Yearly Traffic Safety Analysis

219 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Crawford County recorded 219 total vehicle crashes, representing a 16.5% increase from the 188 crashes documented in the prior year, 2020. This period also saw a rise in total injuries from 62 to 67 and an increase in fatalities from one to two. The most notable year-over-year shift was the overall growth in crash volume across the county.

219

▲ 16.5%was 188

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

67

▲ 8.1%was 62

Persons Injured

2

▲ 100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 Crawford County show a year-over-year increase across key metrics. Total crashes rose by 16.5%, from 188 in 2020 to 219 in 2021. This upward trend was also reflected in crash outcomes, with total injuries increasing by 8.1% from 62 to 67, and fatalities doubling from one to two.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 1↑100.0%

67

Motorists Injured

Prior: 62↑8.1%

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 temporal patterns of crashes showed some shifts between the two periods. While the afternoon hour of 3 p.m. remained the peak time for crashes in both 2020 (20 crashes) and 2021 (21 crashes), the peak day for incidents moved. In 2021, Friday was the most common day for crashes with 44 incidents, a shift from Thursday in 2020, which saw 34 crashes.

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

The severity of crashes shifted year-over-year, with an increase in fatal and serious injury incidents. The number of fatal crashes doubled from one in 2020 to two in 2021, and crashes resulting in serious injuries increased from 6 to 9. Concurrently, the proportion of crashes resulting in no injury rose from 71.8% to 75.3% of all incidents, while the share of 'possible injury' crashes decreased from 18.1% to 12.3%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.9%
↑100.0%prior 1
Serious Injury9serious injury crashes4.1%
↑50.0%prior 6
Minor Injury16minor injury crashes7.3%
↑33.3%prior 12
Possible Injury27possible injury crashes12.3%
↓-20.6%prior 34
No Injury165no injury crashes75.3%
↑22.2%prior 135

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 factors to crashes showed some changes between periods. Collisions involving an animal remained the top factor, with the count of such incidents increasing from 28 in 2020 to 37 in 2021. 'Failure to yield from a stop sign' saw a decrease in count from 19 to 15, moving it from the second to the third most-cited factor. Incidents attributed to 'Followed too close' increased in count from 11 to 14.

Officer-Reported Primary Contributing Cause

Animal37 (16.9%)↑32.1%prior 28
Other (explain in narrative): Other20 (9.1%)↑33.3%prior 15
FTYROW: From stop sign15 (6.8%)↓-21.1%prior 19
Followed too close14 (6.4%)↑27.3%prior 11
Driver Distraction: Other interior distraction14 (6.4%)↑7.7%prior 13
Lost Control14 (6.4%)↓-12.5%prior 16
Ran off road - left11 (5%)↑10.0%prior 10
Ran off road - straight9 (4.1%)↑50.0%prior 6
Ran Stop Sign8 (3.7%)
Made improper turn6 (2.7%)

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

Road & Environmental Conditions

While most crashes in both years occurred in clear weather on dry roads, there was a notable shift in incidents involving adverse road conditions. Crashes on roads with ice or frost more than doubled, increasing from 8 incidents in 2020 to 18 in 2021. The proportion of crashes occurring in daylight decreased from 68.1% of all crashes in 2020 to 60.7% in 2021.

Weather

Clear125 (68.3%)
↑16.8%prior 107
Cloudy38 (20.8%)
↑5.6%prior 36
Freezing rain/drizzle6 (3.3%)
Snow5 (2.7%)
↓-50.0%prior 10
Rain4 (2.2%)
Blowing Snow3 (1.6%)
Fog, smoke, smog1 (0.5%)
Other (explain in narrative)1 (0.5%)

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

Lighting

Daylight133 (72.3%)
↑3.9%prior 128
Dark - roadway not lighted22 (12.0%)
↑37.5%prior 16
Dark - roadway lighted17 (9.2%)
↑70.0%prior 10
Dusk6 (3.3%)
Dawn5 (2.7%)
→0.0%prior 5
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry137 (74.5%)
↑15.1%prior 119
Ice/frost18 (9.8%)
↑125.0%prior 8
Snow14 (7.6%)
↑7.7%prior 13
Wet8 (4.3%)
↓-50.0%prior 16
Gravel6 (3.3%)
Slush1 (0.5%)

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

Vehicles & Demographics

An analysis of persons involved in crashes reveals significant shifts in age group representation. The number of individuals in the 26-34 age group involved in crashes more than doubled, rising from 41 in 2020 to 85 in 2021, and the 65+ age group saw a substantial increase from 44 to 73. Conversely, involvement for the 45-54 age group decreased from 69 to 36. Ford and Chevrolet remained the most common vehicle makes in collisions, with the count of both increasing year-over-year.

Top Vehicle Makes (370 vehicles)

1
FORD80 (21.6%)
↑53.8%prior 52
2
CHEV45 (12.2%)
↑25.0%prior 36
3
CHEVROLET36 (9.7%)
↑71.4%prior 21
4
GMC25 (6.8%)
↑78.6%prior 14
5
DODG21 (5.7%)
↑75.0%prior 12
6
DODGE11 (3%)
↓-8.3%prior 12
7
JEEP10 (2.7%)
↓-41.2%prior 17
8
TOYOTA8 (2.2%)
↓-20.0%prior 10
9
TOYT8 (2.2%)
↑14.3%prior 7
10
TOYO7 (1.9%)

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

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

Sex Distribution (305 persons with recorded sex)

Male185 (60.7%)
↑6.9%prior 173
Female120 (39.3%)
↑10.1%prior 109

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: 219
  • Total persons involved: 464
  • Total vehicles involved: 370

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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