20: GeoHealth Flashcards
GeoHealth Lab
Partnership between UC and Ministry of Health Functions: -research -studentships Policy relevant research Spatial decision support health policy Intersection of GIS and health research -how the environment affects health
Geospatial and health
Geospatial science: a discipline that focuses on using info tech to understand people, places, and processes of the earth
Geographic Info Systems: a tech that is used to view and analyse data from a geographic perspective
Geohealth: health + GIS
- people + place + time
- determinants of disease and ill health
- health care service provision
Why use GIS in Health?
- advanced methods for spatial analyses
- spatial statistics
- exploration of spatial pattern
- visualisation and presentation for non-geographers (doctors and specialists)
Disease mapping
- virtual description of spatial variations of the disease
- maps of incidence, visual identification of areas with high risk
example: cartogram or point/dot map
Geographic correlation studies
analysis of associations among health outcomes and environmental / socioeconomic / demographic / other factors
model together to try to identify the driver(s)
Analyses of spatial patterns
- exploration of spatial and spatiotemporal patterns in data
- hot and cold spots, disease clusters, source identification
Health data types (4)
Case-event data
-locations of individual cases of a disease and other information about the person that might be attributed to the disease like obesity
Irregular lattice data
-measures aggregated/averaged to the level of census tracts or other type of administrative district
Regular lattice data
-measures aggregated/averaged to a regular grid (typically arising from remote sensing)
Geostatistical data
-measurements sampled at point locations
Important aspects of working with health data
PRIVACY and ETHICS
- health and medical data are private, confidential and sensitivity, need to be aware of this in management and presentation of the data, requires specific ethical procedures
- aggregated, anonymized or incomplete data sets
- public health reporting systems and medical registries are committed to the protection of privacy
- usefulness of the local scale analysis vs privacy protection
- availability, accessibility and restrictions
- IDI - integrated data infrastructure (Stats NZ provide anonymised data about the population, can join info from health care with other info)
mGeoHealth
- use of location based applications for smart devices in health
- utilise readily available devices, which people already have, enhanced by suitable software
- mobility and movement as a source of exposure to environments
mGeoHealth pros/cons
Pros
- good dynamic data and insights
- tech is easy to fix
- use of familiar device
- accuracy (time and space)
- no manual entry
Cons
- volume of data and storage
- tech can be pricey (develop app, servers for data)
- energy demanding
- data privacy
- level of tech skills
- peoples habits and behaviour affect accuracy and data quality
For consideration
- ethics
- data ownership (licensing)
- do not forget the people (different skills)
Sensing City
- measurements of environmental data in the city
- combination of existing air quality monitoring network and deployment of low-cost loT air quality sensors
- investigate how this is associated with COPD symptoms
Air pollution exposure
created a surface of air pollution levels for Christchurch with data from sensors around the city
linked air pollution data to movement of individuals with COPD
Immunisation in NZ
Identify where immunisation is lower, to focus on those place to help educate people and ensure services are available, linked to areas with lower socioeconomic status
More examples
Studied proximity of bottle shops to crime
Studied mental health in relation to visibility of the ocean
Access to health services
Sources of outbreaks
Geoprofiling - geographic profiling - trying to find the source / location of the outbreak based on the spatial behaviour of the disease
Future of GIS and Health
- virtual / augmented reality
- geospatial artificial intelligence (GeoAI) and machine learning
- unmanned aerial vehicles (UAVs/Drones)
- location intelligence
- IoT (internet of things)
- personalised location-based services
- cognitive digital maps
