This document describes a heatmap analysis of health facility distribution in Haiti. It obtains hospital location data from OpenStreetMap, population data from haitidata.org, and generates a heatmap based on travel times to the nearest hospital. The analysis incorporates population density to better evaluate service gaps. It was created using Django, GRASS, PostgreSQL/PostGIS, and other open source technologies. The roadmap includes improving the algorithm and collecting better data with the OSM community.

1. HaHeatMap
Health facilities distribution analysis in Haiti
Sunday, December 4, 2011

2. The problem
How can we evaluate the distribution of
a service (e.g. hospitals)?
This information can be useful to:
Show the gap of ser vices
Improve future planning
Make ser vices more efficient
Correlate population with ser vices
Sunday, December 4, 2011

3. Our solution
Get hospitals from OpenStreetMap
Get street information from
OpenStreetMap
Build heatmap based on time-travel routes
to the nearest hospital
Get population infromation from
haitidata.org
Elaborate the informations with population
density
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4. Algorithm + GRASS magic
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5. Algorithm + GRASS magic
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6. Algorithm + GRASS magic
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7. Other features
User can easily
add new data
update and improve information
Data come back to OpenStreetMap
Improve geographic open data
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8. Technologies
Django
GRASS
JQuery / AJAX
PostgreSQL / PostGIS
OpenLayers
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9. Roadmap
Improving the algorithm to take into
account the population density
efficiently
Collect better data involving the OSM
community
Extend the platform to other user
stories
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10. The team
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11. Github repo:
https://github.com/volpino/FindMySpot
RHoK Solution:
http://www.rhok.org/solutions/haheatmap
References:
http://haitidata.org/
http://www.openstreetmap.org/
Sunday, December 4, 2011