How to use the Network Analyst to determine service areas for reanimation of patients with asystoles. Klick here to download the final result before proceeding.
When a heart stops beating (asystole), there are only few
minutes left for reanimation. The last effort to come back to life is much more
successful when using a defibrillator or done by experts. Recently, there were
several defibrillators installed in Cologne that can be operated even by an
amateur and should increase the survival rate in case of an asystole.
Nevertheless, the success of a reanimation is strongly connected to time. While
an instant treatment can save the patient’s life in about 90 per cent of the
cases, the survival rate decreases by 7 – 10 per cent per minute. Therefore, it is crucial to be close to either one of these
public defibrillators or to be in a close range to an ambulance.
The impressive open data site Offene Daten: Köln provides the geographer with a bunch of useful geodata for whole Cologne. Besides
detailed vector data for roads and addresses (a 157.415 point shapefile!!!), you will also find a dataset on the defibrillators. I only had to geocode the
sites of ambulances, which are most of the time also the city’s fire stations.
To prepare the analysis, the road data had to be manipulated because the
research should also include sites of ambulances that are close but not in
Cologne’s municipal area. Thus, I digitized some of the major roads that would
be used by the ambulance when having an operation in the city. To digitize the
access roads, QGIS and the OpenStreetMap WMS turned out to be comfortable
tools. It is important to create a new feature for every junction. Otherwise
you will experience problems in the analysis afterwards.
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| Digitizing access roads with OSM WMS |
After preparing the route data, I moved to ArcMap because I
still struggle using the QGIS pgRouting Plugin.
ArcMap includes the Network Analyst, which is quite handy for such kind of
analysis.
Before starting to create service areas for the
defibrillators and the ambulances, you will have to build a road Network Dataset that can then be used in the Network Analyst. By creating the service areas,
the Network Analyst will take different locations (e.g. fire stations and
defibrillators) and the road network to calculate polygons that show the accessibility
based on your defined distances.
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| Creating a Network Dataset with ArcMap |
According to the literature an asystole cannot be survived
more that 8 to 10 minutes in most cases. Therefore, I decided to estimate the
distances that you can cover by foot and by ambulance in this period. For the
defibrillators, it seemed to be reasonable to take a decreasing running speed
of around 18 to 11 km/h and for the ambulances I decided to assume an average
speed of 50 km/h. You should not forget that the utilization of the defibrillator
usually does not only include the running to the defibrillator but also the
rushing back. Thus, the covered distance for the defibrillators must be halved.
For the ambulance, you can also include one minute for the emergency call and the departure of the vehicle.
When calculating the service areas considering the coverage
per minute, you will have polygons that indicate where help arrives within 1 to
9 minutes.
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| Service areas of defibrillators and ambulances |
Right now, there is only one major mistake. Due to the
overlapping of the defibrillators service areas, some areas are coloured red
although they are much better covered by the ambulance. To fix this issue, you
will have to merge the data and either set a hierarchy for the displaying of
the areas (high preference for minute 1, low preference for minute 8) or
clip and intersect some data.
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| Both Service Area Layers have to be combined to recieve final result |
Initially, I planned another style of visualization, which
is why I did not bother that much on how to present the polygons. Due to the
availability of a point Shapefile that includes every address in Cologne, I
decided to symbolize them according to the appropriate service area.
By this kind of presentation, the viewer is enabled to zoom in and identify its
own house or even search for it in a web based map.
The addresses can be extended by the attribute value
indicating the minutes until arrival of help by performing a spatial join. Using the merged service areas and the point Shapefile, it is possible to
only join the minimum value of an attribute to the target layer. This option
resolves the problem of overlapping polygons with different values and stores
the minimal arrival time for each address independent on whether it is served
by a public defibrillator or the ambulance.
For the final styling I switched back to QGIS because I feel
much more comfortable and powerful using the QGIS Print Composer. Due to storage limitations and diverse issues, my plans to
also publish the data in a web map are not yet implemented but I hope to find a
satisfying solution very soon.
Above the not really satisfying approach to put the data in an acceptable web map. I guess I will still have to work on this issue. At least it offers you the option to identify single features. If you go to the official web map, you can search for your adress using the input field on the upper right.
To enjoy the whole map, I recommend to download this PDF file and zoom in.
You can see, that there are only few locations that are endangered drastically. The city's center is well covered by ambulances and defibrillators. It would be interesting to play a little bit with the variables for the coverage of the ambulances and defibrillators. Possibly my assumptions are over- or underestimating the reality. Moreover, it is likely that I missed one or more sites of ambulance vehicles.
