Yearly Traffic Safety Analysis

2,032 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Black Hawk County, total vehicle crashes increased slightly from 2,006 in the prior year to 2,032 in the current period, a change of approximately 1.3%. While overall crash volume remained stable, the most significant year-over-year shift was a 46.7% decrease in total fatalities, which fell from 15 to 8. The number of injuries also saw a slight decline, from 662 to 653.

2,032

▲ 1.3%was 2,006

Total Crash Events

8

▼ -46.7%was 15

Persons Killed

653

▼ -1.4%was 662

Persons Injured

8

▼ -46.7%was 15

Fatal Crash Events

Note: "Persons Killed" (8) counts individual fatalities across all crash events. "Fatal" in the severity table below (8) 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 crash trends in Black Hawk County were relatively stable year-over-year, with a minor 1.3% increase in total incidents. However, the outcomes of these crashes improved, as total fatalities dropped from 15 to 8 and total injuries decreased from 662 to 653. This indicates a slight increase in crash frequency but a notable decrease in crash severity.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 0→%

1

Cyclists Killed

Prior: 0→%

3

Motorists Killed

Prior: 15↓-80.0%

0

Other Killed

Prior: 0→0.0%

20

Pedestrians Injured

Prior: 15↑33.3%

19

Cyclists Injured

Prior: 22↓-13.6%

609

Motorists Injured

Prior: 624↓-2.4%

5

Other Injured

Prior: 1↑400.0%

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 timing of crashes shifted between the two periods. The peak day for crashes moved from Friday (331 incidents) in the prior year to Thursday (342 incidents) in the current year. Similarly, the peak hour for collisions shifted earlier in the day, from the 5 p.m. hour (162 crashes) in the prior period to the 3 p.m. hour (196 crashes) in the current period.

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 fell from 15 to 8, and their share of all crashes dropped from 0.7% to 0.4%. The count of serious injury crashes also declined from 43 to 37. Conversely, crashes resulting in minor injuries increased from 162 to 174, and those with possible injuries rose from 336 to 350.

Outcome by Severity (Crash Events)

Fatal8fatal crashes0.4%
↓-46.7%prior 15
Serious Injury37serious injury crashes1.8%
↓-14.0%prior 43
Minor Injury174minor injury crashes8.6%
↑7.4%prior 162
Possible Injury350possible injury crashes17.2%
↑4.2%prior 336
No Injury1,463no injury crashes72%
↑0.9%prior 1,450

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 saw some shifts in ranking and volume. While collisions involving an 'Animal' remained a primary cause, their count decreased from 214 to 195. The most significant change was in crashes attributed to 'Followed too close,' which increased by 30.2% from 139 incidents to 181, moving it from the third to the second most common factor. Additionally, crashes from 'Driving too fast for conditions' rose from 86 to 112, while incidents of 'FTYROW: From stop sign' fell from 126 to 101.

Officer-Reported Primary Contributing Cause

Animal195 (9.6%)↓-8.9%prior 214
Followed too close181 (8.9%)↑30.2%prior 139
Other (explain in narrative): Other121 (6%)↓-31.6%prior 177
Driving too fast for conditions112 (5.5%)↑30.2%prior 86
Driver Distraction: Other interior distraction112 (5.5%)↑43.6%prior 78
Ran off road - left105 (5.2%)↓-0.9%prior 106
FTYROW: From stop sign101 (5%)↓-19.8%prior 126
FTYROW: Making left turn100 (4.9%)↓-8.3%prior 109
Ran Stop Sign99 (4.9%)↑23.8%prior 80
Ran Traffic Signal95 (4.7%)↓-12.8%prior 109

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 largely consistent year-over-year, with 'Clear' weather, 'Daylight' lighting, and 'Dry' road surfaces accounting for the majority of incidents in both periods. There was a notable increase in crashes occurring on 'Ice/frost' covered roads, which rose from 58 incidents in the prior year to 101 in the current year. Crashes on 'Snow' covered surfaces also increased from 92 to 109, while those in 'Rain' decreased from 114 to 95.

Weather

Clear1,345 (72.9%)
↑0.6%prior 1,337
Cloudy291 (15.8%)
↑20.2%prior 242
Rain95 (5.1%)
↓-16.7%prior 114
Snow68 (3.7%)
↑25.9%prior 54
Blowing Snow14 (0.8%)
↓-22.2%prior 18
Freezing rain/drizzle13 (0.7%)
↓-7.1%prior 14
Fog, smoke, smog12 (0.7%)
↑20.0%prior 10
Severe Winds5 (0.3%)
↓-16.7%prior 6
Other (explain in narrative)2 (0.1%)
↓-71.4%prior 7
Blowing sand, soil, dirt1 (0.1%)

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

Lighting

Daylight1,324 (71.2%)
↑4.3%prior 1,269
Dark - roadway lighted298 (16.0%)
↓-1.0%prior 301
Dark - roadway not lighted157 (8.4%)
↑6.8%prior 147
Dawn31 (1.7%)
↓-22.5%prior 40
Dusk31 (1.7%)
↓-26.2%prior 42
Dark - unknown roadway lighting18 (1.0%)
↓-10.0%prior 20

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

Road Surface

Dry1,415 (76.4%)
↓-0.6%prior 1,424
Wet195 (10.5%)
↓-4.9%prior 205
Snow109 (5.9%)
↑18.5%prior 92
Ice/frost101 (5.5%)
↑74.1%prior 58
Slush18 (1.0%)
↓-14.3%prior 21
Gravel10 (0.5%)
↓-9.1%prior 11
Other (explain in narrative)4 (0.2%)

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

Vehicles & Demographics

An analysis of vehicles and persons involved shows a shift in the most common vehicle makes, with Chevrolet models (701) surpassing Ford models (572) in crash involvement compared to the prior year (652 and 606, respectively). The age distribution of persons involved in crashes remained broadly similar, though the 16-20 age group saw its involvement increase from 460 individuals to 500. Conversely, the number of persons aged 65 and older involved in crashes decreased from 507 to 490.

Top Vehicle Makes (3,611 vehicles)

1
FORD572 (15.8%)
↓-5.6%prior 606
2
CHEV532 (14.7%)
↑20.9%prior 440
3
TOYT213 (5.9%)
↑18.3%prior 180
4
CHEVROLET169 (4.7%)
↓-20.3%prior 212
5
JEEP169 (4.7%)
↑6.3%prior 159
6
NISS147 (4.1%)
↑27.8%prior 115
7
HOND128 (3.5%)
↑3.2%prior 124
8
DODG126 (3.5%)
↓-0.8%prior 127
9
KIA110 (3%)
↓-8.3%prior 120
10
NR96 (2.7%)
↑3.2%prior 93

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

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

Sex Distribution (2,455 persons with recorded sex)

Male1,369 (55.8%)
↑2.8%prior 1,332
Female1,086 (44.2%)
↓-1.8%prior 1,106

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: 2,032
  • Total persons involved: 3,777
  • Total vehicles involved: 3,611

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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