Drunk driving map with all-Ontario coverage and video

TORONTO STAR STAFF

Link to the map

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As I said in an earlier post, our tools for producing online maps have become much more sophisticated over the last year and a half, and it’s tempting to go back to some of our earlier data and give it the presentation it deserves.

This week, we’re taking another look at our drunk driving maps, which have been consistently popular since they first appeared. They were based on license suspension records from the Ministry of Transportation for the whole of 2007, which showed the age, sex and postal area of accused drunk drivers. (The age graphs of male and female drunk drivers are worth a look.)

The do-over has two main improvements:

- For the first time, we have a map video, produced with the movie feature of Google Maps 5. I had some trouble getting the audio tracks to appear on the movie file; thanks to multimedia editor Scott Simmie for attaching them.

- The map displays 513 Ontario postal codes, showing patterns across the whole province. It uses boundaries I bought from Statistics Canada, very helpfully converted to .kml by Sanjay Singh at Pitney Bowes. I simplified some of the polygon shapes to speed loading, in the Lake of the Woods area, Manitoulin Island and Long Point. This whittled the zipped .kmz file down to about 800K, which is still much larger than anything we’ve tried to display before. It loads acceptably fast in IE and Firefox, but let me know in the comments if it seems slow. Unusually, it actually seems to load faster in IE.

Here is the video:

So, on to the data. The map shows a strong pattern of higher drunk driving rates in rural and northern areas, especially around Georgian Bay (on all sides – Bruce and Grey Counties, Manitoulin, Parry Sound-Muskoka) and lower rates in rural and suburban areas in the GTA, London and Ottawa.

Here is a top 20 list. It differs (though not enormously) from the previous one because it uses FSA population estimates from the 2006 census, which weren’t available at the time.

Here is a top 10 list:

P0P	Manitoulin	0.49%
P0A	Burks Falls/Sundridge	0.43%
K8H	Petawawa	0.43%
P0C	Georgian Bay shore south of Parry Sound	0.40%
P8T	Sioux Lookout	0.38%
K6K	Rural area north of Cornwall	0.35%
P0X	Whitefish Bay	0.34%
P0G	Georgian Bay shore north of Parry Sound	0.33%
P1L	Bracebridge	0.32%
P1P	Gravenhurst	0.32%
N0A	Nanticoke/Cayuga	0.31%
P0B	Muskoka Lakes	0.30%
P2A	Parry Sound	0.29%
K0E	Rural areas east and west of Brockville	0.28%
N0C	Grey Highlands/Flesherton	0.27%
P9N	Kenora	0.27%
N7T	Rural area south of Sarnia	0.26%
N0H	Bruce Peninsula	0.26%
N3H	Preston	0.26%
P5A	Eliot Lake	0.26%

… and a bottom 10 list:

M6B	Toronto: Glencairn/the Allen	0.06%
N9B	Windsor: university area	0.06%
M4X	Toronto: St. Jamestown	0.05%
M6J	Toronto: Queen/Ossington	0.05%
M1V	Toronto: L'Amoreaux/Agincourt	0.05%
M4W	Toronto: Rosedale	0.05%
K1J	Ottawa: Beacon Hill	0.05%
M4V	Toronto: Casa Loma/southern Forest Hill	0.04%
M3C	Toronto: Flemingdon Park	0.04%
M4P	Toronto: North Toronto (N of Eglinton/Mount Pleasant)	0.04%
M6A	Toronto: Lawrence Manor/Lawrence Heights	0.04%
M5A	Toronto: Regent Park/St Lawrence/Corktown	0.04%
M6G	Toronto: Little Italy: Seaton Village	0.04%
M4S	Toronto: Mt. Pleasant/Davisville	0.04%
N9G	Windsor: Dougall Ave/Howard Ave area	0.04%
M5R	Toronto: Annex	0.04%
M4Y	Toronto: Church/Wellesley	0.04%
M2K	Toronto: York Mills	0.04%
M4H	Toronto: Thorncliffe Park	0.03%
M2H	Toronto: Hillcrest Village	0.02%

FSAs with fewer than 10,000 people were excluded from the rankings.

Comments

[Dave Stasila]

Interesting numbers.

I have two comments/questions.

Would it be possible to do the same analysis by licensed drivers by postal code vs by population by postal code? This might eliminate "licensing rate" differences in postal codes. It should also minimize the errors inherent in using databases from two sources. I.E. MTO suspensions per MTO licenses vs MTO suspensions per StatsCan population.

It was not clear to me that the "by age" suspensions were rates. If not, it would be appealing to see suspensions by age vs licensed drivers by age for both male and females. I was wondering whether the 75+ group would benefit from zero tolerance. Well experienced with declining facilities vs Inexperienced with "peaking" facilities.

If I have misunderstood the maps/stats I'd appreciate knowing that.

Thanks,

DGS