Yearly Traffic Safety Analysis

282 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Dickinson County recorded 282 total crashes, a 12.8% increase from the 250 crashes documented in 2020. Total injuries rose 17.6% from 91 to 107, and fatalities increased from 2 to 3. The most significant year-over-year change was a 250% increase in crashes involving a driver under the influence, which rose from 8 incidents in 2020 to 28 in 2021.

282

▲ 12.8%was 250

Total Crash Events

3

▲ 50.0%was 2

Persons Killed

107

▲ 17.6%was 91

Persons Injured

1

▼ -50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash trends in Dickinson County show an increase across key metrics from 2020 to 2021. Total crashes rose by 12.8% from 250 to 282 incidents. Similarly, the number of people injured increased by 17.6% to 107, and fatalities rose from 2 to 3.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 2↑50.0%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 0→%

105

Motorists Injured

Prior: 90↑16.7%

1

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes in Dickinson County showed minor shifts between 2020 and 2021. The peak day for crashes moved from Friday (46 crashes) in 2020 to Saturday (51 crashes) in 2021. The peak hour for collisions remained consistent, occurring at 3 p.m. in both periods, with 24 crashes in 2020 and 25 in 2021.

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the number of fatal crashes decreased from 2 in 2020 to 1 in 2021, the number of fatalities increased from 2 to 3 people. The rate of fatal crashes per 100 collisions fell from 0.8 to 0.35. The count of serious injury crashes doubled, rising from 6 in 2020 to 12 in 2021, representing a proportional increase from 2.4% to 4.3% of all crashes.

Severity is per crash event (most severe injury). 1 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.4%
↓-50.0%prior 2
Serious Injury12serious injury crashes4.3%
↑100.0%prior 6
Minor Injury32minor injury crashes11.3%
↓-5.9%prior 34
Possible Injury42possible injury crashes14.9%
↑31.3%prior 32
No Injury195no injury crashes69.1%
↑10.8%prior 176

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Most severe injury per crash record

Top Contributing Factors

The leading contributing factor in both periods was 'Followed too close,' with the count increasing from 40 incidents in 2020 to 49 in 2021. 'Failure to yield right-of-way from a stop sign' saw a notable rise in count, increasing by 73.3% from 15 to 26 incidents, making it the second most common factor in 2021. Crashes attributed to 'Animal' decreased slightly from 27 to 24, and 'Driving too fast for conditions' dropped from 19 to 14 incidents.

Officer-Reported Primary Contributing Cause

Followed too close49 (17.4%)↑22.5%prior 40
FTYROW: From stop sign26 (9.2%)↑73.3%prior 15
Animal24 (8.5%)↓-11.1%prior 27
FTYROW: Making left turn21 (7.4%)↑31.3%prior 16
Improper Backing15 (5.3%)↑200.0%prior 5
Lost Control15 (5.3%)↑50.0%prior 10
Driving too fast for conditions14 (5%)↓-26.3%prior 19
Ran off road - left12 (4.3%)↑50.0%prior 8
Ran off road - straight11 (3.9%)↑10.0%prior 10
Ran Stop Sign10 (3.5%)→0.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of environmental conditions during crashes remained largely consistent between 2020 and 2021. In both years, the majority of incidents occurred in clear weather, during daylight hours, and on dry road surfaces. Crashes on dry roads accounted for 68.8% of the total in 2021 compared to 67.2% in 2020, while daylight crashes made up 70.9% in 2021 versus 68.0% in 2020, indicating no significant shift in conditions.

Weather

Clear171 (65.3%)
↑11.8%prior 153
Cloudy46 (17.6%)
↑12.2%prior 41
Rain19 (7.3%)
↑111.1%prior 9
Snow8 (3.1%)
↓-46.7%prior 15
Freezing rain/drizzle8 (3.1%)
↑60.0%prior 5
Blowing Snow5 (1.9%)
↓-28.6%prior 7
Fog, smoke, smog3 (1.1%)
Severe Winds2 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Weather condition at time of crash

Lighting

Daylight200 (76.0%)
↑17.6%prior 170
Dark - roadway not lighted29 (11.0%)
↑7.4%prior 27
Dark - roadway lighted22 (8.4%)
↓-31.3%prior 32
Dark - unknown roadway lighting6 (2.3%)
Dusk4 (1.5%)
↓-20.0%prior 5
Dawn2 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Lighting condition field

Road Surface

Dry194 (74.0%)
↑15.5%prior 168
Wet34 (13.0%)
↑142.9%prior 14
Snow16 (6.1%)
↓-33.3%prior 24
Ice/frost11 (4.2%)
↓-52.2%prior 23
Slush4 (1.5%)
Gravel3 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Road surface condition field

Vehicles & Demographics

The most common vehicle makes involved in crashes were consistent year-over-year, with Chevrolet and Ford being the top two in both periods. The number of Ford vehicles involved in crashes increased from 58 to 83, while Chevrolet vehicles rose from 106 to 120. Regarding the age of persons involved, the 55-64 age group saw a significant increase from 49 individuals in 2020 to 83 in 2021. Conversely, involvement for the 16-20 age group decreased from 85 to 77 individuals.

Top Vehicle Makes (493 vehicles)

1
FORD83 (16.8%)
↑43.1%prior 58
2
CHEV63 (12.8%)
↓-4.5%prior 66
3
CHEVROLET57 (11.6%)
↑42.5%prior 40
4
GMC27 (5.5%)
↓-10.0%prior 30
5
JEEP25 (5.1%)
↑13.6%prior 22
6
TOYT20 (4.1%)
↓-25.9%prior 27
7
DODGE20 (4.1%)
↑17.6%prior 17
8
CHRY19 (3.9%)
↑90.0%prior 10
9
TOYOTA15 (3%)
→0.0%prior 15
10
CHRYSLER10 (2%)
↑66.7%prior 6

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · Vehicle unit records

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

Sex Distribution (414 persons with recorded sex)

Male225 (54.3%)
↓-1.3%prior 228
Female189 (45.7%)
↑13.9%prior 166

Source: Iowa Crash Data · ArcGIS Open Data · 2021-01-01 to 2021-12-31 · 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: 2021-01-01 through 2021-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2021-01-01 through 2021-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 282
  • Total persons involved: 607
  • Total vehicles involved: 493

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: 2021." Published September 9, 2026. Reporting period: 2021-01-01 to 2021-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2021-annual-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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