall, Kent, OH, 44242, USA. acurti13@kent.edu.

ABSTRACT

Background: A call has recently been made by the public health and medical communities to understand the neighborhood context of a patient's life in order to improve education and treatment. To do this, methods are required that can collect "contextual" characteristics while complementing the spatial analysis of more traditional data. This also needs to happen within a standardized, transferable, easy-to-implement framework.

Methods: The Spatial Video Geonarrative (SVG) is an environmentally-cued narrative where place is used to stimulate discussion about fine-scale geographic characteristics of an area and the context of their occurrence. It is a simple yet powerful approach to enable collection and spatial analysis of expert and resident health-related perceptions and experiences of places. Participants comment about where they live or work while guiding a driver through the area. Four GPS-enabled cameras are attached to the vehicle to capture the places that are observed and discussed by the participant. Audio recording of this narrative is linked to the video via time stamp. A program (G-Code) is then used to geotag each word as a point in a geographic information system (GIS). Querying and density analysis can then be performed on the narrative text to identify spatial patterns within one narrative or across multiple narratives. This approach is illustrated using case studies on post-disaster psychopathology, crime, mosquito control, and TB in homeless populations.

Results: SVG can be used to map individual, group, or contested group context for an environment. The method can also gather data for cohorts where traditional spatial data are absent. In addition, SVG provides a means to spatially capture, map and archive institutional knowledge.

Conclusions: SVG GIS output can be used to advance theory by being used as input into qualitative and/or spatial analyses. SVG can also be used to gain near-real time insight therefore supporting applied interventions. Advances over existing geonarrative approaches include the simultaneous collection of video data to visually support any commentary, and the ease-of-application making it a transferable method across different environments and skillsets.

No MeSH data available.