Monthly Traffic Safety Analysis

4,508 CRASHES IN
IOWA, IA
JUNE 2023

All metrics benchmarked againstJune 2022

In June 2023, there were 4,508 traffic crashes, a 3.5% increase from the 4,357 crashes recorded in June 2022. The most notable year-over-year change was a significant increase in crash severity, with total fatalities rising 81% from 21 to 38, and fatal crashes increasing from 19 to 34.

4,508

▲ 3.5%was 4,357

Total Crash Events

38

▲ 81.0%was 21

Persons Killed

1,555

▲ 2.4%was 1,518

Persons Injured

34

▲ 78.9%was 19

Fatal Crash Events

Note: "Persons Killed" (38) counts individual fatalities across all crash events. "Fatal" in the severity table below (34) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash trends indicate an increase in both volume and severity compared to the same month last year. Total crashes rose by 151 incidents (a 3.5% increase), and total injuries saw a slight uptick from 1,518 to 1,555. Most significantly, the number of fatalities increased sharply from 21 in June 2022 to 38 in June 2023.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 1↑200.0%

0

Cyclists Killed

Prior: 1↓-100.0%

34

Motorists Killed

Prior: 19↑78.9%

1

Other Killed

Prior: 0→%

23

Pedestrians Injured

Prior: 30↓-23.3%

45

Cyclists Injured

Prior: 29↑55.2%

1,477

Motorists Injured

Prior: 1,458↑1.3%

10

Other Injured

Prior: 1↑900.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal pattern of crashes shifted from the prior year. The peak day for crashes moved from Thursday (775 crashes) in June 2022 to Friday (916 crashes) in June 2023. The peak hour also shifted earlier, from the 5 p.m. hour in the prior period (339 crashes) to the 3 p.m. hour in the current period (345 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

Crash severity worsened significantly year-over-year. The number of fatal crashes increased by 79%, from 19 in June 2022 to 34 in June 2023, and the fatal crash rate grew from 0.44% to 0.75% of all crashes. While the proportion of crashes resulting in any injury remained stable at approximately 30% for both periods, the share of serious injury crashes decreased slightly from 3.3% to 3.0%.

Severity is per crash event (most severe injury). 34 fatal crash events resulted in 38 persons killed.

Outcome by Severity (Crash Events)

Fatal34fatal crashes0.8%
↑78.9%prior 19
Serious Injury135serious injury crashes3%
↓-6.3%prior 144
Minor Injury520minor injury crashes11.5%
↑7.9%prior 482
Possible Injury700possible injury crashes15.5%
↑3.9%prior 674
No Injury3,119no injury crashes69.2%
↑2.7%prior 3,038

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Most severe injury per crash record

Top Contributing Factors

Collisions with animals remained the leading contributing factor in both periods, though the count decreased slightly from 778 to 758. "Followed too close" was the second-most common factor, with its count increasing by 10.9% from 433 to 480 crashes. Incidents of "Ran off road - left" increased by 10.7% (from 215 to 238), moving it up in the rankings, while crashes from "FTYROW: From stop sign" decreased in count by 12.1% from 240 to 211.

Officer-Reported Primary Contributing Cause

Animal758 (16.8%)↓-2.6%prior 778
Followed too close480 (10.6%)↑10.9%prior 433
Other (explain in narrative): Other269 (6%)↓-4.9%prior 283
Ran off road - left238 (5.3%)↑10.7%prior 215
Lost Control227 (5%)↑0.4%prior 226
FTYROW: Making left turn216 (4.8%)↑2.4%prior 211
FTYROW: From stop sign211 (4.7%)↓-12.1%prior 240
Ran Traffic Signal158 (3.5%)↑12.9%prior 140
Operating vehicle in an reckless, erratic, careless, negligent manner148 (3.3%)↑32.1%prior 112
Driver Distraction: Other interior distraction138 (3.1%)↑20.0%prior 115

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

Crash conditions remained largely consistent year-over-year, with no major shifts in environmental factors. In both June 2023 and June 2022, the majority of crashes occurred in daylight (69.4% vs 68.9%), in clear weather (69.6% vs 73.1%), and on dry road surfaces (78.6% vs 78.4%). The proportion of crashes under adverse conditions did not change significantly between the two periods.

Weather

Clear3,139 (80.9%)
↓-1.4%prior 3,184
Cloudy535 (13.8%)
↑31.4%prior 407
Rain153 (3.9%)
↑15.9%prior 132
Fog, smoke, smog37 (1.0%)
↑362.5%prior 8
Other (explain in narrative)7 (0.2%)
Blowing sand, soil, dirt4 (0.1%)
Freezing rain/drizzle2 (0.1%)
Severe Winds2 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Weather condition at time of crash

Lighting

Daylight3,127 (80.3%)
↑4.2%prior 3,001
Dark - roadway lighted340 (8.7%)
↑3.0%prior 330
Dark - roadway not lighted280 (7.2%)
↑1.4%prior 276
Dusk71 (1.8%)
↓-14.5%prior 83
Dawn56 (1.4%)
↑1.8%prior 55
Dark - unknown roadway lighting20 (0.5%)
↑53.8%prior 13

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Lighting condition field

Road Surface

Dry3,545 (91.1%)
↑3.7%prior 3,417
Wet249 (6.4%)
↑16.4%prior 214
Gravel86 (2.2%)
↓-20.4%prior 108
Other (explain in narrative)4 (0.1%)
Mud, dirt4 (0.1%)
↓-42.9%prior 7
Sand1 (0.0%)
Water (standing or moving)1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes, primarily Ford and Chevrolet models, remained consistent between the two periods. The age demographics of individuals involved in crashes showed some changes. The proportion of people in the 35-44 age group increased from 15.9% to 17.4% of all persons involved, while the 26-34 age group's share decreased from 18.5% to 16.5%.

Top Vehicle Makes (7,579 vehicles)

1
FORD1,188 (15.7%)
↑7.7%prior 1,103
2
CHEV1,051 (13.9%)
↓-0.5%prior 1,056
3
CHEVROLET373 (4.9%)
↓-8.1%prior 406
4
TOYT344 (4.5%)
↑11.7%prior 308
5
DODG302 (4%)
↑4.9%prior 288
6
HOND302 (4%)
↑6.0%prior 285
7
JEEP290 (3.8%)
↑8.2%prior 268
8
NISS267 (3.5%)
↑33.5%prior 200
9
GMC264 (3.5%)
↑15.8%prior 228
10
KIA219 (2.9%)
↑10.6%prior 198

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · Vehicle unit records

1,193 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,875 persons with recorded sex)

Male4,066 (59.1%)
↑6.5%prior 3,819
Female2,809 (40.9%)
↓-0.5%prior 2,823

Source: Iowa Crash Data · ArcGIS Open Data · 2023-06-01 to 2023-06-30 · 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: 2023-06-01 through 2023-06-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-06-01 through 2023-06-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,508
  • Total persons involved: 10,347
  • Total vehicles involved: 7,579

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 2023." Published September 9, 2026. Reporting period: 2023-06-01 to 2023-06-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/june-2023-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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