Monthly Traffic Safety Analysis

4,417 CRASHES IN
IOWA, IA
MAY 2025

All metrics benchmarked againstMay 2024

In May 2025, Iowa recorded 4,417 vehicle crashes, a 2.9% decrease from the 4,548 crashes reported in May 2024. Overall crash totals, fatalities (24 vs. 29), and injuries (1,462 vs. 1,485) all saw a decline year-over-year. One of the most significant changes occurred in Des Moines, where the number of crashes fell from 526 in the prior year to 403 in the current period.

4,417

▼ -2.9%was 4,548

Total Crash Events

24

▼ -17.2%was 29

Persons Killed

1,462

▼ -1.5%was 1,485

Persons Injured

24

Fatal Crash Events

Note: "Persons Killed" (24) counts individual fatalities across all crash events. "Fatal" in the severity table below (24) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety metrics showed a general improvement in May 2025 compared to the same month in 2024. The total number of crashes decreased by 2.9%, from 4,548 to 4,417. This downward trend was also reflected in casualties, with total fatalities dropping from 29 to 24 and total injuries declining from 1,485 to 1,462.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 3↓-66.7%

0

Cyclists Killed

Prior: 0→0.0%

23

Motorists Killed

Prior: 26↓-11.5%

0

Other Killed

Prior: 0→0.0%

28

Pedestrians Injured

Prior: 30↓-6.7%

45

Cyclists Injured

Prior: 46↓-2.2%

1,385

Motorists Injured

Prior: 1,405↓-1.4%

4

Other Injured

Prior: 4→0.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · 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 largely consistent year-over-year. Friday was the peak day for crashes in both May 2025 (846 crashes) and May 2024 (880 crashes). The peak hour for collisions shifted slightly later in the afternoon, moving from the 3 p.m. hour in the prior year (411 crashes) to the 4 p.m. hour in the current period (395 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The distribution of crash severity was very similar between the two periods, with the fatal crash rate remaining nearly flat at 0.54% in May 2025 versus 0.53% in May 2024. Both periods recorded exactly 24 fatal crash events, though the number of persons killed was lower this year (24 vs. 29). The overall proportion of crashes resulting in any type of injury (serious, minor, or possible) saw a slight decrease from 29.0% of all crashes in the prior year to 28.2% in the current year.

Outcome by Severity (Crash Events)

Fatal24fatal crashes0.5%
→0.0%prior 24
Serious Injury117serious injury crashes2.6%
→0.0%prior 117
Minor Injury454minor injury crashes10.3%
↑0.7%prior 451
Possible Injury677possible injury crashes15.3%
↓-9.7%prior 750
No Injury3,145no injury crashes71.2%
↓-1.9%prior 3,206

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factors for crashes were consistent across both periods, with collisions involving an 'Animal' being the most common cause in both May 2025 (636 crashes) and May 2024 (697 crashes). The count of crashes attributed to animals decreased by 8.8% year-over-year. 'Followed too close' remained the second-leading factor, with its count decreasing from 502 to 492. 'Failure to yield right-of-way from a stop sign' held the third position in both years, with a nearly identical count of 277 in the current period versus 275 in the prior period.

Officer-Reported Primary Contributing Cause

Animal636 (14.4%)↓-8.8%prior 697
Followed too close492 (11.1%)↓-2.0%prior 502
FTYROW: From stop sign277 (6.3%)↑0.7%prior 275
Ran off road - left241 (5.5%)↑7.1%prior 225
Other (explain in narrative): Other230 (5.2%)↓-13.5%prior 266
FTYROW: Making left turn211 (4.8%)↑8.8%prior 194
Lost Control171 (3.9%)↓-0.6%prior 172
Driver Distraction: Other interior distraction163 (3.7%)↓-5.2%prior 172
Ran Traffic Signal143 (3.2%)↓-8.9%prior 157
Operating vehicle in an reckless, erratic, careless, negligent manner137 (3.1%)↑8.7%prior 126

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred under ideal conditions: in clear weather, during daylight hours, and on dry roads. In May 2025, 71.4% of crashes happened during daylight, a marginal increase from 70.6% in May 2024. The number of crashes occurring in rain decreased from 265 to 204, and collisions on wet road surfaces fell from 454 to 372, indicating fewer crashes happened in adverse conditions compared to the previous year.

Weather

Clear2,951 (76.7%)
↓-3.0%prior 3,042
Cloudy650 (16.9%)
↑1.6%prior 640
Rain204 (5.3%)
↓-23.0%prior 265
Severe Winds23 (0.6%)
↑187.5%prior 8
Fog, smoke, smog5 (0.1%)
↓-44.4%prior 9
Blowing sand, soil, dirt4 (0.1%)
Freezing rain/drizzle4 (0.1%)
↓-33.3%prior 6
Other (explain in narrative)4 (0.1%)
Sleet, hail1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Weather condition at time of crash

Lighting

Daylight3,155 (81.3%)
↓-1.7%prior 3,211
Dark - roadway lighted333 (8.6%)
↓-8.3%prior 363
Dark - roadway not lighted263 (6.8%)
↑4.0%prior 253
Dusk59 (1.5%)
↓-39.2%prior 97
Dawn41 (1.1%)
↓-37.9%prior 66
Dark - unknown roadway lighting30 (0.8%)
↓-6.3%prior 32

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Lighting condition field

Road Surface

Dry3,389 (88.1%)
↓-1.3%prior 3,434
Wet372 (9.7%)
↓-18.1%prior 454
Gravel78 (2.0%)
↑1.3%prior 77
Water (standing or moving)3 (0.1%)
Other (explain in narrative)2 (0.1%)
Mud, dirt2 (0.1%)
↓-66.7%prior 6
Slush1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Road surface condition field

Vehicles & Demographics

Top Vehicle Makes (7,583 vehicles)

1
FORD1,165 (15.4%)
↓-3.7%prior 1,210
2
CHEV1,007 (13.3%)
↓-7.2%prior 1,085
3
TOYT383 (5.1%)
↓-4.0%prior 399
4
CHEVROLET382 (5%)
↓-5.7%prior 405
5
JEEP375 (4.9%)
↓-2.3%prior 384
6
HOND324 (4.3%)
↓-8.2%prior 353
7
NISS281 (3.7%)
↑1.4%prior 277
8
GMC258 (3.4%)
↓-2.3%prior 264
9
DODG235 (3.1%)
↓-5.6%prior 249
10
KIA214 (2.8%)
↓-3.2%prior 221

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · Vehicle unit records

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

Sex Distribution (4,947 persons with recorded sex)

Male2,855 (57.7%)
↓-0.5%prior 2,868
Female2,092 (42.3%)
↓-8.4%prior 2,284

Source: Iowa Crash Data · ArcGIS Open Data · 2025-05-01 to 2025-05-31 · 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: 2025-05-01 through 2025-05-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2025-05-01 through 2025-05-31 (31 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,417
  • Total persons involved: 7,907
  • Total vehicles involved: 7,583

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: May 2025." Published September 9, 2026. Reporting period: 2025-05-01 to 2025-05-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/may-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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