Monthly Traffic Safety Analysis

4,137 CRASHES IN
IOWA, IA
JUNE 2025

All metrics benchmarked againstJune 2024

In June 2025, there were 4,137 total crashes, a 6.3% decrease from the 4,416 crashes recorded in June 2024. This downward trend was also reflected in crash outcomes, with total fatalities decreasing by 18.8% from 32 to 26 and total injuries falling by 10.2% from 1,504 to 1,351 year-over-year. The most notable shift in contributing factors was a 22.2% decrease in the count of crashes involving animals, which dropped from 769 to 598, though it remained the top single factor in both periods.

4,137

▼ -6.3%was 4,416

Total Crash Events

26

▼ -18.8%was 32

Persons Killed

1,351

▼ -10.2%was 1,504

Persons Injured

25

▼ -16.7%was 30

Fatal Crash Events

Note: "Persons Killed" (26) counts individual fatalities across all crash events. "Fatal" in the severity table below (25) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes showed a general downward trend in June 2025 compared to the same month in the prior year. Total crashes decreased by 6.3%, from 4,416 to 4,137. Similarly, total fatalities fell from 32 to 26, and the number of injuries decreased from 1,504 to 1,351.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 2↑50.0%

1

Cyclists Killed

Prior: 0→%

21

Motorists Killed

Prior: 30↓-30.0%

1

Other Killed

Prior: 0→%

26

Pedestrians Injured

Prior: 23↑13.0%

45

Cyclists Injured

Prior: 36↑25.0%

1,272

Motorists Injured

Prior: 1,434↓-11.3%

8

Other Injured

Prior: 11↓-27.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes shifted slightly between the two periods. In June 2025, Monday was the peak day for crashes with 713 incidents, a change from June 2024 when Friday was the peak day with 702 crashes. The peak hour for collisions remained consistent, occurring at 4 p.m. in both years, with 339 crashes in the current period compared to 334 in the prior period.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes decreased year-over-year. The number of fatal crashes fell from 30 to 25, and the fatal crash rate per 100 crashes decreased from 0.68 to 0.60. The count of serious injury crashes also declined from 138 to 107. The overall proportion of crashes resulting in any level of injury (fatal, serious, minor, or possible) remained stable at approximately 29% across both periods.

Severity is per crash event (most severe injury). 25 fatal crash events resulted in 26 persons killed.

Outcome by Severity (Crash Events)

Fatal25fatal crashes0.6%
↓-16.7%prior 30
Serious Injury107serious injury crashes2.6%
↓-22.5%prior 138
Minor Injury450minor injury crashes10.9%
↓-7.8%prior 488
Possible Injury622possible injury crashes15%
↓-1.1%prior 629
No Injury2,933no injury crashes70.9%
↓-6.3%prior 3,131

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Most severe injury per crash record

Top Contributing Factors

While 'Animal' remained the top contributing factor in both periods, its count decreased by 22.2% from 769 to 598 crashes. 'Followed too close' was the second-leading factor in both years, with its count dropping from 494 to 451. Notably, 'FTYROW: From stop sign' moved up from the fifth-ranked factor to the third, with its crash count increasing from 222 to 242. Conversely, crashes attributed to 'Ran off road - left' decreased from 233 to 227.

Officer-Reported Primary Contributing Cause

Animal598 (14.5%)↓-22.2%prior 769
Followed too close451 (10.9%)↓-8.7%prior 494
FTYROW: From stop sign242 (5.8%)↑9.0%prior 222
Ran off road - left227 (5.5%)↓-2.6%prior 233
Other (explain in narrative): Other196 (4.7%)↓-14.8%prior 230
Lost Control186 (4.5%)↑8.1%prior 172
Driver Distraction: Other interior distraction157 (3.8%)↑12.9%prior 139
FTYROW: Making left turn152 (3.7%)↓-11.1%prior 171
Operating vehicle in an reckless, erratic, careless, negligent manner142 (3.4%)↑3.6%prior 137
Ran Traffic Signal140 (3.4%)↓-10.3%prior 156

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions were largely similar year-over-year, with the majority of incidents in both periods occurring in clear weather (65.2% vs. 68.0%), during daylight hours (71.8% vs. 67.6%), and on dry roads (73.6% vs. 75.7%). However, there was a notable increase in the absolute number of crashes occurring in adverse conditions. Crashes in the rain increased from 212 to 281, and collisions on wet road surfaces increased from 333 to 460.

Weather

Clear2,697 (75.0%)
↓-10.2%prior 3,003
Cloudy597 (16.6%)
↑16.8%prior 511
Rain281 (7.8%)
↑32.5%prior 212
Severe Winds10 (0.3%)
↑11.1%prior 9
Fog, smoke, smog5 (0.1%)
Freezing rain/drizzle3 (0.1%)
Other (explain in narrative)2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Weather condition at time of crash

Lighting

Daylight2,970 (81.6%)
↓-0.5%prior 2,984
Dark - roadway lighted290 (8.0%)
↓-18.1%prior 354
Dark - roadway not lighted245 (6.7%)
↓-13.1%prior 282
Dusk64 (1.8%)
↓-28.9%prior 90
Dawn49 (1.3%)
↑8.9%prior 45
Dark - unknown roadway lighting23 (0.6%)
↓-17.9%prior 28

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Lighting condition field

Road Surface

Dry3,045 (84.4%)
↓-8.9%prior 3,344
Wet460 (12.8%)
↑38.1%prior 333
Gravel92 (2.6%)
↑31.4%prior 70
Mud, dirt6 (0.2%)
Other (explain in narrative)2 (0.1%)
Sand1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet accounting for the highest volumes in both June 2025 and June 2024. Among persons involved in crashes, most age groups saw a decrease in numbers, consistent with the overall trend. However, the 16-20 age group saw a slight increase in involvement, from 935 individuals in the prior year to 967 in the current period.

Top Vehicle Makes (7,084 vehicles)

1
FORD1,078 (15.2%)
↓-10.3%prior 1,202
2
CHEV966 (13.6%)
↑3.6%prior 932
3
CHEVROLET361 (5.1%)
↓-12.0%prior 410
4
JEEP348 (4.9%)
↑19.6%prior 291
5
TOYT347 (4.9%)
↓-0.3%prior 348
6
HOND286 (4%)
↓-1.4%prior 290
7
NISS258 (3.6%)
↑11.7%prior 231
8
GMC249 (3.5%)
↓-12.0%prior 283
9
DODG237 (3.3%)
↑2.6%prior 231
10
KIA181 (2.6%)
↓-26.1%prior 245

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · Vehicle unit records

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

Sex Distribution (4,569 persons with recorded sex)

Male2,660 (58.2%)
↓-1.2%prior 2,693
Female1,909 (41.8%)
↓-1.1%prior 1,930

Source: Iowa Crash Data · ArcGIS Open Data · 2025-06-01 to 2025-06-30 · 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: 2025-06-01 through 2025-06-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-06-01 through 2025-06-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,137
  • Total persons involved: 7,372
  • Total vehicles involved: 7,084

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: June 2025." Published September 9, 2026. Reporting period: 2025-06-01 to 2025-06-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/june-2025-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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