Rohan Fisher - 2011
Dr John snow’s cholera map the beginnings of spatial epidemiology
• 1854 Broad Street outbreak.
• Health mapping for what? • What is GIS? • Health mapping applications • Case study – Eastern Indonesia
Improving health service delivery Short term
Disaster response, epidemic outbreak
Medium term
Inform resource allocation A tool for monitoring public health indicators, education and advocacy. and health data Developing implementing and communication.
Providing critical infrastructure & need assessments for rapid response.
monitoring public health research/initiatives.
Longer Term
Inform policy and Infrastructure investment
Model access to health services and evaluating public health initiatives.
• Spatial epidemiology, which covers the exploration description, and modeling of the spatiotemporal incidence of disease and related environmental phenomena, the detection and analysis of disease clusters and patterns, causality analysis, and the generation of new disease hypotheses.
• The geography of healthcare systems, the planning, management, and delivery of suitable health services, ensuring among other things adequate patient access, after determining healthcare needs of the target community and service catchment zones Preventive and health promotion activities form part of these services.
– Visualisation revealing trends and interrelationships • Monitoring Services • Advocacy and education
– Epidemiological analyses • Analysing Spatial Clusters and environmental hazards • Analysing the risk and spread of infectious diseases • Exploring the ecology of vector borne diseases
– Service Availability Mapping (SAM) • Access analysis. • Locating services
• Introduction to GIS – Information representation – Database connection – Software – Field data collection technology – Remote sensing/satellite data – Participatory GIS • Introduction to Geodesy – Projections & Coordinate systems
Information representation • Vector data – Points (locations) – Lines (Length, and location) – Polygons (Length, area, and location)
• Raster Data – Pixels
Points eg. •Location of health infrastucture •A residence •A sample site
Points eg. •Location of health infrastucture •A residence •A sample site Lines eg. •Roads, Power Lines •Rivers
Points eg. •Location of health infrastucture •A residence •A sample site Lines eg. •Roads, Power Lines •Rivers Polygons eg. •Administrative boundaries •Tenure •Biophsyical attribute (Veg, Soil) •Catchment area
Demo - OpenJump
•Satellite imagery •CAT Scans •Digital elevation models •Population distribution Girds •Rainfall Grids
Risk Factor Modeling 2
8
4
1
3 +
22
14 3
Demo – Raster Risk
5 =
30
18 4
Data connection: • Vector data links to a data table of attributes. • Raster data generally has only one value.
GIS Software Proprietary -ESRI (ARC GIS) -MAP Info
Web Based Ushadi
Free Ware Epi Info Health Mapper
Open Source QGIS OPEN JUMP
What is Epi Info™? Physicians, nurses, epidemiologists, and other public health workers lacking a background in information technology often have a need for simple tools that allow the rapid creation of data collection instruments and data analysis, visualization, and reporting using epidemiologic methods. Epi Info™, a suite of lightweight software tools, delivers core ad-hoc epidemiologic functionality without the complexity or expense of large, enterprise applications.
Health Mapper
Field data collection: Hardware Software Proprietary GPS - Locations ArcPad PDA – Data + Locations Freeware Mobile Phone – SMS Cybertracker reporting & Epi-collect surveillance Frontline SMS
• Field data collection tool. Collecting georeferenced data for direct export to a GIS. • Used extensively by indigenous ranger groups to collect enviromental information such as the siteing of fishing boats or ghost nets. • http://www.cybertracker.org/
EpiCollect
Satellite data • Google earth • Free • Very low temporal resolution • High spatial resolution • Web visualisation
Satellite data • Google earth • Free • Very low temporal resolution • High spatial resolution • Web visualisation
• MODIS • Very high temporal resolution • Near real time assessments • Very good for fire monitoring.
Satellite data • Google earth • Free • Very low temporal resolution • High spatial resolution • Web visualisation
• MODIS • Very high temporal resolution • Near real time assessments • Very good for fire monitoring.
• Hi-resolution • Expensive • Detailed disaster assessments.
Participatory GIS – Community mapping – Empowering local decision making Improving data quality, analysis and communication – GIS as appropriate technology
• World Grid Systems • Latitude + Longitude • Degrees, Minutes, Seconds • Default format for GPS – data logger/health mapper
• Projections (Universal Transvers Mecator) • World divided into zones • Easting's and Northing's (each unit is 1 meter) • More intuitive
– Visualisation communication and education. – Epidemiological analyses • Analysing Spatial Clusters and environmental hazards • Analysing the risk and spread of infectious diseases • Exploring the ecology of vector borne diseases
– Service Availability Mapping (SAM) • Access analysis and locating services • Monitoring Services
– Advocacy communication and education. • Data reporting • Practice Health AtlasTM (PHA) • Malaria Atlas
– Monitoring Services • Stop Stock outs – SMS Reporting – Web Posting – Participatory GIS - community activism
• The Practice Health Atlas is a decision support tool, designed by the Adelaide Western General Practice Network, for General Practitioners (GPs), Practice Managers and other Practice staff. •
http://healthatlas.org.au/Sample_PHA_r pt_v9.pdf
• The Practice Health Atlas is a decision support tool, designed by the Adelaide Western General Practice Network, for General Practitioners (GPs), Practice Managers and other Practice staff. •
http://healthatlas.org.au/Sample_PHA_r pt_v9.pdf
Taking action to eliminate stock-outs •District health management teams should be participatory to encourage transparency and accountability in the supply chain •Monitoring of availability of medicines at the health facilities •Advocacy for 100% availability of essential medicines •Advocacy for increased funding for essential medicines
http://stopstockouts.org/ushahidi/
Taking action to eliminate stock-outs •District health management teams should be participatory to encourage transparency and accountability in the supply chain •Monitoring of availability of medicines at the health facilities •Advocacy for 100% availability of essential medicines •Advocacy for increased funding for essential medicines
http://stopstockouts.org/ushahidi/
• Analysing Spatial Clusters and environmental hazards – Pollution – Diarrhea
• Analysing epidemiology of antibiotic use and resistance • Analysing the risk and spread of infectious diseases – Tuberculosis
• Exploring the ecology of vector borne diseases – Melioidosis mapping – Dengue mapping and climate change
• Analysing Spatial Clusters – Finding correlations
Spatial patterns of fetal loss and infant death in an arsenic-affected area in Bangladesh
Nazmul Sohel, Marie Vahter, etal International Journal of Health Geographics 2010, 9:53 http://www.ij-healthgeographics.com/content/9/1/53
Use of a geographic information system to track smelter-related lead exposures in children: North Lake Macquarie, Australia, 1991–2002 Alan Willmore, Tim Sladden, Lucy Bates, etal International Journal of Health Geographics 2006, 5:30 (19 July 2006) http://www.ijhealthgeographics.com/content/5/1/30
A spatial approach for the epidemiology of antibiotic use and resistance in community-based studies: the emergence of urban clusters of Escherichia coli quinolone resistance in Sao Paulo, Brasil
Carlos RV Kiffer, Eduardo CG Camargo, Silvia E Shimakura, Paulo J Ribeiro, Trevor C Bailey, Antonio CC Pignatari, Antonio MV Monteiro International Journal of Health Geographics 2011, 10:17 (28 February 2011)
Selling points influence zones to ciprofloxacin in S達o Paulo city, 2002.
E. coli CIP resistant cluster emergence was detected and significantly related to usage. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density.
S達o Paulo city estimated residual (log) risk map showing hotspots of ciprofloxacin.
Using GIS technology to identify areas of tuberculosis transmission and incidence
Average incidence by zip code.
Using GIS technology to identify areas of tuberculosis transmission and incidence
Percent of patients genotypically cluster by zip code (1993 – 2000).
Using GIS analysis combined with molecular epidemiological surveillance may be an effective method for identifying instances of local transmission. These methods can be used to enhance targeted screening and control efforts, with the goal of interruption of disease transmission and ultimately incidence reduction. Patrick K Moonan, etal, International Journal of Health Geographics 2004, 3:23 (13 October 2004)
http://www.ij-healthgeographics.com/content/3/1/23
Extracted DNA from more than 800 soil samples throughout the Top End to identify the bacterium in soil. These results were used to create a map to help predict the location of potential melioidosis “hot spots� where people may be at an increased risk of catching the disease. http://www.cdu.edu.au/newsroom/origins/edition1_2010/researchersclosein.pdf
Dengue and climate change in Australia: predictions for the future should incorporate knowledge from the past RC Russell, BJ Currie, MD Lindsay, JS Mackenzie‌ - Med J Aust, 2009 - mja.com.au
http://www.mja.com.au/public/issues/ 190_05_020309/rus10887_fm.pdf
•Simple linear buffer
•Simple linear buffer •Network Analysis
•Simple linear buffer •Network Analysis •Grid Analysis
Demo – AcessMOD
MODIS IMAGE
• One of the poorest regions in eastern Indonesia • Population of around four million. • 85% working as low income or subsistence farmers. • 4th highest incidence of Malaria in Indonesia. •Neonatal and Maternal mortality rates more than national average.
Data collection and analysis at the local level can increase data understanding and data quality.
Data Collection
‘The experts’
Data Analysis Understanding Data
Action
1. No centralised database 2. No need for data base development knowledge 3. Not web based
Web GIS not the solution Access (% Population) 80%
70%
60%
50%
40%
30%
20%
10%
0% Africa
Indonesia
WORLD TOTAL
Europe
Oceania / Australia
North America
DECREASING HARDWARE COSTS
CONVERGENCE OF GPS/ MOBILE-PHONE/ PDA HARDWARE
DECREASING HARDWARE COSTS
CONVERGENCE OF GPS/ MOBILE-PHONE/ PDA HARDWARE
FREE/OPEN-SOURCE SPATIAL DATA SOFTWARE
DECREASING HARDWARE COSTS
Three components 1. Integration of existing data for spatial visualisation 2. Rapid field data collection for: • Updating health infrastructure data • Conducting Household surveys
3. Service Availability Mapping (SAM).
Kabupaten Kupang
Kota Kupang
Ngada
• 3 Days training • Clear multimedia training package providing: • All software • Base spatial data • Problem based tutorials.
• Follow up mentoring. • Some additional training using AccesMod for service availability mapping.
Update Mei 2009 Puskesmas : 10 Pustu : 33 Polindes : 46 (Poskesdes : 6)
Dokter, 2008
Perawat, 2008
77
Bidan, 2008
Keberadaan Bidan, 2008
78
1 Hr travel time from health infrastructure.
Clinic
Community Health Center
Birth Centre
GIS can be appropriate technology to empower decentralised decision making in low resource, internet free environments.
–Visualisation revealing trends and interrelationships –Epidemiological analyses –Service Availability Mapping
Talk on Dr John Snows cholera map. http://www.ted.com/talks/steven_johnson_tours_the_ghost_map.html International Journal of Health Geographics http://www.ij-healthgeographics.com/ EpiInfo http://wwwn.cdc.gov/epiinfo/ Health Mapper http://www.who.int/health_mapping/tools/healthmapper/en/ Stop Stockouts http://stopstockouts.org/ Frontline SMS http://www.frontlinesms.com/ EpiCollect http://www.epicollect.net/ Malaria Atlas http://www.map.ox.ac.uk/ Eastern Indonesian Health Project http://healthpslp.cdu.edu.au/index.html
• Kamel Boulos, MN, Roudsari, AV & Carson, ER 2001, 'Health geomatics: An enabling suite of technologies in health and healthcare', Journal of Biomedical Informatics, vol. 34, no. 3, pp. 195-219. • Grinzi, P 2008, GIS and General Practice: Where are we going and when will we get there...?, Australian Primary Health Care Research Institute, Canberra. • Fisher, R & Myers, B 2011, 'Free and simple GIS as appropriate for health mapping in a low resource setting: a case study in eastern Indonesia ', International Journal of Health Geographics, vol. 11.