Monthly Traffic Safety Analysis

4,118 CRASHES IN
IOWA, IA
JULY 2025

All metrics benchmarked againstJuly 2024

In July 2025, there were 4,118 total crashes, a 1.2% increase from the 4,069 crashes recorded in July 2024. Despite the slight rise in total incidents, the number of fatalities saw a notable year-over-year decrease, dropping from 39 to 28. Crashes involving 'Driver Distraction: Other interior distraction' saw a 19.2% increase in count from the prior year.

4,118

▲ 1.2%was 4,069

Total Crash Events

28

▼ -28.2%was 39

Persons Killed

1,407

▼ -2.7%was 1,446

Persons Injured

25

▼ -28.6%was 35

Fatal Crash Events

Note: "Persons Killed" (28) 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 · 2025-07-01 to 2025-07-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume remained relatively stable, with a slight 1.2% increase from 4,069 incidents in July 2024 to 4,118 in July 2025. However, the severity of these crashes decreased, as total injuries fell by 2.7% from 1,446 to 1,407, and fatalities dropped by 28.2% from 39 to 28 compared to the same period last year.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 2↓-50.0%

0

Cyclists Killed

Prior: 1↓-100.0%

27

Motorists Killed

Prior: 36↓-25.0%

0

Other Killed

Prior: 0→0.0%

35

Pedestrians Injured

Prior: 29↑20.7%

57

Cyclists Injured

Prior: 37↑54.1%

1,309

Motorists Injured

Prior: 1,371↓-4.5%

6

Other Injured

Prior: 9↓-33.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The peak hour for crashes remained consistent at 4 p.m. year-over-year, with nearly identical crash counts of 346 in July 2025 and 347 in July 2024. The peak day of the week shifted from Wednesday (735 crashes) in the prior period to Thursday (710 crashes) in the current period. Crashes on Tuesdays and Thursdays saw increases, while incidents on Mondays and Wednesdays decreased compared to the previous year.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes decreased from July 2024 to July 2025. The number of fatal crashes fell from 35 to 25, and the fatal crash rate dropped from 0.86 to 0.61 per 100 crashes. The proportion of serious injury crashes also declined from 3.1% to 2.7% of all incidents. Correspondingly, the share of crashes resulting in possible injury or no injury saw a slight increase.

Severity is per crash event (most severe injury). 25 fatal crash events resulted in 28 persons killed.

Outcome by Severity (Crash Events)

Fatal25fatal crashes0.6%
↓-28.6%prior 35
Serious Injury113serious injury crashes2.7%
↓-11.7%prior 128
Minor Injury446minor injury crashes10.8%
↓-9.5%prior 493
Possible Injury633possible injury crashes15.4%
↑7.7%prior 588
No Injury2,901no injury crashes70.4%
↑2.7%prior 2,825

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors remained consistent year-over-year, with 'Animal' (505 crashes) and 'Followed too close' (468 crashes) as the top two causes in July 2025. The count for crashes attributed to 'Followed too close' increased by 32 incidents, a 7.3% rise in count from the prior year's 436. Notably, crashes involving 'Driver Distraction: Other interior distraction' rose by 19.2% in count, from 156 to 186 incidents. Conversely, crashes due to 'Ran off road - left' decreased in count by 8.5% from 247 to 226.

Officer-Reported Primary Contributing Cause

Animal505 (12.3%)↑0.2%prior 504
Followed too close468 (11.4%)↑7.3%prior 436
FTYROW: From stop sign232 (5.6%)↑5.0%prior 221
Ran off road - left226 (5.5%)↓-8.5%prior 247
Other (explain in narrative): Other201 (4.9%)↓-11.1%prior 226
Driver Distraction: Other interior distraction186 (4.5%)↑19.2%prior 156
Lost Control181 (4.4%)↓-0.5%prior 182
FTYROW: Making left turn168 (4.1%)↑11.3%prior 151
Ran off road - straight136 (3.3%)↑7.9%prior 126
Ran Traffic Signal135 (3.3%)↓-18.2%prior 165

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained remarkably stable year-over-year. In both July 2025 and July 2024, the vast majority of crashes occurred in clear weather (69.2% vs 70.0% of total crashes), during daylight hours (71.5% vs 70.7%), and on dry road surfaces (79.2% vs 79.1%). There were no significant shifts in the proportion of crashes happening under adverse weather, lighting, or road surface conditions.

Weather

Clear2,850 (77.8%)
→0.0%prior 2,849
Cloudy564 (15.4%)
↑2.7%prior 549
Rain220 (6.0%)
↑17.6%prior 187
Fog, smoke, smog20 (0.5%)
↑33.3%prior 15
Other (explain in narrative)7 (0.2%)
↑16.7%prior 6
Freezing rain/drizzle1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Weather condition at time of crash

Lighting

Daylight2,944 (79.5%)
↑2.3%prior 2,877
Dark - roadway lighted337 (9.1%)
↓-2.6%prior 346
Dark - roadway not lighted269 (7.3%)
↑4.3%prior 258
Dusk62 (1.7%)
↓-27.1%prior 85
Dawn59 (1.6%)
↓-3.3%prior 61
Dark - unknown roadway lighting32 (0.9%)
↓-20.0%prior 40

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Lighting condition field

Road Surface

Dry3,261 (88.9%)
↑1.3%prior 3,218
Wet330 (9.0%)
↑2.8%prior 321
Gravel72 (2.0%)
↓-13.3%prior 83
Other (explain in narrative)3 (0.1%)
Mud, dirt2 (0.1%)
Water (standing or moving)2 (0.1%)
↓-60.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet models being the most common in both periods. The representation of different age groups among persons involved in crashes saw a notable shift. The 35-44 age group's involvement increased from 1,005 to 1,102 persons, making it the most frequently involved group in July 2025. Conversely, the 26-34 age group, which was the most represented in the prior year with 1,144 persons, saw its involvement decrease to 1,063.

Top Vehicle Makes (7,066 vehicles)

1
FORD1,101 (15.6%)
↓-5.3%prior 1,163
2
CHEV910 (12.9%)
↓-1.3%prior 922
3
CHEVROLET366 (5.2%)
↓-4.4%prior 383
4
TOYT328 (4.6%)
↑5.1%prior 312
5
JEEP313 (4.4%)
↑3.0%prior 304
6
HOND310 (4.4%)
↑17.4%prior 264
7
NISS261 (3.7%)
↑25.5%prior 208
8
DODG249 (3.5%)
↑10.2%prior 226
9
GMC240 (3.4%)
↓-10.1%prior 267
10
KIA217 (3.1%)
↑3.3%prior 210

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · Vehicle unit records

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

Sex Distribution (4,622 persons with recorded sex)

Male2,689 (58.2%)
↑2.1%prior 2,634
Female1,933 (41.8%)
↑5.7%prior 1,828

Source: Iowa Crash Data · ArcGIS Open Data · 2025-07-01 to 2025-07-31 · 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: 2025-07-01 through 2025-07-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-07-01 through 2025-07-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,118
  • Total persons involved: 7,431
  • Total vehicles involved: 7,066

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: July 2025." Published September 9, 2026. Reporting period: 2025-07-01 to 2025-07-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/july-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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