Yearly Traffic Safety Analysis

206 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Clarke County recorded 206 total crashes, a 41.1% increase from the 146 crashes reported in 2020. The most significant year-over-year change was the increase in traffic fatalities, which rose from zero in 2020 to four in 2021. These fatalities occurred across two separate fatal crash events during the current period.

206

▲ 41.1%was 146

Total Crash Events

4

Persons Killed

46

▲ 4.5%was 44

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (4) 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

Overall, traffic collisions in Clarke County showed a significant upward trend from 2020 to 2021. The total number of crashes increased by 41.1%, from 146 to 206. While the total number of injuries remained relatively stable with a 4.5% increase from 44 to 46, fatalities rose from zero in 2020 to four in 2021.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

46

Motorists Injured

Prior: 43↑7.0%

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 temporal patterns of crashes shifted between the two periods. In 2021, the peak day for crashes was Thursday with 34 incidents, a change from 2020 when crashes peaked on Monday and Friday with 26 incidents each. The peak hour for collisions also shifted later in the day, from 1 p.m. in 2020 (19 crashes) to 4 p.m. in 2021 (19 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

Crash severity worsened in 2021, marked by the appearance of two fatal crashes which accounted for 1% of all crashes, whereas there were none in 2020. This resulted in four fatalities compared to zero in the prior year. While the count of serious injury crashes decreased slightly from four to three, minor injury crashes increased from 12 in 2020 to 21 in 2021.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1%
Serious Injury3serious injury crashes1.5%
↓-25.0%prior 4
Minor Injury21minor injury crashes10.2%
↑75.0%prior 12
Possible Injury16possible injury crashes7.8%
↓-15.8%prior 19
No Injury164no injury crashes79.6%
↑47.7%prior 111

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

Collisions involving an animal remained the top contributing factor in both periods, with the count of such incidents increasing from 36 in 2020 to 49 in 2021. Crashes attributed to 'Followed too close' saw a significant increase in count, rising from 4 to 15 incidents. 'Lost Control' also became more prevalent, with its count increasing from 10 to 15, tying it for the second-most common factor in 2021.

Officer-Reported Primary Contributing Cause

Animal49 (23.8%)↑36.1%prior 36
Followed too close15 (7.3%)
Lost Control15 (7.3%)↑50.0%prior 10
FTYROW: From stop sign11 (5.3%)↑83.3%prior 6
Ran off road - left10 (4.9%)↑66.7%prior 6
Ran off road - straight10 (4.9%)↓-9.1%prior 11
Other (explain in narrative): Other9 (4.4%)↓-25.0%prior 12
Driver Distraction: Other interior distraction8 (3.9%)
FTYROW: Making left turn8 (3.9%)↑60.0%prior 5
Driving too fast for conditions6 (2.9%)↓-14.3%prior 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

Crashes on dry roads and in clear weather both increased in count, from 76 to 117 and from 66 to 118, respectively. While daylight remained the most common lighting condition, the count of crashes occurring in darkness on unlit roadways rose from 20 in 2020 to 35 in 2021. The proportion of total crashes happening in daylight decreased from 59.6% in 2020 to 51.9% in 2021.

Weather

Clear118 (72.0%)
↑78.8%prior 66
Cloudy25 (15.2%)
↓-13.8%prior 29
Snow10 (6.1%)
↑66.7%prior 6
Rain6 (3.7%)
→0.0%prior 6
Blowing Snow3 (1.8%)
Freezing rain/drizzle1 (0.6%)
↓-80.0%prior 5
Fog, smoke, smog1 (0.6%)

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

Lighting

Daylight107 (65.6%)
↑23.0%prior 87
Dark - roadway not lighted35 (21.5%)
↑75.0%prior 20
Dark - roadway lighted12 (7.4%)
↑50.0%prior 8
Dusk5 (3.1%)
Dawn4 (2.5%)

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

Road Surface

Dry117 (71.3%)
↑53.9%prior 76
Wet19 (11.6%)
↑5.6%prior 18
Snow13 (7.9%)
Gravel9 (5.5%)
↑80.0%prior 5
Ice/frost5 (3.0%)
→0.0%prior 5
Mud, dirt1 (0.6%)

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

Vehicles & Demographics

Ford and Chevrolet were the two most common vehicle makes involved in crashes in both years, with their counts increasing from 2020 to 2021. The number of Fords involved rose from 34 to 50, and the combined count of Chevrolets ('CHEV' and 'CHEVROLET') increased from 40 to 66. Among persons involved in crashes, the 16-20 age group saw its numbers increase from 32 to 56, while the 65+ age group saw a decrease from 34 to 29.

Top Vehicle Makes (314 vehicles)

1
FORD50 (15.9%)
↑47.1%prior 34
2
CHEV35 (11.1%)
↑45.8%prior 24
3
CHEVROLET31 (9.9%)
↑93.8%prior 16
4
DODG15 (4.8%)
↑150.0%prior 6
5
JEEP10 (3.2%)
→0.0%prior 10
6
NR9 (2.9%)
7
DODGE9 (2.9%)
↓-10.0%prior 10
8
NISS9 (2.9%)
9
GMC9 (2.9%)
↑50.0%prior 6
10
TOYT8 (2.5%)

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

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

Sex Distribution (257 persons with recorded sex)

Male163 (63.4%)
↑32.5%prior 123
Female94 (36.6%)
↑28.8%prior 73

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: 206
  • Total persons involved: 389
  • Total vehicles involved: 314

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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