Yearly Traffic Safety Analysis

770 CRASHES IN
IOWA, IA
2025

All metrics benchmarked against2024

In Des Moines County, total crashes decreased from 788 in 2024 to 770 in 2025, a change of approximately -2.3%. Despite the overall drop in collisions, the number of people injured rose by 14.9%, from 175 to 201. Fatalities also increased from 3 to 4 year-over-year.

770

▼ -2.3%was 788

Total Crash Events

4

▲ 33.3%was 3

Persons Killed

201

▲ 14.9%was 175

Persons Injured

4

▲ 33.3%was 3

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 collisions in Des Moines County showed a slight decrease in 2025, falling by 2.3% from 788 crashes in the prior year to 770. While the total number of crashes declined, the outcomes worsened, with total injuries increasing by 14.9% and fatalities rising from 3 to 4.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 1↓-100.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 2↑100.0%

0

Other Killed

Prior: 0→0.0%

2

Pedestrians Injured

Prior: 4↓-50.0%

5

Cyclists Injured

Prior: 5→0.0%

193

Motorists Injured

Prior: 165↑17.0%

1

Other Injured

Prior: 1→0.0%

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 shifted between the two periods. The peak day for crashes moved from Monday (137 crashes) in 2024 to Friday (137 crashes) in 2025. Similarly, the peak hour for collisions occurred earlier in the day, shifting from 5 p.m. (65 crashes) in the prior year to 3 p.m. (68 crashes) in the current year.

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 increased in 2025 compared to the previous year. The number of fatal crashes rose from 3 to 4, and the count of serious injury crashes increased from 10 to 16. Overall, crashes resulting in any level of injury (fatal, serious, minor, or possible) accounted for 24.3% of all incidents in 2025, up from a share of 21.3% in 2024.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.5%
↑33.3%prior 3
Serious Injury16serious injury crashes2.1%
↑60.0%prior 10
Minor Injury68minor injury crashes8.8%
↑9.7%prior 62
Possible Injury99possible injury crashes12.9%
↑6.5%prior 93
No Injury583no injury crashes75.7%
↓-6.0%prior 620

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

Collisions involving an 'Animal' remained the top contributing factor in both periods, though the count decreased from 159 in 2024 to 152 in 2025. The top five factors were largely consistent, with 'Failure to yield from a stop sign' holding steady at 44 incidents in both years. Notably, incidents attributed to 'Driving too fast for conditions' increased by 45.8% in count, from 24 to 35, while crashes from 'Followed too close' decreased by 25% in count, from 56 to 42.

Officer-Reported Primary Contributing Cause

Animal152 (19.7%)↓-4.4%prior 159
Driver Distraction: Other interior distraction69 (9%)↑7.8%prior 64
Other (explain in narrative): Other47 (6.1%)↓-11.3%prior 53
FTYROW: From stop sign44 (5.7%)→0.0%prior 44
Followed too close42 (5.5%)↓-25.0%prior 56
Driving too fast for conditions35 (4.5%)↑45.8%prior 24
FTYROW: Making left turn29 (3.8%)↓-6.5%prior 31
Lost Control26 (3.4%)↓-13.3%prior 30
Improper or erratic lane changing22 (2.9%)↑37.5%prior 16
Ran off road - left21 (2.7%)↓-40.0%prior 35

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

Road & Environmental Conditions

Driving conditions at the time of crashes remained largely consistent year-over-year. In both 2025 and 2024, the majority of collisions occurred in 'Clear' weather (473 and 482 crashes, respectively) and during 'Daylight' hours (436 and 425 crashes). Crashes on dry road surfaces were also nearly identical, with 493 in the current period and 495 in the prior, indicating no significant shift in the proportion of crashes occurring in adverse conditions.

Weather

Clear473 (76.0%)
↓-1.9%prior 482
Cloudy88 (14.1%)
↑37.5%prior 64
Rain26 (4.2%)
↓-3.7%prior 27
Snow21 (3.4%)
↓-40.0%prior 35
Blowing Snow4 (0.6%)
Freezing rain/drizzle3 (0.5%)
↓-57.1%prior 7
Severe Winds3 (0.5%)
Other (explain in narrative)2 (0.3%)
Fog, smoke, smog2 (0.3%)
↓-71.4%prior 7

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

Lighting

Daylight436 (69.1%)
↑2.6%prior 425
Dark - roadway lighted109 (17.3%)
↓-6.8%prior 117
Dark - roadway not lighted52 (8.2%)
↓-11.9%prior 59
Dusk20 (3.2%)
↑25.0%prior 16
Dawn8 (1.3%)
↑33.3%prior 6
Dark - unknown roadway lighting6 (1.0%)
↓-53.8%prior 13

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

Road Surface

Dry493 (79.3%)
↓-0.4%prior 495
Wet53 (8.5%)
↓-15.9%prior 63
Snow32 (5.1%)
↓-27.3%prior 44
Gravel19 (3.1%)
↑137.5%prior 8
Ice/frost18 (2.9%)
↑5.9%prior 17
Slush6 (1.0%)
↑20.0%prior 5
Other (explain in narrative)1 (0.2%)

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

Vehicles & Demographics

Ford and Chevrolet vehicles were the top two makes involved in crashes in both years; the count for Fords decreased from 216 to 205, while Chevrolets increased from 161 to 195. In terms of demographics, the '65+' age group saw the largest increase in persons involved in crashes, rising from 197 individuals in 2024 to 225 in 2025. Conversely, involvement for the '35-44' age group decreased from 194 to 169 persons.

Top Vehicle Makes (1,282 vehicles)

1
FORD205 (16%)
↓-5.1%prior 216
2
CHEV195 (15.2%)
↑21.1%prior 161
3
JEEP75 (5.9%)
↑23.0%prior 61
4
KIA70 (5.5%)
↑7.7%prior 65
5
DODG62 (4.8%)
↓-6.1%prior 66
6
GMC58 (4.5%)
↑3.6%prior 56
7
CHEVROLET55 (4.3%)
↑7.8%prior 51
8
TOYO52 (4.1%)
↓-21.2%prior 66
9
BUIC47 (3.7%)
↑11.9%prior 42
10
NISS46 (3.6%)
↓-11.5%prior 52

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

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

Sex Distribution (759 persons with recorded sex)

Male413 (54.4%)
↑1.5%prior 407
Female346 (45.6%)
→0.0%prior 346

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: 770
  • Total persons involved: 1,329
  • Total vehicles involved: 1,282

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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Des Moines County, IA Crash Report — 2025 | ThatCarHitMe.com