Yearly Traffic Safety Analysis

186 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In 2025, Allamakee County recorded 186 total crashes, a 7.5% decrease from the 201 crashes reported in 2024. While overall crashes and injuries declined, incidents reported as involving a driver under the influence increased by 50%, rising from 8 in the prior year to 12 in the current year. Fatalities remained unchanged, with two deaths recorded in both periods.

186

▼ -7.5%was 201

Total Crash Events

2

Persons Killed

41

▼ -28.1%was 57

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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

Crash data for Allamakee County indicates a downward trend in 2025 compared to the previous year. Total crashes decreased by 7.5% from 201 to 186, and total injuries saw a more significant drop of 28.1% from 57 to 41. The number of fatalities remained stable at two for both periods.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 2→0.0%

41

Motorists Injured

Prior: 56↓-26.8%

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 (33 crashes) in 2024 to Saturday (38 crashes) in 2025. Similarly, the peak hour for collisions shifted from 5 p.m. in the prior year, with 26 incidents, to 6 p.m. in the current year, with a lower peak of 15 incidents.

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

While the number of fatal crashes and total fatalities remained constant at two year-over-year, the overall severity of crashes decreased. The proportion of crashes resulting in any type of injury fell from 25.9% in 2024 to 18.9% in 2025. Consequently, crashes resulting in no injuries increased their share from 73.1% to 80.1% of all incidents.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.1%
→0.0%prior 2
Serious Injury4serious injury crashes2.2%
↓-42.9%prior 7
Minor Injury13minor injury crashes7%
↓-18.8%prior 16
Possible Injury18possible injury crashes9.7%
↓-37.9%prior 29
No Injury149no injury crashes80.1%
↑1.4%prior 147

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, with a slight decrease in count from 54 incidents in 2024 to 51 in 2025. 'Lost Control' was the second-most cited factor, also decreasing from 30 incidents to 23. In contrast, crashes attributed to 'Failure to Yield Right of Way: From stop sign' increased from 5 to 9, and incidents involving 'Driver Distraction: Other interior distraction' also rose from 5 to 9.

Officer-Reported Primary Contributing Cause

Animal51 (27.4%)↓-5.6%prior 54
Lost Control23 (12.4%)↓-23.3%prior 30
Ran off road - straight14 (7.5%)↑16.7%prior 12
Ran off road - left11 (5.9%)↓-26.7%prior 15
FTYROW: From stop sign9 (4.8%)↑80.0%prior 5
Driver Distraction: Other interior distraction9 (4.8%)↑80.0%prior 5
Ran Stop Sign7 (3.8%)↑40.0%prior 5
Driver Distraction: Inattentive/lost in thought5 (2.7%)
Driving too fast for conditions5 (2.7%)↓-28.6%prior 7
Other (explain in narrative): Other5 (2.7%)↓-50.0%prior 10

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

Road & Environmental Conditions

The distribution of crashes by lighting conditions shifted, with a higher proportion of incidents occurring in the dark. Crashes in dark conditions (lighted or unlighted) rose from representing 19.9% of all crashes in 2024 to 26.9% in 2025, with incidents on unlighted roadways increasing from 30 to 38. Additionally, crashes on surfaces with snow, ice, or slush increased from 16 to 23 year-over-year.

Weather

Clear114 (77.0%)
↓-0.9%prior 115
Cloudy11 (7.4%)
↓-45.0%prior 20
Blowing Snow5 (3.4%)
Fog, smoke, smog5 (3.4%)
Rain5 (3.4%)
↓-16.7%prior 6
Snow5 (3.4%)
→0.0%prior 5
Severe Winds1 (0.7%)
Freezing rain/drizzle1 (0.7%)
Other (explain in narrative)1 (0.7%)

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

Lighting

Daylight91 (60.7%)
↓-18.0%prior 111
Dark - roadway not lighted38 (25.3%)
↑26.7%prior 30
Dark - roadway lighted9 (6.0%)
↑28.6%prior 7
Dusk6 (4.0%)
Dawn3 (2.0%)
Dark - unknown roadway lighting3 (2.0%)

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

Road Surface

Dry97 (64.7%)
↓-17.8%prior 118
Wet16 (10.7%)
↑6.7%prior 15
Snow13 (8.7%)
↑44.4%prior 9
Gravel12 (8.0%)
↑33.3%prior 9
Ice/frost8 (5.3%)
Slush2 (1.3%)
Mud, dirt1 (0.7%)
Other (explain in narrative)1 (0.7%)

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

Vehicles & Demographics

The top makes of vehicles involved in crashes saw a shift in ranking. Ford, the most common make in 2024 with 57 vehicles, saw its count drop to 42 in 2025, while Chevrolet-branded vehicles (CHEV/CHEVROLET) became the most frequent with a combined 68 vehicles. Analysis of persons involved shows a notable decrease in the 16-20 age group, which fell from 45 individuals in 2024 to 30 in 2025. Conversely, the 26-34 age group saw an increase from 32 to 39 individuals involved in crashes.

Top Vehicle Makes (257 vehicles)

1
CHEV47 (18.3%)
↑30.6%prior 36
2
FORD42 (16.3%)
↓-26.3%prior 57
3
CHEVROLET21 (8.2%)
↓-36.4%prior 33
4
JEEP13 (5.1%)
5
DODG13 (5.1%)
↑18.2%prior 11
6
HOND11 (4.3%)
↑83.3%prior 6
7
TOYOTA10 (3.9%)
↑66.7%prior 6
8
GMC8 (3.1%)
↓-42.9%prior 14
9
BUIC8 (3.1%)
10
FREIGHTLINER6 (2.3%)

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

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

Sex Distribution (124 persons with recorded sex)

Male73 (58.9%)
↓-9.9%prior 81
Female51 (41.1%)
↓-17.7%prior 62

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: 186
  • Total persons involved: 263
  • Total vehicles involved: 257

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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