Monthly Traffic Safety Analysis

4,673 CRASHES IN
IOWA, IA
JUNE 2021

All metrics benchmarked againstJune 2020

In June 2021, Iowa recorded 4,673 traffic crashes, a 17.9% increase from the 3,963 crashes reported in June 2020. This year-over-year rise was accompanied by a significant increase in both injuries, which climbed 18.5% from 1,419 to 1,682, and fatalities, which rose 37.5% from 24 to 33.

4,673

▲ 17.9%was 3,963

Total Crash Events

33

▲ 37.5%was 24

Persons Killed

1,682

▲ 18.5%was 1,419

Persons Injured

32

▲ 33.3%was 24

Fatal Crash Events

Note: "Persons Killed" (33) counts individual fatalities across all crash events. "Fatal" in the severity table below (32) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Iowa saw a significant year-over-year increase in June 2021 compared to the same month in 2020. The total number of collisions rose by 710, from 3,963 to 4,673, representing a 17.9% increase. This upward trend was also reflected in crash severity, with total injuries increasing by 18.5% and fatalities rising by 37.5%.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 3→0.0%

3

Cyclists Killed

Prior: 0→%

27

Motorists Killed

Prior: 21↑28.6%

0

Other Killed

Prior: 0→0.0%

24

Pedestrians Injured

Prior: 18↑33.3%

37

Cyclists Injured

Prior: 33↑12.1%

1,612

Motorists Injured

Prior: 1,366↑18.0%

9

Other Injured

Prior: 2↑350.0%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. The peak day for crashes moved from Monday (701 crashes) in June 2020 to Wednesday (774 crashes) in June 2021. The single busiest hour also shifted slightly later in the day, from the 3 p.m. hour in the prior year to the 4 p.m. hour in the current period, which saw 378 crashes.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes increased in June 2021 compared to the prior year. The number of fatal crashes rose from 24 to 32, and the corresponding fatal crash rate increased from 0.61 to 0.68 per 100 crashes. While the share of crashes resulting in serious injuries decreased from 3.2% to 2.6%, the proportion of crashes involving minor injuries grew from 11.0% to 11.8% of all incidents.

Severity is per crash event (most severe injury). 32 fatal crash events resulted in 33 persons killed.

Outcome by Severity (Crash Events)

Fatal32fatal crashes0.7%
↑33.3%prior 24
Serious Injury120serious injury crashes2.6%
↓-4.8%prior 126
Minor Injury551minor injury crashes11.8%
↑27.0%prior 434
Possible Injury732possible injury crashes15.7%
↑20.2%prior 609
No Injury3,238no injury crashes69.3%
↑16.9%prior 2,770

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Most severe injury per crash record

Top Contributing Factors

The top two contributing factors remained consistent, with collisions involving an 'Animal' (702 crashes) and 'Followed too close' (526 crashes) ranking first and second in both June 2020 and June 2021. However, the count of crashes attributed to 'Followed too close' increased substantially by 38.1%, rising from 381 incidents in the prior year. Other notable increases in crash counts were seen for 'Lost Control' (from 204 to 250) and 'Ran off road - left' (from 235 to 265).

Officer-Reported Primary Contributing Cause

Animal702 (15%)↑6.2%prior 661
Followed too close526 (11.3%)↑38.1%prior 381
Other (explain in narrative): Other295 (6.3%)↑32.9%prior 222
Ran off road - left265 (5.7%)↑12.8%prior 235
Lost Control250 (5.3%)↑22.5%prior 204
FTYROW: From stop sign218 (4.7%)↑4.3%prior 209
FTYROW: Making left turn179 (3.8%)↑24.3%prior 144
Operating vehicle in an reckless, erratic, careless, negligent manner168 (3.6%)↑34.4%prior 125
Driver Distraction: Other interior distraction166 (3.6%)↑38.3%prior 120
Other (explain in narrative): No improper action146 (3.1%)↑49.0%prior 98

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

A higher proportion of crashes in June 2021 occurred under favorable environmental conditions compared to June 2020. The share of crashes taking place in daylight increased from 68.5% to 70.8%, while incidents on dry road surfaces rose from 76.3% to 78.8% of the total. Conversely, the proportion of crashes occurring in rain decreased from 5.1% to 3.8%, indicating the overall increase in collisions was not driven by worsening weather or road conditions.

Weather

Clear3,360 (82.5%)
↑23.0%prior 2,732
Cloudy509 (12.5%)
↑4.7%prior 486
Rain179 (4.4%)
↓-12.3%prior 204
Fog, smoke, smog11 (0.3%)
Other (explain in narrative)3 (0.1%)
↓-50.0%prior 6
Blowing sand, soil, dirt3 (0.1%)
Freezing rain/drizzle3 (0.1%)
Severe Winds3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Weather condition at time of crash

Lighting

Daylight3,309 (80.8%)
↑21.8%prior 2,716
Dark - roadway lighted335 (8.2%)
↑15.9%prior 289
Dark - roadway not lighted293 (7.2%)
↑2.1%prior 287
Dusk83 (2.0%)
↓-3.5%prior 86
Dawn59 (1.4%)
↑13.5%prior 52
Dark - unknown roadway lighting15 (0.4%)
↑36.4%prior 11

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Lighting condition field

Road Surface

Dry3,681 (90.2%)
↑21.8%prior 3,022
Wet296 (7.3%)
↓-8.6%prior 324
Gravel92 (2.3%)
↑17.9%prior 78
Mud, dirt3 (0.1%)
↓-50.0%prior 6
Sand2 (0.0%)
Water (standing or moving)2 (0.0%)
Ice/frost1 (0.0%)
Other (explain in narrative)1 (0.0%)
↓-85.7%prior 7
Oil1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes remained consistent, with Ford and Chevrolet models leading in both periods. The number of vehicles identified as 'CHEVROLET' involved in crashes saw a 37.6% increase, from 511 to 703. An analysis of persons involved shows a demographic shift, with the representation of individuals aged 65 and older increasing from 10.0% of all persons in June 2020 to 11.1% in June 2021.

Top Vehicle Makes (8,041 vehicles)

1
FORD1,231 (15.3%)
↑24.8%prior 986
2
CHEV862 (10.7%)
↑4.5%prior 825
3
CHEVROLET703 (8.7%)
↑37.6%prior 511
4
TOYT309 (3.8%)
↑34.9%prior 229
5
JEEP303 (3.8%)
↑13.5%prior 267
6
GMC271 (3.4%)
↑11.5%prior 243
7
HOND252 (3.1%)
↑24.1%prior 203
8
DODG246 (3.1%)
↓-3.9%prior 256
9
NR232 (2.9%)
↑4.0%prior 223
10
TOYOTA228 (2.8%)
↑45.2%prior 157

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · Vehicle unit records

1,327 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (7,104 persons with recorded sex)

Male4,033 (56.8%)
↑14.6%prior 3,518
Female3,071 (43.2%)
↑27.9%prior 2,402

Source: Iowa Crash Data · ArcGIS Open Data · 2021-06-01 to 2021-06-30 · 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: 2021-06-01 through 2021-06-30
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-06-01 through 2021-06-30 (30 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 4,673
  • Total persons involved: 10,847
  • Total vehicles involved: 8,041

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 2021." Published September 9, 2026. Reporting period: 2021-06-01 to 2021-06-30. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/june-2021-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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