New research has revealed which New Mexico counties have the highest fatal crash rates.
The researchers, Las Vegas personal injury lawyers H&P Law, looked at the most recent statistics on motor vehicle crashes in each county, scaling the total crashes per 10,000 county population. Counties with a population of less than 5,000 people were removed from the results due to the number being too small to calculate.
And the research shows that Torrance County is the most dangerous county in the state, with a rate of 25.7 fatal crashes per 10,000 people in the county. Even though Torrance County has one of the smaller populations of counties in the state, the crash rate here is 126% above the state average (11.36 per 10,000 people).
Following behind it is Cibola County. According to the latest data, the county had an average of 23.2 fatal crashes per 10,000 people – a 104% increase from the state average.
The third most dangerous is Socorro County, with a rate of 18.2 fatal incidents per 10,000 residents, with 105 fatal crashes across a five-year period.
On the opposite end of the study, Los Alamos County found itself as the safest county for drivers with a rate of only 3.1 fatal incidents per 10,000 residents – a 72% decrease from the state average.
Despite being the one of least populated counties in New Mexico, drivers in Los Alamos can drive happier knowing that they are least likely to experience a deadly car crash.
For rural locations, it might be better to compute the number of fatalities per mile. A county the size of Torrance requires individual to spend far more time on the road and travel far more distances in their day to day life. If you did an actual comparison based on fatalities per mile or per hundred or per thousands, I think your would find that Los Alamos County is far more dangerous. It should come as no surprise that Torrance County has far more pubic roads (county and state) than Los Alamos County Also, one needs to factor in I40 and its impact on the numbers. In sum, the conclusion is based upon a biased premise. While the data is illuminating, it is of limited value.