Monthly Traffic Safety Analysis

5,172 CRASHES IN
IOWA, IA
OCTOBER 2025

All metrics benchmarked againstOctober 2024

In October 2025, Iowa recorded 5,172 total traffic crashes, a 1.0% increase from the 5,119 crashes documented in October 2024. Despite the slight rise in total incidents, the number of fatalities saw a significant year-over-year decrease. The most notable shift was a 42.5% reduction in total fatalities, which dropped from 40 in the prior period to 23 in the current period.

5,172

▲ 1.0%was 5,119

Total Crash Events

23

▼ -42.5%was 40

Persons Killed

1,598

▲ 3.2%was 1,549

Persons Injured

21

▼ -43.2%was 37

Fatal Crash Events

Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (21) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume remained relatively stable, with total crashes increasing by 1.0% from 5,119 in October 2024 to 5,172 in October 2025. While total injuries rose by 3.2%, from 1,549 to 1,598, total fatalities decreased substantially by 42.5% over the same period. This indicates a shift towards less severe outcomes despite a marginal increase in the number of crashes.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 6↓-66.7%

1

Cyclists Killed

Prior: 1→0.0%

20

Motorists Killed

Prior: 33↓-39.4%

0

Other Killed

Prior: 0→0.0%

35

Pedestrians Injured

Prior: 40↓-12.5%

58

Cyclists Injured

Prior: 53↑9.4%

1,494

Motorists Injured

Prior: 1,447↑3.2%

11

Other Injured

Prior: 9↑22.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed a notable shift in the peak day of the week. In October 2025, Friday was the day with the most crashes (1,014), a change from October 2024 when Wednesday saw the highest volume (919). The peak hour for crashes remained consistent year-over-year, occurring in the 3 p.m. hour for both periods, with 434 crashes in the current period compared to 445 in the prior period.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes decreased year-over-year. The number of fatal crashes dropped from 37 in October 2024 to 21 in October 2025, and their share of all crashes fell from 0.7% to 0.4%. Similarly, serious injury crashes declined from 107 (a 2.1% share) to 95 (a 1.8% share). Correspondingly, the proportion of crashes resulting in no injury increased from 72.6% to 74.0% of all incidents.

Severity is per crash event (most severe injury). 21 fatal crash events resulted in 23 persons killed.

Outcome by Severity (Crash Events)

Fatal21fatal crashes0.4%
↓-43.2%prior 37
Serious Injury95serious injury crashes1.8%
↓-11.2%prior 107
Minor Injury497minor injury crashes9.6%
↓-2.0%prior 507
Possible Injury734possible injury crashes14.2%
↓-2.7%prior 754
No Injury3,825no injury crashes74%
↑3.0%prior 3,714

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors cited in crashes remained consistent year-over-year, with the top three rankings unchanged. 'Animal' was the top factor in both October 2025 (995 crashes) and October 2024 (943 crashes), representing a 5.5% increase in count. 'Followed too close' and 'FTYROW: From stop sign' held their second and third rankings, respectively, though both saw slight decreases in their crash counts. Notably, crashes attributed to 'Driving too fast for conditions' increased by 38.3% in count, from 94 to 130 incidents.

Officer-Reported Primary Contributing Cause

Animal995 (19.2%)↑5.5%prior 943
Followed too close572 (11.1%)↓-2.6%prior 587
FTYROW: From stop sign286 (5.5%)↓-3.1%prior 295
Other (explain in narrative): Other250 (4.8%)↑5.5%prior 237
Ran off road - left235 (4.5%)↓-9.6%prior 260
FTYROW: Making left turn220 (4.3%)↓-0.5%prior 221
Lost Control192 (3.7%)↑6.1%prior 181
Driver Distraction: Other interior distraction175 (3.4%)↓-0.6%prior 176
Ran Stop Sign157 (3%)↑10.6%prior 142
Ran Traffic Signal153 (3%)↓-3.8%prior 159

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Adverse weather and road conditions were more prevalent factors in October 2025 compared to the previous year. Crashes on wet road surfaces increased significantly, from 194 incidents in October 2024 to 563 in October 2025. This corresponds with a rise in crashes occurring during rain, which were noted in 318 crashes this period versus 115 in the prior period. While most crashes occurred in daylight in both periods, the number of incidents on dark, unlit roadways increased from 384 to 490.

Weather

Clear3,177 (74.0%)
↓-17.0%prior 3,829
Cloudy742 (17.3%)
↑141.7%prior 307
Rain318 (7.4%)
↑176.5%prior 115
Fog, smoke, smog30 (0.7%)
↑400.0%prior 6
Freezing rain/drizzle10 (0.2%)
Severe Winds7 (0.2%)
↓-30.0%prior 10
Other (explain in narrative)6 (0.1%)
Blowing sand, soil, dirt1 (0.0%)
↓-85.7%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Weather condition at time of crash

Lighting

Daylight2,930 (67.6%)
↓-4.1%prior 3,056
Dark - roadway lighted639 (14.7%)
↑7.8%prior 593
Dark - roadway not lighted490 (11.3%)
↑27.6%prior 384
Dawn122 (2.8%)
↑20.8%prior 101
Dusk118 (2.7%)
↓-16.3%prior 141
Dark - unknown roadway lighting38 (0.9%)
↓-45.7%prior 70

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Lighting condition field

Road Surface

Dry3,638 (84.6%)
↓-8.8%prior 3,988
Wet563 (13.1%)
↑190.2%prior 194
Gravel94 (2.2%)
→0.0%prior 94
Mud, dirt4 (0.1%)
Other (explain in narrative)3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes showed a consistent pattern year-over-year. Ford and Chevrolet remained the two most common makes in both October 2025 and October 2024, with Ford vehicles involved in 1,344 crashes and Chevrolet in 1,635 crashes (combining 'CHEV' and 'CHEVROLET' categories) in the current period. The demographic distribution of persons involved in crashes also remained stable, with no significant shifts in the representation of any particular age group between the two periods.

Top Vehicle Makes (8,762 vehicles)

1
FORD1,344 (15.3%)
↓-4.4%prior 1,406
2
CHEV1,255 (14.3%)
↑11.1%prior 1,130
3
TOYT479 (5.5%)
↑1.9%prior 470
4
JEEP385 (4.4%)
↓-4.2%prior 402
5
HOND381 (4.3%)
↑22.1%prior 312
6
CHEVROLET380 (4.3%)
↓-8.9%prior 417
7
NISS332 (3.8%)
↑9.2%prior 304
8
GMC312 (3.6%)
↑6.1%prior 294
9
DODG292 (3.3%)
↓-2.0%prior 298
10
KIA262 (3%)
↑0.4%prior 261

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · Vehicle unit records

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

Sex Distribution (5,618 persons with recorded sex)

Male3,219 (57.3%)
↑1.9%prior 3,159
Female2,399 (42.7%)
↓-1.9%prior 2,446

Source: Iowa Crash Data · ArcGIS Open Data · 2025-10-01 to 2025-10-31 · 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: 2025-10-01 through 2025-10-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-10-01 through 2025-10-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 5,172
  • Total persons involved: 9,143
  • Total vehicles involved: 8,762

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: October 2025." Published September 9, 2026. Reporting period: 2025-10-01 to 2025-10-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/october-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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