Yearly Traffic Safety Analysis

206 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Crawford County, traffic crashes decreased from 236 in 2024 to 206 in 2025, a 12.7% reduction. This overall decline was accompanied by fewer injuries, which dropped from 91 to 69, and fewer fatalities, which fell from 2 to 1. The most notable year-over-year shift was a 70% decrease in serious injury crashes, from 10 incidents in 2024 to 3 in 2025.

206

▼ -12.7%was 236

Total Crash Events

1

▼ -50.0%was 2

Persons Killed

69

▼ -24.2%was 91

Persons Injured

1

▼ -50.0%was 2

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 safety trends in Crawford County improved from 2024 to 2025. Total crashes fell by 12.7%, from 236 to 206. This positive trend extended to crash outcomes, as total injuries decreased by 24.2% from 91 to 69, and fatalities were halved from 2 to 1.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 2↓-50.0%

1

Cyclists Injured

Prior: 3↓-66.7%

68

Motorists Injured

Prior: 88↓-22.7%

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 showed some shifts between the two periods. The peak day for crashes moved from Friday in 2024 (46 crashes) to Thursday in 2025 (40 crashes). However, the peak hour for collisions remained consistent at 3 p.m. in both years, accounting for 26 crashes in 2024 and 21 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 decreased notably year-over-year. The number of fatal crashes was halved from 2 in 2024 to 1 in 2025, and the count of serious injury crashes fell from 10 to 3. Consequently, the proportion of no-injury crashes increased from 69.1% of all incidents in 2024 to 72.3% in 2025, indicating a general reduction in the severity of collisions.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
↓-50.0%prior 2
Serious Injury3serious injury crashes1.5%
↓-70.0%prior 10
Minor Injury22minor injury crashes10.7%
↓-8.3%prior 24
Possible Injury31possible injury crashes15%
↓-16.2%prior 37
No Injury149no injury crashes72.3%
↓-8.6%prior 163

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 with animals were the leading contributing factor in both 2024 and 2025, with an identical count of 33 crashes each year. However, the ranking of other factors changed; crashes attributed to 'Lost Control' decreased by 40% from 15 to 9, while those from 'Followed too close' increased by 36%, from 11 to 15 incidents. 'Driving too fast for conditions' also saw a decrease, falling from 6 crashes in 2024 to 11 in 2025, while 'Ran Stop Sign' incidents remained unchanged at 9.

Officer-Reported Primary Contributing Cause

Animal33 (16%)→0.0%prior 33
Followed too close15 (7.3%)↑36.4%prior 11
Other (explain in narrative): Other15 (7.3%)↓-28.6%prior 21
FTYROW: From stop sign11 (5.3%)→0.0%prior 11
Ran off road - left11 (5.3%)↓-15.4%prior 13
Driving too fast for conditions11 (5.3%)↑83.3%prior 6
Lost Control9 (4.4%)↓-40.0%prior 15
Ran Stop Sign9 (4.4%)→0.0%prior 9
Ran off road - straight7 (3.4%)↓-36.4%prior 11
Driver Distraction: Other interior distraction7 (3.4%)↓-46.2%prior 13

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

Road & Environmental Conditions

Crash conditions remained broadly similar year-over-year, with clear weather and dry roads being the most common circumstances in both periods. In 2025, 126 crashes (61.2% of total) occurred in clear weather, compared to 152 (64.4%) in 2024. Crashes on snow-covered roads decreased from 21 incidents in 2024 to 16 in 2025. Daylight was the predominant lighting condition for crashes in both years, accounting for 135 incidents in 2025 and 142 in 2024.

Weather

Clear126 (76.4%)
↓-17.1%prior 152
Cloudy21 (12.7%)
↓-30.0%prior 30
Rain8 (4.8%)
Snow3 (1.8%)
↓-76.9%prior 13
Blowing Snow2 (1.2%)
Sleet, hail2 (1.2%)
Fog, smoke, smog2 (1.2%)
Severe Winds1 (0.6%)

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

Lighting

Daylight135 (76.7%)
↓-4.9%prior 142
Dark - roadway not lighted21 (11.9%)
↓-12.5%prior 24
Dark - roadway lighted8 (4.5%)
↓-71.4%prior 28
Dusk7 (4.0%)
→0.0%prior 7
Dark - unknown roadway lighting4 (2.3%)
Dawn1 (0.6%)

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

Road Surface

Dry126 (72.0%)
↓-19.2%prior 156
Wet16 (9.1%)
↑128.6%prior 7
Snow16 (9.1%)
↓-23.8%prior 21
Gravel8 (4.6%)
↓-27.3%prior 11
Ice/frost7 (4.0%)
↓-30.0%prior 10
Slush2 (1.1%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes were Chevrolet and Ford in both years, though their order changed. The number of Chevrolet vehicles (combining 'CHEV' and 'CHEVROLET' entries) increased from 79 to 101, while Ford vehicles decreased from 77 to 60. Analysis of persons involved shows a notable decrease in the 16-20 age group, which fell from 62 individuals in 2024 to 40 in 2025. The 65+ age group became the most represented in 2025 with 61 persons involved, up from 57 in the prior year.

Top Vehicle Makes (345 vehicles)

1
CHEV78 (22.6%)
↑47.2%prior 53
2
FORD60 (17.4%)
↓-22.1%prior 77
3
CHEVROLET23 (6.7%)
↓-11.5%prior 26
4
JEEP22 (6.4%)
↑4.8%prior 21
5
GMC19 (5.5%)
→0.0%prior 19
6
TOYT18 (5.2%)
↓-10.0%prior 20
7
RAM12 (3.5%)
↑33.3%prior 9
8
NISS12 (3.5%)
→0.0%prior 12
9
DODG11 (3.2%)
↓-38.9%prior 18
10
HOND6 (1.7%)
↓-53.8%prior 13

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

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

Sex Distribution (209 persons with recorded sex)

Male129 (61.7%)
↓-15.7%prior 153
Female80 (38.3%)
↓-16.7%prior 96

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: 206
  • Total persons involved: 360
  • Total vehicles involved: 345

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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