Yearly Traffic Safety Analysis

105 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Kossuth County recorded 105 total crashes, a 28.1% decrease from the 146 crashes reported in 2024. Total injuries remained relatively stable at 55 in 2025 compared to 58 in 2024. The most significant change was the reduction in traffic fatalities, which dropped from 3 in the prior year to 0 in the current year.

105

▼ -28.1%was 146

Total Crash Events

0

▼ -100.0%was 3

Persons Killed

55

▼ -5.2%was 58

Persons Injured

0

▼ -100.0%was 3

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall, traffic crashes in Kossuth County showed a significant downward trend year-over-year. The total number of crashes fell by 41, from 146 in 2024 to 105 in 2025, representing a 28.1% decrease. This improvement was also reflected in crash outcomes, with total injuries seeing a slight decrease from 58 to 55, and fatalities dropping from 3 to 0.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 3↓-100.0%

1

Pedestrians Injured

Prior: 0→%

54

Motorists Injured

Prior: 58↓-6.9%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted between the two periods. The peak day for crashes moved from Tuesday (24 crashes) in 2024 to Wednesday (21 crashes) in 2025. Similarly, the peak hour for collisions changed from 1 p.m. in the prior year (16 crashes) to 3 p.m. in the current year (13 crashes). Crashes on Sundays saw a notable decrease, falling from 15 in 2024 to just 5 in 2025.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity improved significantly year-over-year. There were no fatal crashes in 2025, compared to 3 fatal crashes (2.1% of all crashes) in 2024. The count of serious injury crashes also decreased from 7 to 3. While the absolute number of no-injury crashes fell from 105 to 67, their share of all crashes also decreased from 71.9% to 63.8% as the proportion of minor and possible injury crashes increased.

Outcome by Severity (Crash Events)

Serious Injury3serious injury crashes2.9%
↓-57.1%prior 7
Minor Injury21minor injury crashes20%
↑10.5%prior 19
Possible Injury14possible injury crashes13.3%
↑16.7%prior 12
No Injury67no injury crashes63.8%
↓-36.2%prior 105

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes shifted between periods. "Driving too fast for conditions" became the most cited factor in 2025 with 13 crashes, an increase from 7 crashes in the prior year. Conversely, "Lost Control," which was the top factor in 2024 with a count of 14 crashes, saw its count decrease to 5. Crashes involving animals more than doubled, rising from 4 to 9 incidents, while "Failure to yield from a stop sign" remained a top-three factor in both years with counts of 10 in 2024 and 8 in 2025.

Officer-Reported Primary Contributing Cause

Driving too fast for conditions13 (12.4%)↑85.7%prior 7
Animal9 (8.6%)
FTYROW: From stop sign8 (7.6%)↓-20.0%prior 10
Made improper turn7 (6.7%)↑40.0%prior 5
Ran Stop Sign7 (6.7%)↑16.7%prior 6
Ran off road - left6 (5.7%)↓-50.0%prior 12
Other (explain in narrative): Other5 (4.8%)↓-44.4%prior 9
Driver Distraction: Inattentive/lost in thought5 (4.8%)
Lost Control5 (4.8%)↓-64.3%prior 14
FTYROW: At uncontrolled intersection4 (3.8%)↓-33.3%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crashes in clear weather and on dry roads remained the most common scenario in both years, though their share of total crashes decreased. In 2025, 64.8% of crashes occurred on dry roads, down from a 74.7% share in 2024. The proportion of crashes occurring during adverse weather, such as snow or freezing rain, increased from 5.5% of all crashes in 2024 to 14.3% in 2025. Crashes in dark conditions made up a slightly larger share of the total in the current year (26.7%) compared to the prior year (23.3%).

Weather

Clear72 (75.0%)
↓-35.1%prior 111
Cloudy9 (9.4%)
↓-55.0%prior 20
Snow8 (8.3%)
Freezing rain/drizzle3 (3.1%)
Fog, smoke, smog2 (2.1%)
↓-60.0%prior 5
Blowing Snow1 (1.0%)
Severe Winds1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Weather condition at time of crash

Lighting

Daylight63 (64.9%)
↓-35.1%prior 97
Dark - roadway lighted14 (14.4%)
→0.0%prior 14
Dark - roadway not lighted14 (14.4%)
↓-30.0%prior 20
Dawn5 (5.2%)
↓-16.7%prior 6
Dusk1 (1.0%)
↓-85.7%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Lighting condition field

Road Surface

Dry68 (70.8%)
↓-37.6%prior 109
Snow11 (11.5%)
↑83.3%prior 6
Ice/frost6 (6.3%)
↓-60.0%prior 15
Gravel6 (6.3%)
↑20.0%prior 5
Wet4 (4.2%)
↓-50.0%prior 8
Slush1 (1.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet vehicles were the most frequently involved in crashes in both periods, though their total counts decreased year-over-year. In 2025, Ford was the top make with 37 vehicles involved, compared to 2024 when Chevrolet was the top make with 50 vehicles. The demographic profile of persons involved in crashes also shifted, with the 65+ age group becoming the most represented in 2025 (41 persons), up from 35 persons in the prior year. Meanwhile, the involvement of the 35-44 age group decreased from 47 persons to 26.

Top Vehicle Makes (174 vehicles)

1
FORD37 (21.3%)
↓-21.3%prior 47
2
CHEV32 (18.4%)
↓-36.0%prior 50
3
JEEP9 (5.2%)
↓-10.0%prior 10
4
TOYT7 (4%)
5
DODG7 (4%)
↑16.7%prior 6
6
NISS7 (4%)
↑40.0%prior 5
7
CHEVROLET6 (3.4%)
↓-45.5%prior 11
8
GMC6 (3.4%)
↓-57.1%prior 14
9
BUIC5 (2.9%)
↓-61.5%prior 13
10
KIA5 (2.9%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Vehicle unit records

15 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (102 persons with recorded sex)

Male64 (62.7%)
↓-42.9%prior 112
Female38 (37.3%)
↓-34.5%prior 58

Source: Iowa Crash Data · ArcGIS Open Data · 2025-01-01 to 2025-12-31 · Person-level records linked to crash events

Data Sources & Methodology

Primary Data Source

All crash data in this report is sourced from Iowa Crash Data, accessed programmatically via the ArcGIS Open Data API (SODA). This dataset contains official police-reported motor vehicle traffic crash records maintained by the reporting jurisdiction's law enforcement agency. Records are published to the open data portal by the municipality and are subject to the portal's terms of use.

Data Retrieval

  • Access method: ArcGIS Open Data API (SoQL queries)
  • Data format: Structured JSON via REST API
  • Record types queried: Crash events, person records, and vehicle unit records
  • Date filter applied: 2025-01-01 through 2025-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 105
  • Total persons involved: 183
  • Total vehicles involved: 174

Analytical Methodology

  • Severity classification: Uses the KABCO injury scale (K=Fatal, A=Incapacitating injury, B=Non-incapacitating injury, C=Possible injury, O=No injury/property damage only), the standard classification in U.S. Model Minimum Uniform Crash Criteria (MMUCC). Severity is assigned per crash event based on the most severe injury in that crash. A single fatal crash (K) may involve multiple fatalities; therefore the "Persons Killed" count in the headline KPIs may differ from the "Fatal" crash count in the severity breakdown.
  • Contributing factors: Reflect the officer-determined primary contributory cause recorded at the time of the crash report. These are preliminary determinations and may not reflect final investigation findings.
  • Hit-and-run classification: Based on the hit-and-run indicator field in the official crash report, as determined by the responding officer at the scene.
  • Temporal analysis: Day-of-week and hour-of-day distributions are computed from the crash date/time timestamp in each record.
  • Demographics: Age and sex distributions are drawn from person-level records linked to each crash event. A single crash may involve multiple persons.
  • Vehicle data: Make information is drawn from vehicle unit records linked to each crash event.
  • AI commentary: Narrative sections are generated by Google Gemini (large language model) based on the structured data. Commentary is descriptive, not predictive, and should not be interpreted as expert opinion.

Limitations & Disclaimers

  • Only crashes reported to and documented by law enforcement are included. Minor incidents, unreported crashes, and near-misses are not captured in this dataset.
  • Data reflects conditions at the time of the initial police report and may be subject to subsequent corrections, reclassifications, or supplements by the reporting agency.
  • Open data portal records may experience a publication lag - recently occurring crashes may not yet appear in the dataset at the time of report generation.
  • AI-generated commentary is produced by a large language model and is intended to highlight patterns in the data. It does not constitute legal, medical, or professional analysis.
  • Percentages are calculated from reported data and are subject to rounding.

Non-Affiliation Disclosure

This report is produced independently by ThatCarHitMe.com (Injuria.ai). It is not affiliated with, endorsed by, or produced in partnership with any law enforcement agency, municipal government, state department of transportation, or the National Highway Traffic Safety Administration (NHTSA). Data is sourced from publicly available government open data portals.

Data License

The underlying crash data is provided under the municipality's Open Data Terms of Use and is made available to the public for unrestricted use. This analysis and report is © 2026 Injuria.ai and may be cited with attribution using the suggested citation below.

Corrections & Feedback

If you believe any data in this report is inaccurate or have questions about our methodology, please contact: data@injuria.ai. We are committed to accuracy and will issue corrections promptly.

Suggested Citation

ThatCarHitMe.com (Injuria.ai). "iowa, IA Crash Intelligence Report: 2025." Published September 9, 2026. Reporting period: 2025-01-01 to 2025-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2025-annual-report

About the Publisher

ThatCarHitMe.com is a crash data intelligence platform developed by Injuria.ai, a legal technology company specializing in traffic safety analytics. We aggregate and analyze publicly available government crash data to produce structured intelligence reports for communities, researchers, journalists, and legal professionals. Our reports combine programmatic data retrieval from official open data portals with AI-assisted narrative analysis.

Questions about this report's data or methodology: data@injuria.ai

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