Yearly Traffic Safety Analysis

297 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Buchanan County, total traffic crashes decreased slightly from 305 in 2024 to 297 in 2025, a 2.6% reduction. While overall totals remained stable, the most notable year-over-year shift was in the timing of crashes, with the peak day moving from Thursday in the prior period to Wednesday in the current period, and the peak hour shifting from the 6 a.m. morning commute to 3 p.m.

297

▼ -2.6%was 305

Total Crash Events

1

Persons Killed

70

▼ -9.1%was 77

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

Overall traffic safety trends in Buchanan County show a slight improvement year-over-year. Total crashes decreased by 2.6% from 305 to 297, and total injuries fell by 9.1% from 77 to 70. The number of fatalities remained unchanged, with one person killed in a crash in both 2025 and 2024.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

1

Cyclists Injured

Prior: 2↓-50.0%

69

Motorists Injured

Prior: 74↓-6.8%

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 temporal patterns of crashes shifted between the two periods. The peak day for crashes moved from Thursday (54 crashes) in 2024 to Wednesday (60 crashes) in 2025. Similarly, the peak hour for collisions changed from 6 a.m. in the prior year (22 crashes) to 3 p.m. in the current year (22 crashes), indicating a move from the morning commute to the afternoon.

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 remained broadly consistent year-over-year. The fatal crash rate was nearly identical at 0.34% in 2025 compared to 0.33% in 2024, with one fatal crash recorded in each period. The proportion of serious injury crashes saw a minor increase, rising from 3.0% (9 crashes) to 3.4% (10 crashes) of all incidents. Conversely, crashes resulting in possible injuries decreased from 9.8% (30 crashes) to 7.1% (21 crashes) of the total.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.3%
→0.0%prior 1
Serious Injury10serious injury crashes3.4%
↑11.1%prior 9
Minor Injury24minor injury crashes8.1%
↑4.3%prior 23
Possible Injury21possible injury crashes7.1%
↓-30.0%prior 30
No Injury241no injury crashes81.1%
↓-0.4%prior 242

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 remained the top contributing factor in both periods, increasing slightly from 112 crashes in 2024 to 114 in 2025. The ranking of other top factors shifted; crashes attributed to 'Failure to yield right of way from a stop sign' saw a significant decrease in count, falling from 19 incidents to 8. Meanwhile, 'Ran off road - straight' increased from 10 crashes to 16, and 'Followed too close' increased from 15 to 19 crashes.

Officer-Reported Primary Contributing Cause

Animal114 (38.4%)↑1.8%prior 112
Followed too close19 (6.4%)↑26.7%prior 15
Lost Control18 (6.1%)↓-10.0%prior 20
Ran off road - straight16 (5.4%)↑60.0%prior 10
Ran off road - left12 (4%)↓-42.9%prior 21
Driving too fast for conditions10 (3.4%)↓-37.5%prior 16
Other (explain in narrative): Other8 (2.7%)↓-38.5%prior 13
FTYROW: From stop sign8 (2.7%)↓-57.9%prior 19
Driver Distraction: Other interior distraction7 (2.4%)↓-30.0%prior 10
Other (explain in narrative): No improper action6 (2%)

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 were largely similar year-over-year, with most incidents occurring in clear weather and on dry roads in both periods. However, there was a notable decrease in crashes under adverse conditions in 2025. Crashes on wet roads dropped from 19 to 10, and incidents on icy or frosty surfaces fell from 18 to 10. Additionally, crashes in dark, unlighted conditions decreased from 47 in 2024 to 36 in 2025.

Weather

Clear134 (71.3%)
↓-0.7%prior 135
Cloudy29 (15.4%)
↓-9.4%prior 32
Snow11 (5.9%)
→0.0%prior 11
Rain5 (2.7%)
↓-37.5%prior 8
Freezing rain/drizzle2 (1.1%)
Severe Winds2 (1.1%)
Fog, smoke, smog2 (1.1%)
↓-66.7%prior 6
Blowing Snow2 (1.1%)
Other (explain in narrative)1 (0.5%)

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

Lighting

Daylight141 (73.8%)
↑1.4%prior 139
Dark - roadway not lighted36 (18.8%)
↓-23.4%prior 47
Dark - roadway lighted6 (3.1%)
↓-53.8%prior 13
Dawn5 (2.6%)
Dusk2 (1.0%)
↓-60.0%prior 5
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry139 (73.2%)
→0.0%prior 139
Snow16 (8.4%)
↑23.1%prior 13
Gravel11 (5.8%)
→0.0%prior 11
Wet10 (5.3%)
↓-47.4%prior 19
Ice/frost10 (5.3%)
↓-44.4%prior 18
Slush4 (2.1%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes showed some changes year-over-year. While Ford and Chevrolet were the top two makes in both periods, Chevrolet-involved crashes increased from 72 to 90, overtaking Ford (77 crashes) as the most frequent make. The age distribution of persons involved in crashes also shifted; involvement decreased for the 16-20 age group (from 69 to 55 persons) and the 26-34 group (from 76 to 60 persons), while increasing for the 21-25 age group (from 31 to 48 persons).

Top Vehicle Makes (410 vehicles)

1
CHEV90 (22%)
↑25.0%prior 72
2
FORD77 (18.8%)
↑6.9%prior 72
3
DODG16 (3.9%)
→0.0%prior 16
4
JEEP15 (3.7%)
→0.0%prior 15
5
TOYO14 (3.4%)
→0.0%prior 14
6
GMC12 (2.9%)
↓-40.0%prior 20
7
KIA12 (2.9%)
↑9.1%prior 11
8
RAM11 (2.7%)
↑37.5%prior 8
9
TOYT11 (2.7%)
↓-21.4%prior 14
10
CHRY10 (2.4%)
↑25.0%prior 8

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

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

Sex Distribution (216 persons with recorded sex)

Male127 (58.8%)
↓-9.3%prior 140
Female89 (41.2%)
↑1.1%prior 88

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 10, 2026

Data Coverage

  • Reporting period: 2025-01-01 through 2025-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 297
  • Total persons involved: 427
  • Total vehicles involved: 410

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 10, 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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