Yearly Traffic Safety Analysis

2,428 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Woodbury County, total traffic crashes increased slightly from 2,402 in 2024 to 2,428 in 2025, a change of 1.1%. While overall crash volume and fatalities remained stable, the most notable year-over-year shift was a 36.5% increase in the count of crashes involving driving under the influence (DUI), which rose from 85 to 116 incidents.

2,428

▲ 1.1%was 2,402

Total Crash Events

11

Persons Killed

778

▲ 5.1%was 740

Persons Injured

10

Fatal Crash Events

Note: "Persons Killed" (11) counts individual fatalities across all crash events. "Fatal" in the severity table below (10) 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 crash trends in Woodbury County show a slight increase year-over-year. Total crashes rose by 1.1% from 2,402 to 2,428. While total fatalities were unchanged at 11, the number of people injured increased by 5.1%, from 740 in the prior period to 778 in the current period.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

10

Motorists Killed

Prior: 11↓-9.1%

0

Other Killed

Prior: 0→0.0%

28

Pedestrians Injured

Prior: 27↑3.7%

13

Cyclists Injured

Prior: 15↓-13.3%

732

Motorists Injured

Prior: 697↑5.0%

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 temporal patterns of crashes remained consistent year-over-year. Friday was the peak day for crashes in both 2025 (427 crashes) and 2024 (407 crashes). Similarly, the 3 p.m. hour was the peak time for collisions in both periods, with 221 crashes in 2025 and 223 in 2024, indicating no significant shift in when crashes occurred.

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

The severity of crashes showed mixed changes between the two periods. The number of fatal crashes was unchanged at 10, and the fatal crash rate saw a negligible decrease from 0.42% to 0.41%. The count of serious injury crashes increased from 42 to 44, while minor injury crashes decreased from 227 to 204. Consequently, the proportion of crashes resulting in any injury (fatal, serious, minor, or possible) was nearly stable, moving from 30.1% in 2024 to 29.5% in 2025.

Severity is per crash event (most severe injury). 10 fatal crash events resulted in 11 persons killed.

Outcome by Severity (Crash Events)

Fatal10fatal crashes0.4%
→0.0%prior 10
Serious Injury44serious injury crashes1.8%
↑4.8%prior 42
Minor Injury204minor injury crashes8.4%
↓-10.1%prior 227
Possible Injury468possible injury crashes19.3%
↑2.9%prior 455
No Injury1,702no injury crashes70.1%
↑2.0%prior 1,668

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 remained consistent, with 'Followed too close' being the top cause in both years (283 incidents in 2025 vs. 282 in 2024). However, several other factors saw significant count-based increases. Crashes attributed to 'Operating vehicle in an reckless, erratic, careless, negligent manner' grew by 55.6%, from 54 to 84 incidents. Collisions involving 'Driving too fast for conditions' increased by 29.2% (from 96 to 124), and those involving 'Driver Distraction: Other interior distraction' rose by 27.4% (from 73 to 93).

Officer-Reported Primary Contributing Cause

Followed too close283 (11.7%)↑0.4%prior 282
Ran off road - left238 (9.8%)↑3.9%prior 229
FTYROW: From stop sign195 (8%)↑4.8%prior 186
Ran Traffic Signal144 (5.9%)↑10.8%prior 130
Other (explain in narrative): Other134 (5.5%)↑16.5%prior 115
FTYROW: Making left turn126 (5.2%)↓-13.7%prior 146
Driving too fast for conditions124 (5.1%)↑29.2%prior 96
Driver Distraction: Other interior distraction93 (3.8%)↑27.4%prior 73
Ran Stop Sign90 (3.7%)↓-5.3%prior 95
Operating vehicle in an reckless, erratic, careless, negligent manner84 (3.5%)↑55.6%prior 54

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

Road & Environmental Conditions

In both periods, the majority of crashes occurred in clear weather on dry, daylight-lit roads. The proportion of crashes happening in daylight increased from 67.6% to 70.1% year-over-year. There was a notable shift in adverse road surface conditions: crashes on snowy roads increased from 168 to 194, while crashes on icy or frosty roads decreased significantly from 124 to 64.

Weather

Clear1,718 (72.8%)
↓-0.7%prior 1,730
Cloudy357 (15.1%)
↑4.7%prior 341
Snow134 (5.7%)
↑26.4%prior 106
Rain99 (4.2%)
↑19.3%prior 83
Freezing rain/drizzle17 (0.7%)
↓-15.0%prior 20
Blowing Snow15 (0.6%)
↓-6.3%prior 16
Fog, smoke, smog9 (0.4%)
↓-30.8%prior 13
Severe Winds8 (0.3%)
Sleet, hail4 (0.2%)

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

Lighting

Daylight1,703 (71.9%)
↑4.9%prior 1,624
Dark - roadway lighted457 (19.3%)
↑2.2%prior 447
Dark - roadway not lighted105 (4.4%)
↓-24.5%prior 139
Dawn50 (2.1%)
↑25.0%prior 40
Dusk46 (1.9%)
↓-14.8%prior 54
Dark - unknown roadway lighting7 (0.3%)
↓-46.2%prior 13

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

Road Surface

Dry1,817 (76.9%)
↑3.4%prior 1,758
Wet234 (9.9%)
→0.0%prior 234
Snow194 (8.2%)
↑15.5%prior 168
Ice/frost64 (2.7%)
↓-48.4%prior 124
Slush37 (1.6%)
↑60.9%prior 23
Gravel16 (0.7%)
↑45.5%prior 11
Oil1 (0.0%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained largely the same, with Ford and Chevrolet being the most common in both periods. The number of Fords involved increased from 656 to 689, while Chevrolets decreased from 862 to 820. Analysis of persons involved shows a shift in age representation; the share of individuals aged 16-20 decreased from 12.9% to 11.8% of all persons involved, while the 0-15 age group's share increased from 1.8% to 2.3%.

Top Vehicle Makes (4,585 vehicles)

1
FORD689 (15%)
↑5.0%prior 656
2
CHEV537 (11.7%)
↓-3.1%prior 554
3
CHEVROLET283 (6.2%)
↓-8.1%prior 308
4
JEEP212 (4.6%)
↓-7.8%prior 230
5
GMC209 (4.6%)
↓-6.3%prior 223
6
HOND201 (4.4%)
↑24.1%prior 162
7
TOYT180 (3.9%)
↑13.9%prior 158
8
KIA164 (3.6%)
↑14.7%prior 143
9
NR160 (3.5%)
↓-19.2%prior 198
10
DODG157 (3.4%)
↑4.0%prior 151

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

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

Sex Distribution (3,070 persons with recorded sex)

Male1,771 (57.7%)
↑3.8%prior 1,706
Female1,299 (42.3%)
↑0.9%prior 1,288

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: 2,428
  • Total persons involved: 4,800
  • Total vehicles involved: 4,585

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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