Minnesota recently released its annual list of its 13 counties with the highest combined totals of alcohol-related traffic deaths and serious injuries for 2008-10. And as these pages (in the St. Cloud Times) have noted the past several years, the list contains few surprises.
Not surprisingly, the 13 counties accounted for almost half of the state’s alcohol-related deaths (202) and half of the state’s serious injuries (462) during 2008-2010.
Not surprisingly, the combined population of the 13 counties amounts to more than 65 percent of the state’s 5.2 million residents.
Not surprisingly, 12 of the 13 counties run from St. Cloud through the Twin Cities and down to Rochester. (St. Louis County is the only county listed outside that area.)
Not surprisingly, all 13 counties have made the annual list in most (or all) recent years.
And finally — and not surprisingly — the list was generated and made public because it brings attention to the newest “heightened enforcement” efforts being launched in these 13 counties and set to last through September. This effort last year used about $2.75 million in federal aid to conduct high-visibility enforcement tactics and advertise the importance of driving sober.
Please know this (editorial) board supports trying to make Minnesota roads safer by reducing drunken driving. However, this list — and especially its predictability and cost — annually raises two fundamental questions.
— Isn’t this stating the obvious?
The list is clearly volume-based. It doesn’t take an advanced degree in mathematics to determine that the counties with biggest populations are going to have the highest numbers of accidents and fatalities — probably regardless of driver sobriety.
— Might there be a more strategic way of interpreting all this data?
This board repeats that question — first asked in 2008 — simply because a volume-based approach seems to present a challenge that can’t be solved. (There will always be 13 counties with more DUI crashes and fatalities than 74 others.)
To truly develop strategic ways that make roads safer it seems wise to look at DUI crash data on a per-capita basis county by county. From there, the state should examine why differences exist beyond just population. Might driver demographics be a factor? Road designs? Enforcement tactics? Rural, suburban or urban issues?
Again, our point is simple — and is not meant to bash this list. Rather, it’s to urge the state to take a different look at the same list it generates annually. Perhaps that new look will reveal new solutions that can complement enforcement efforts.
— The St. Cloud Times