Ten Ways GIS and Spatial Analytics Can Be Used for Community Engaged Health Research

Clearly, GIS/GPS is a major tool and resource for the mapping, targeting, and elimination of health disparities at the community level. There are at least ten specific ways participatory GIS and spatial analytics can be used to support and enhance community-based participatory health disparities research:

  • 1. Data collection, integration, and management. Geographic information systems can be used to develop a robust data management and analytical framework. The framework facilitates the creative use of large-scale datasets for health monitoring and tracking and has a strong potential to yield effective multilevel interventions (Figure 4.4). Integration of place, time, and person- level health measures into the design of multilevel interventions through the use of smart and connected mobile health monitoring devices and sensors yields robust geospatial measures. Robust data services and study and analytical protocols must always take data collection, processing and manipulation, quality assurance and quality controls, analysis, sharing, protection, interpretation, storage, and best practices of metadata documentation into consideration.
  • 2. Activity-level monitoring. Researchers and communities can use personal air quality or physical activity monitors (wearable motion- or chemical-sensing technologies) equipped with high precision GPS sensors with submeter accuracy to collect robust and unbiased geospatial measures.
  • 3. Understanding spatial trajectories of life course exposure. Spatial trajectories of individuals collected with GIS/GPS tools can provide more accurate assessment of exposures to environmental or social factors when integrated with detailed GIS data, especially the data and knowledge of spatial and temporal variations of disease risk factors. Further, GIS/GPS can help researchers and communities establish reliable activity patterns and life course profiles of cohorts with a wide spectrum of environmental exposure at different spatial scales. This requires proper alignments, matching, and harmonization of primary and secondary sources of spatial and temporal datasets.
  • 4. Quantification of robust and unbiased geospatial measures. Examples of common geospatial measures include:

a. Neighborhood safety measure (crime and street lights data)

b. Food access measure (spatial access such as proximity of restaurants, groceries, and farmers markets; temporal access measures; and spatiotempo- ral access measures)

c. Physical activity measure (built environment/street connectivity, land use mix, recreational facilities, walkability score, monitors and trackers)

A data science approach that integrates big geospatial data, including citizen sensors, data streams, and archived data

Figure 4.4 A data science approach that integrates big geospatial data, including citizen sensors, data streams, and archived data.44

d. Derive near/proximity and other geospatial measures to support interventions (nearest restaurants, nearest healthcare provider, etc.)

  • 5. Asset mapping and tracking. Identifying key community resources (assets) and tracking them in a timely manner can facilitate the understanding of disease dynamics and community burden.
  • 6. Community mapping and health needs assessment. For example, participants can create images containing GPS data and map community resources and develop a virtual map showing a transect walk through the community enhanced by photos of specific locations for use in a needs assessment dialogue. Walking and talking to experience place has been promoted as a strong methodology for gathering rich and diverse qualitative data. Figure 4.1 shows a framework that incorporates geospatial measures for community health needs assessment.
  • 7. Risk assessment and risk management. Studies have applied risk assessment and risk management concepts to develop effective guidelines and policies to mitigate and manage environmental and occupational hazards and improve human health outcomes.
  • 8. Mapping disease risk. GIS/GPS tools can be used to map settings and study locations, participants, activity pattern/routines, health outcomes, healthcare providers, and risk factors. The use of GIS/GPS has been proven to be effective in many scientific reports, primarily in maximizing geographic targeting and intervention options.
  • 9. GIS-based multicriteria evaluation and decision-making. Critical community dialogue can lead to valuable input for ranking and assigning weights to important health measures and outcomes and risk factors. The identification of community health priorities using a multicriteria approach helps to target intervention efforts and resources in the right places and direction.
  • 10. Visualization and map analytics. Photo mapping, photovoice, data visual analytics and strategies, and other geovisualization tools can aid the effective presentation and communication of community health information.
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