Counties in Minnesota by traffic fatality rate, 2024

Name: Counties in Minnesota by traffic fatality rate, 2024
License: https://invokely.ai/docs/methodology

Traverse County had the highest traffic fatality rate of 87 counties in 2024, at 63.8 per 100,000 people. Swift County had the lowest, at 0 per 100,000 people. The median was 12.5 per 100,000 people and the figure for Minnesota was 8.2 per 100,000 people. Source: NHTSA and BEA.

Highest63.8Traverse County

Lowest0Swift County

Median12.587 counties

Minnesota8.2History

Map of counties, 2024

Under 5.1
5.1 to 9.4
9.4 to 12
12 to 17
17 to 21
21 and over

per 100,000 people, 2024. Source: Invokely calculation with data from NHTSA, BEA. Boundaries: U.S. Census Bureau cartographic boundary files.

Top 40 counties, 2024

per 100,000 people. Source: Invokely calculation with data from NHTSA, BEA. Retrieved 2026-10-12.

Full ranking

Rank	Counties	2024 per 100,000 people	Change on 2023
1	Traverse County Estimated	63.8	+63.8 pts
2	Cottonwood County Estimated	52.9	+52.9 pts
3	Kanabec County Estimated	48.2	+42.2 pts
4	Koochiching County Estimated	43.1	+34.6 pts
5	Mahnomen County Estimated	37.8	+0.3 pts
6	Aitkin County Estimated	36.7	+18.1 pts
7	Cass County Estimated	31.8	+28.6 pts
8	Lac qui Parle County Estimated	30.1	+15.2 pts
9	Pennington County Estimated	29.3	+22 pts
10	Renville County Estimated	27.7	+0.1 pts
11	Pope County Estimated	26.1	+17.3 pts
12	Red Lake County Estimated	25.8	+25.8 pts
13	Becker County Estimated	25.4	+8.4 pts
14	Le Sueur County Estimated	23.8	+13.5 pts
15	Faribault County Estimated	21.6	-14.3 pts
16	Wadena County Estimated	20.8	+13.8 pts
17	Stevens County Estimated	20.4	+20.4 pts
18	Jackson County Estimated	20.3	+10.2 pts
19	Morrison County Estimated	20.3	+2.8 pts
20	Kandiyohi County Estimated	20.1	-9.2 pts
21	Roseau County Estimated	19.7	+19.7 pts
22	Lake County Estimated	18.7	+0.3 pts
23	Nobles County Estimated	18.2	+9.1 pts
24	Hubbard County Estimated	18.1	+13.6 pts
25	Mille Lacs County Estimated	18.1	+7.2 pts
26	Lincoln County Estimated	18	+18 pts
27	Cook County Estimated	18	+17.9 pts
28	Beltrami County Estimated	17.1	+2.1 pts
29	Benton County Estimated	16.7	+7.1 pts
30	Freeborn County Estimated	16.5	+0.1 pts
31	Pine County Estimated	16.5	+3.2 pts
32	Otter Tail County Estimated	16.4	+13.1 pts
33	Chippewa County Estimated	16.3	-16.4 pts
34	Steele County Estimated	16	+13.4 pts
35	Wilkin County Estimated	16	+16 pts
36	Norman County Estimated	15.9	+0.1 pts
37	Brown County Estimated	15.6	-0 pts
38	Todd County Estimated	15.4	+11.5 pts
39	Itasca County Estimated	15.4	0 pts
40	Winona County Estimated	14	+8 pts
41	Carlton County Estimated	13.6	+5.4 pts
42	Crow Wing County Estimated	13.1	+10.2 pts
43	Redwood County Estimated	13.1	-13 pts
44	St. Louis County Estimated	12.5	-0.5 pts
45	Murray County Estimated	12.4	+12.4 pts
46	Chisago County Estimated	11.8	+6.7 pts
47	Lyon County Estimated	11.7	+3.9 pts
48	Clearwater County Estimated	11.6	+0.1 pts
49	Isanti County Estimated	11.4	+9.1 pts
50	Houston County Estimated	10.9	-10.6 pts
51	McLeod County Estimated	10.9	-5.4 pts
52	Sherburne County Estimated	10.7	-5.9 pts
53	Yellow Medicine County Estimated	10.7	+10.7 pts
54	Rock County Estimated	10.5	+10.5 pts
55	Clay County Estimated	10.5	+1.4 pts
56	Martin County Estimated	10.2	+0.1 pts
57	Wright County Estimated	9.7	+1.8 pts
58	Dodge County Estimated	9.4	-0.1 pts
59	Fillmore County Estimated	9.3	-13.9 pts
60	Watonwan County Estimated	8.9	-9 pts
61	Nicollet County Estimated	8.7	+2.9 pts
62	Meeker County Estimated	8.5	+4.3 pts
63	Goodhue County Estimated	8.3	+2.1 pts
64	Stearns County Estimated	7.3	-2.6 pts
65	Olmsted County Estimated	6.6	+3.6 pts
66	Polk County Estimated	6.6	+3.3 pts
67	Carver County Estimated	6.2	+1.7 pts
68	Rice County Estimated	5.8	-11.7 pts
69	Blue Earth County Estimated	5.7	+1.4 pts
70	Waseca County Estimated	5.4	+0.1 pts
71	Ramsey County Estimated	5.2	+1.1 pts
72	Scott County Estimated	5.1	+2.5 pts
73	Dakota County Estimated	5.1	+1.5 pts
74	Mower County Estimated	4.9	-2.5 pts
75	Wabasha County Estimated	4.6	-9.2 pts
76	Hennepin County Estimated	4.3	-0 pts
77	Anoka County Estimated	3.5	-2.2 pts
78	Washington County Estimated	2.8	-3.6 pts
79	Douglas County Estimated	2.5	-7.5 pts
80	Big Stone County Estimated	0	0 pts
80	Grant County Estimated	0	-48.7 pts
80	Kittson County Estimated	0	-24.9 pts
80	Lake of the Woods County Estimated	0	-26.3 pts
80	Marshall County Estimated	0	-11.3 pts
80	Pipestone County Estimated	0	0 pts
80	Sibley County Estimated	0	-6.6 pts
80	Swift County Estimated	0	-10.3 pts

Other periods

About this ranking

Traffic fatalities (NHTSA FARS) per 100,000 residents in the same year and place.

Deaths are counted where the crash happened and divided by the resident population, so counties with busy highways and few residents can show very high rates. Differs from the WHO road traffic death rate (road_traffic_death_rate).

Every value in the ranking comes from the same publisher and the same period, so the counties are compared on one definition. Equal values share a rank.

How to cite

Invokely calculation from NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents. https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k. Retrieved 2026-10-12.

Citation styles

Invokely calculated this figure from the publishers' data, so Invokely is the author and the publishers of the inputs are named.

APA 7

Invokely. (n.d.). NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents (Counties in Minnesota by traffic fatality rate, 2024) [Data set]. Calculated from data by NHTSA and BEA. Retrieved October 12, 2026, from https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k

MLA 9

NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents, Counties in Minnesota by traffic fatality rate, 2024. Calculated from data by NHTSA and BEA. Invokely, https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k. Accessed 12 Oct. 2026.

Chicago (author-date)

Invokely. n.d. NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents. Counties in Minnesota by traffic fatality rate, 2024. Dataset. Calculated from data by NHTSA and BEA. Accessed October 12, 2026. https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k.

Harvard

Invokely (no date) NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents, Counties in Minnesota by traffic fatality rate, 2024 [Dataset]. Calculated from data by NHTSA and BEA. Available at: https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k (Accessed: 12 October 2026).

BibTeX

@misc{invokely_counties_in_minnesota_by_2024,
  author = {{Invokely}},
  title = {{NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents: Counties in Minnesota by traffic fatality rate, 2024}},
  howpublished = {Data set},
  url = {https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k},
  urldate = {2026-10-12},
  note = {Calculated from data by NHTSA and BEA. Accessed via Invokely, https://invokely.ai/rankings/traffic-fatality-rate/minnesota-counties. Publisher attribution: Invokely calculation from NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents. https://invokely.ai/docs/methodology\#traffic\_fatality\_rate\_per\_100k. Retrieved 2026-10-12.},
}

RIS

TY  - DATA
AU  - Invokely
TI  - NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents: Counties in Minnesota by traffic fatality rate, 2024
PB  - Invokely
DB  - Invokely
UR  - https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k
L2  - https://invokely.ai/rankings/traffic-fatality-rate/minnesota-counties
Y2  - 2026/10/12
N1  - Calculated from data by NHTSA and BEA.
N1  - Accessed via Invokely, https://invokely.ai/rankings/traffic-fatality-rate/minnesota-counties.
N1  - Publisher attribution: Invokely calculation from NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents. https://invokely.ai/docs/methodology#traffic_fatality_rate_per_100k. Retrieved 2026-10-12.
ER  -

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Questions

Which county has the highest traffic fatality rate?

Traverse County, with 63.8 per 100,000 people in 2024, according to NHTSA and BEA.

Which county has the lowest traffic fatality rate?

Swift County, with 0 per 100,000 people in 2024.

Where does this ranking come from?

Every value comes from one source and one period, so the places are comparable: Invokely, NHTSA FARS traffic fatalities divided by BEA mid-year population (SAINC1 and CAINC1), per 100,000 residents. Retrieved 2026-10-12.