Yearly Traffic Safety Analysis

137 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Cherokee County, total crashes decreased from 175 in 2024 to 137 in 2025, a 21.7% reduction. While overall crashes declined, the most significant development was the occurrence of one fatal crash in 2025, compared to zero in the prior year. Despite the drop in total incidents, the number of people injured increased slightly from 50 to 54.

137

▼ -21.7%was 175

Total Crash Events

1

Persons Killed

54

▲ 8.0%was 50

Persons Injured

1

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) 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

Traffic crashes in Cherokee County showed a downward trend year-over-year, with total incidents falling by 21.7% from 175 in 2024 to 137 in 2025. Despite this decrease in crash volume, the number of people injured rose by 8% from 50 to 54. The county also recorded one fatality in 2025, after having none in the previous year.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 0→%

2

Pedestrians Injured

Prior: 0→%

52

Motorists Injured

Prior: 50↑4.0%

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 peak day for crashes shifted from Saturday (30 crashes) in 2024 to Friday (29 crashes) in 2025. A more pronounced change occurred in the peak hour of crashes, which moved from the evening at 7 p.m. in the prior year (16 crashes) to the late morning at 11 a.m. in the current year (11 crashes).

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

The severity of crashes increased in 2025 compared to the previous year. The county recorded one fatal crash, up from zero in 2024. The proportion of crashes resulting in a serious injury increased from 1.7% (3 crashes) in 2024 to 7.3% (10 crashes) in 2025. Consequently, the share of crashes with no injuries decreased from 77.7% of all incidents to 67.9%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.7%
Serious Injury10serious injury crashes7.3%
↑233.3%prior 3
Minor Injury19minor injury crashes13.9%
↓-5.0%prior 20
Possible Injury14possible injury crashes10.2%
↓-12.5%prior 16
No Injury93no injury crashes67.9%
↓-31.6%prior 136

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

Collisions involving an animal remained the leading contributing factor in both periods, though the count of such incidents decreased by nearly 40% from 48 in 2024 to 29 in 2025. 'Lost Control' was the second most common factor in 2025 with 14 crashes, a slight increase from 13 in the prior year. Crashes attributed to 'Driving too fast for conditions' saw a notable drop from 11 incidents to 7, while 'Followed too close' incidents increased from 8 to 10.

Officer-Reported Primary Contributing Cause

Animal29 (21.2%)↓-39.6%prior 48
Lost Control14 (10.2%)↑7.7%prior 13
Other (explain in narrative): Other13 (9.5%)↑8.3%prior 12
Followed too close10 (7.3%)↑25.0%prior 8
FTYROW: From stop sign9 (6.6%)↓-25.0%prior 12
FTYROW: Making left turn7 (5.1%)↑16.7%prior 6
Ran off road - left7 (5.1%)→0.0%prior 7
Driving too fast for conditions7 (5.1%)↓-36.4%prior 11
Ran off road - straight5 (3.6%)↓-44.4%prior 9
Driver Distraction: Other interior distraction4 (2.9%)↓-20.0%prior 5

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 2025 were more likely to occur during daylight hours, which accounted for 59.9% of incidents compared to 49.7% in 2024. The proportion of crashes on dry road surfaces also increased from 50.9% to 56.9%. Notably, crashes on roads with ice or frost saw a significant reduction, dropping from 20 incidents in 2024 to 4 in 2025.

Weather

Clear71 (66.4%)
↓-26.0%prior 96
Cloudy20 (18.7%)
↑17.6%prior 17
Snow6 (5.6%)
→0.0%prior 6
Rain4 (3.7%)
Severe Winds3 (2.8%)
Blowing Snow2 (1.9%)
Freezing rain/drizzle1 (0.9%)

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

Lighting

Daylight82 (75.9%)
↓-5.7%prior 87
Dark - roadway not lighted12 (11.1%)
↓-42.9%prior 21
Dark - roadway lighted6 (5.6%)
↓-14.3%prior 7
Dusk5 (4.6%)
↓-44.4%prior 9
Dawn2 (1.9%)
↓-60.0%prior 5
Dark - unknown roadway lighting1 (0.9%)
↓-80.0%prior 5

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

Road Surface

Dry78 (72.2%)
↓-12.4%prior 89
Wet12 (11.1%)
↑33.3%prior 9
Snow11 (10.2%)
↑10.0%prior 10
Ice/frost4 (3.7%)
↓-80.0%prior 20
Gravel2 (1.9%)
Slush1 (0.9%)

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 years, though their counts fell from 53 to 40 and 47 to 37, respectively. In 2025, GMC vehicles were the third most common with 20 involved, displacing Jeep from its position in the prior year. Among persons involved in crashes, the 65+ age group saw an increase in representation from 36 individuals to 41, becoming the largest cohort in 2025. Conversely, the number of individuals aged 16-20 involved in crashes decreased from 35 to 27.

Top Vehicle Makes (212 vehicles)

1
FORD40 (18.9%)
↓-24.5%prior 53
2
CHEV37 (17.5%)
↓-21.3%prior 47
3
GMC20 (9.4%)
↑81.8%prior 11
4
CHEVROLET10 (4.7%)
↓-9.1%prior 11
5
JEEP10 (4.7%)
↓-37.5%prior 16
6
BUIC7 (3.3%)
↓-30.0%prior 10
7
DODG7 (3.3%)
↓-46.2%prior 13
8
RAM6 (2.8%)
↓-40.0%prior 10
9
FREIGHTLINER5 (2.4%)
10
KIA5 (2.4%)

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 (120 persons with recorded sex)

Male68 (56.7%)
↓-18.1%prior 83
Female52 (43.3%)
↓-10.3%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: 137
  • Total persons involved: 219
  • Total vehicles involved: 212

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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