Monthly Traffic Safety Analysis

4,416 CRASHES IN
IOWA, IA
JUNE 2024

All metrics benchmarked againstJune 2023

In June 2024, Iowa recorded 4,416 vehicle crashes, a 2.0% decrease from the 4,508 crashes reported in June 2023. This overall decline was accompanied by a 15.8% drop in fatalities, from 38 to 32, and a 3.3% reduction in injuries. The most notable shift was the decrease in the number of crashes resulting in possible injuries, which fell from 700 to 629 year-over-year.

4,416

▼ -2.0%was 4,508

Total Crash Events

32

▼ -15.8%was 38

Persons Killed

1,504

▼ -3.3%was 1,555

Persons Injured

30

▼ -11.8%was 34

Fatal Crash Events

Note: "Persons Killed" (32) counts individual fatalities across all crash events. "Fatal" in the severity table below (30) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic collisions in Iowa showed a downward trend in June 2024 compared to the same month in the previous year. The total number of crashes fell by 92, from 4,508 to 4,416, representing a 2.0% decrease. This trend extended to crash outcomes, with total fatalities dropping from 38 to 32 and total injuries decreasing from 1,555 to 1,504.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 3↓-33.3%

0

Cyclists Killed

Prior: 0→0.0%

30

Motorists Killed

Prior: 34↓-11.8%

0

Other Killed

Prior: 1↓-100.0%

23

Pedestrians Injured

Prior: 23→0.0%

36

Cyclists Injured

Prior: 45↓-20.0%

1,434

Motorists Injured

Prior: 1,477↓-2.9%

11

Other Injured

Prior: 10↑10.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · 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 broadly consistent year-over-year, with Friday being the peak day for crashes in both June 2023 (916 crashes) and June 2024 (702 crashes). However, the peak hour for collisions shifted slightly, moving from the 3 p.m. hour in the prior year (345 crashes) to the 4 p.m. hour in the current period (334 crashes). Weekend crashes on Sunday saw a notable increase from 441 to 637 incidents.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes decreased slightly in June 2024 compared to the prior year. The fatal crash rate fell from 0.75% to 0.68% of all crashes. The proportion of collisions resulting in any type of injury (fatal, serious, minor, or possible) also declined, accounting for 29.1% of crashes in the current period versus 30.8% in June 2023. Specifically, crashes involving possible injuries dropped from 700 to 629.

Severity is per crash event (most severe injury). 30 fatal crash events resulted in 32 persons killed.

Outcome by Severity (Crash Events)

Fatal30fatal crashes0.7%
↓-11.8%prior 34
Serious Injury138serious injury crashes3.1%
↑2.2%prior 135
Minor Injury488minor injury crashes11.1%
↓-6.2%prior 520
Possible Injury629possible injury crashes14.2%
↓-10.1%prior 700
No Injury3,131no injury crashes70.9%
↑0.4%prior 3,119

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both periods, with counts rising from 758 to 769. Following too closely was the second most common factor, also increasing in count from 480 to 494. A notable change was the decrease in crashes attributed to losing control, which fell from 227 incidents in June 2023 to 172 in June 2024. Conversely, crashes where a driver failed to keep in the proper lane increased from 44 to 66.

Officer-Reported Primary Contributing Cause

Animal769 (17.4%)↑1.5%prior 758
Followed too close494 (11.2%)↑2.9%prior 480
Ran off road - left233 (5.3%)↓-2.1%prior 238
Other (explain in narrative): Other230 (5.2%)↓-14.5%prior 269
FTYROW: From stop sign222 (5%)↑5.2%prior 211
Lost Control172 (3.9%)↓-24.2%prior 227
FTYROW: Making left turn171 (3.9%)↓-20.8%prior 216
Ran Traffic Signal156 (3.5%)↓-1.3%prior 158
Driver Distraction: Other interior distraction139 (3.1%)↑0.7%prior 138
Operating vehicle in an reckless, erratic, careless, negligent manner137 (3.1%)↓-7.4%prior 148

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions shifted slightly toward more adverse weather compared to the previous year. The proportion of crashes occurring on wet road surfaces increased from 5.5% in June 2023 to 7.5% in June 2024. This corresponded with a rise in the share of crashes happening during rain, which grew from 3.4% to 4.8% of all incidents. Consequently, the share of crashes on dry roads and in clear weather decreased year-over-year.

Weather

Clear3,003 (80.3%)
↓-4.3%prior 3,139
Cloudy511 (13.7%)
↓-4.5%prior 535
Rain212 (5.7%)
↑38.6%prior 153
Severe Winds9 (0.2%)
Fog, smoke, smog4 (0.1%)
↓-89.2%prior 37
Blowing sand, soil, dirt1 (0.0%)
Other (explain in narrative)1 (0.0%)
↓-85.7%prior 7

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Weather condition at time of crash

Lighting

Daylight2,984 (78.9%)
↓-4.6%prior 3,127
Dark - roadway lighted354 (9.4%)
↑4.1%prior 340
Dark - roadway not lighted282 (7.5%)
↑0.7%prior 280
Dusk90 (2.4%)
↑26.8%prior 71
Dawn45 (1.2%)
↓-19.6%prior 56
Dark - unknown roadway lighting28 (0.7%)
↑40.0%prior 20

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Lighting condition field

Road Surface

Dry3,344 (89.0%)
↓-5.7%prior 3,545
Wet333 (8.9%)
↑33.7%prior 249
Gravel70 (1.9%)
↓-18.6%prior 86
Water (standing or moving)5 (0.1%)
Mud, dirt2 (0.1%)
Sand1 (0.0%)
Other (explain in narrative)1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Ford and Chevrolet models being the most frequent. The number of Ford vehicles in crashes increased from 1,188 to 1,202, while the count for 'CHEV' models decreased from 1,051 to 932. An analysis of persons involved shows the 26-34 age group's share increased from 16.5% to 17.3%, while the 16-20 age group's representation decreased slightly from 14.2% to 13.6%.

Top Vehicle Makes (7,426 vehicles)

1
FORD1,202 (16.2%)
↑1.2%prior 1,188
2
CHEV932 (12.6%)
↓-11.3%prior 1,051
3
CHEVROLET410 (5.5%)
↑9.9%prior 373
4
TOYT348 (4.7%)
↑1.2%prior 344
5
JEEP291 (3.9%)
↑0.3%prior 290
6
HOND290 (3.9%)
↓-4.0%prior 302
7
GMC283 (3.8%)
↑7.2%prior 264
8
KIA245 (3.3%)
↑11.9%prior 219
9
NISS231 (3.1%)
↓-13.5%prior 267
10
DODG231 (3.1%)
↓-23.5%prior 302

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · Vehicle unit records

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

Sex Distribution (4,623 persons with recorded sex)

Male2,693 (58.3%)
↓-33.8%prior 4,066
Female1,930 (41.7%)
↓-31.3%prior 2,809

Source: Iowa Crash Data · ArcGIS Open Data · 2024-06-01 to 2024-06-30 · 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: 2024-06-01 through 2024-06-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-06-01 through 2024-06-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,416
  • Total persons involved: 7,792
  • Total vehicles involved: 7,426

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: June 2024." Published September 9, 2026. Reporting period: 2024-06-01 to 2024-06-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/june-2024-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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