Monthly Traffic Safety Analysis

4,357 CRASHES IN
IOWA, IA
JUNE 2022

All metrics benchmarked againstJune 2021

In June 2022, Iowa recorded 4,357 traffic crashes, representing a 6.8% decrease from the 4,673 crashes documented in June 2021. This overall reduction in incidents was accompanied by a notable 36.4% drop in traffic fatalities, which fell from 33 to 21 year-over-year. While most metrics saw improvement, the share of crashes resulting in serious injuries increased.

4,357

▼ -6.8%was 4,673

Total Crash Events

21

▼ -36.4%was 33

Persons Killed

1,518

▼ -9.8%was 1,682

Persons Injured

19

▼ -40.6%was 32

Fatal Crash Events

Note: "Persons Killed" (21) counts individual fatalities across all crash events. "Fatal" in the severity table below (19) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Iowa showed a general improvement in June 2022 compared to the same month in 2021. The total number of crashes decreased by 6.8%, from 4,673 to 4,357. This downward trend extended to crash outcomes, with total injuries falling by 9.7% and total fatalities decreasing by 36.4%.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 3↓-66.7%

1

Cyclists Killed

Prior: 3↓-66.7%

19

Motorists Killed

Prior: 27↓-29.6%

0

Other Killed

Prior: 0→0.0%

30

Pedestrians Injured

Prior: 24↑25.0%

29

Cyclists Injured

Prior: 37↓-21.6%

1,458

Motorists Injured

Prior: 1,612↓-9.6%

1

Other Injured

Prior: 9↓-88.9%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes shifted slightly between the two periods. The peak day for crashes moved from Wednesday (774 incidents) in 2021 to Thursday (775 incidents) in 2022, with a nearly identical volume. The busiest hour for collisions shifted one hour later, from the 4 p.m. hour in 2021 (378 crashes) to the 5 p.m. hour in 2022 (339 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The overall severity of crashes decreased from June 2021 to June 2022, with the fatal crash rate falling from 0.68% to 0.44%. The absolute number of fatal crashes also declined from 32 to 19. While the proportion of crashes involving minor or possible injuries remained relatively stable, the share of crashes resulting in serious injuries increased from 2.6% to 3.3% of all incidents.

Severity is per crash event (most severe injury). 19 fatal crash events resulted in 21 persons killed.

Outcome by Severity (Crash Events)

Fatal19fatal crashes0.4%
↓-40.6%prior 32
Serious Injury144serious injury crashes3.3%
↑20.0%prior 120
Minor Injury482minor injury crashes11.1%
↓-12.5%prior 551
Possible Injury674possible injury crashes15.5%
↓-7.9%prior 732
No Injury3,038no injury crashes69.7%
↓-6.2%prior 3,238

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Most severe injury per crash record

Top Contributing Factors

The top contributing factors remained consistent, though their counts and rankings changed year-over-year. Crashes involving an 'Animal' became the leading cause in June 2022, with the count of such incidents increasing by 10.8% from 702 to 778. In contrast, crashes attributed to 'Followed too close' saw a 17.7% decrease in count from 526 to 433, moving it to the second-ranked factor. Crashes due to 'Operating vehicle in a reckless, erratic, careless, negligent manner' also saw a significant count-based reduction of 33.3%, from 168 to 112 incidents.

Officer-Reported Primary Contributing Cause

Animal778 (17.9%)↑10.8%prior 702
Followed too close433 (9.9%)↓-17.7%prior 526
Other (explain in narrative): Other283 (6.5%)↓-4.1%prior 295
FTYROW: From stop sign240 (5.5%)↑10.1%prior 218
Lost Control226 (5.2%)↓-9.6%prior 250
Ran off road - left215 (4.9%)↓-18.9%prior 265
FTYROW: Making left turn211 (4.8%)↑17.9%prior 179
Ran Traffic Signal140 (3.2%)↑8.5%prior 129
Ran Stop Sign134 (3.1%)↓-4.3%prior 140
Driver Distraction: Other interior distraction115 (2.6%)↓-30.7%prior 166

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of environmental conditions during crashes remained largely consistent year-over-year. In June 2022, 73.1% of crashes occurred in clear weather, compared to 71.9% in June 2021. Crashes on dry road surfaces accounted for 78.4% of incidents, nearly unchanged from 78.8% in the prior year. The proportion of crashes happening in daylight decreased slightly from 70.8% to 68.9%.

Weather

Clear3,184 (85.1%)
↓-5.2%prior 3,360
Cloudy407 (10.9%)
↓-20.0%prior 509
Rain132 (3.5%)
↓-26.3%prior 179
Fog, smoke, smog8 (0.2%)
↓-27.3%prior 11
Severe Winds4 (0.1%)
Other (explain in narrative)3 (0.1%)
Blowing sand, soil, dirt1 (0.0%)
Freezing rain/drizzle1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Weather condition at time of crash

Lighting

Daylight3,001 (79.9%)
↓-9.3%prior 3,309
Dark - roadway lighted330 (8.8%)
↓-1.5%prior 335
Dark - roadway not lighted276 (7.3%)
↓-5.8%prior 293
Dusk83 (2.2%)
→0.0%prior 83
Dawn55 (1.5%)
↓-6.8%prior 59
Dark - unknown roadway lighting13 (0.3%)
↓-13.3%prior 15

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Lighting condition field

Road Surface

Dry3,417 (91.1%)
↓-7.2%prior 3,681
Wet214 (5.7%)
↓-27.7%prior 296
Gravel108 (2.9%)
↑17.4%prior 92
Mud, dirt7 (0.2%)
Other (explain in narrative)3 (0.1%)
Water (standing or moving)1 (0.0%)
Ice/frost1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Road surface condition field

Vehicles & Demographics

The top vehicle makes involved in crashes were consistent across both periods, led by Ford and Chevrolet. The count of Ford vehicles involved in crashes decreased from 1,231 to 1,103 year-over-year. The age distribution of persons involved in crashes showed minor changes; the share of individuals aged 16-20 decreased from 12.6% to 12.2% of the total, while the proportion of those aged 65 and older increased slightly from 11.1% to 11.3%.

Top Vehicle Makes (7,359 vehicles)

1
FORD1,103 (15%)
↓-10.4%prior 1,231
2
CHEV1,056 (14.3%)
↑22.5%prior 862
3
CHEVROLET406 (5.5%)
↓-42.2%prior 703
4
TOYT308 (4.2%)
↓-0.3%prior 309
5
DODG288 (3.9%)
↑17.1%prior 246
6
HOND285 (3.9%)
↑13.1%prior 252
7
JEEP268 (3.6%)
↓-11.6%prior 303
8
GMC228 (3.1%)
↓-15.9%prior 271
9
NR201 (2.7%)
↓-13.4%prior 232
10
NISS200 (2.7%)
↓-3.4%prior 207

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · Vehicle unit records

1,162 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (6,642 persons with recorded sex)

Male3,819 (57.5%)
↓-5.3%prior 4,033
Female2,823 (42.5%)
↓-8.1%prior 3,071

Source: Iowa Crash Data · ArcGIS Open Data · 2022-06-01 to 2022-06-30 · 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: 2022-06-01 through 2022-06-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-06-01 through 2022-06-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,357
  • Total persons involved: 10,016
  • Total vehicles involved: 7,359

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 2022." Published September 9, 2026. Reporting period: 2022-06-01 to 2022-06-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/june-2022-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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