Yearly Traffic Safety Analysis

764 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Lee County recorded 764 total crashes, a 25% increase from the 611 crashes documented in 2020. While overall collisions and injuries rose, the most notable year-over-year shift was a significant decrease in fatalities, which fell from 9 in the prior year to 4 in the current period. Correspondingly, total injuries increased by 33%, from 133 to 177.

764

▲ 25.0%was 611

Total Crash Events

4

▼ -55.6%was 9

Persons Killed

177

▲ 33.1%was 133

Persons Injured

4

▼ -50.0%was 8

Fatal Crash Events

Note: "Persons Killed" (4) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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

The overall trend shows a significant increase in traffic crashes in Lee County year-over-year. Total crashes rose by 25% from 611 in 2020 to 764 in 2021. This was accompanied by a 33% increase in total injuries from 133 to 177, while total fatalities decreased from 9 to 4.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

4

Motorists Killed

Prior: 9↓-55.6%

4

Pedestrians Injured

Prior: 3↑33.3%

8

Cyclists Injured

Prior: 2↑300.0%

165

Motorists Injured

Prior: 128↑28.9%

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 Friday with 134 incidents, a change from Wednesday, which was the peak day with 101 incidents in the prior year. The peak hour also shifted from 7 p.m. (39 crashes) in 2020 to the 5 p.m. hour (51 crashes) 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 total crashes increased, the proportion of fatal crashes decreased from 1.3% of all incidents in 2020 to 0.5% in 2021, with the count of fatal crashes dropping from 8 to 4. The share of crashes resulting in a serious injury increased slightly from 2.6% to 3.1% of the total. Crashes resulting in no injury remained the largest category, accounting for 80.5% of incidents in 2021 compared to 81.2% in 2020.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.5%
↓-50.0%prior 8
Serious Injury24serious injury crashes3.1%
↑50.0%prior 16
Minor Injury46minor injury crashes6%
↑15.0%prior 40
Possible Injury75possible injury crashes9.8%
↑47.1%prior 51
No Injury615no injury crashes80.5%
↑24.0%prior 496

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 increasing from 244 in 2020 to 269 in 2021. A notable change was observed in crashes attributed to 'Failure to Yield Right of Way from a stop sign,' where the count more than doubled from 23 to 56, moving this factor from fifth to third in the rankings. In contrast, incidents where a driver 'Lost Control' decreased from 41 to 33, dropping from the second-ranked factor in 2020 to the fifth in 2021.

Officer-Reported Primary Contributing Cause

Animal269 (35.2%)↑10.2%prior 244
Other (explain in narrative): Other70 (9.2%)↑84.2%prior 38
FTYROW: From stop sign56 (7.3%)↑143.5%prior 23
Followed too close35 (4.6%)↑40.0%prior 25
Lost Control33 (4.3%)↓-19.5%prior 41
Ran off road - left31 (4.1%)↑47.6%prior 21
Driver Distraction: Other interior distraction30 (3.9%)↑172.7%prior 11
Driving too fast for conditions26 (3.4%)↑52.9%prior 17
Ran off road - straight16 (2.1%)↓-15.8%prior 19
FTYROW: Making left turn15 (2%)↑66.7%prior 9

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 in daylight increased from 243 to 365, and collisions on dry roads rose from 291 to 397, in line with the overall increase in total crashes. The number of incidents occurring in the dark on unlighted roadways increased from 68 to 84 year-over-year. Crashes reported during rain increased from 17 to 22, and those on wet road surfaces rose from 42 to 52.

Weather

Clear354 (68.2%)
↑33.1%prior 266
Cloudy100 (19.3%)
↑63.9%prior 61
Rain22 (4.2%)
↑29.4%prior 17
Snow21 (4.0%)
↑10.5%prior 19
Blowing Snow7 (1.3%)
Fog, smoke, smog6 (1.2%)
Freezing rain/drizzle3 (0.6%)
↓-62.5%prior 8
Other (explain in narrative)2 (0.4%)
Sleet, hail2 (0.4%)
Severe Winds1 (0.2%)

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

Lighting

Daylight365 (70.1%)
↑50.2%prior 243
Dark - roadway not lighted84 (16.1%)
↑23.5%prior 68
Dark - roadway lighted54 (10.4%)
↑45.9%prior 37
Dawn8 (1.5%)
↓-20.0%prior 10
Dusk8 (1.5%)
↓-42.9%prior 14
Dark - unknown roadway lighting2 (0.4%)
↓-71.4%prior 7

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

Road Surface

Dry397 (76.2%)
↑36.4%prior 291
Wet52 (10.0%)
↑23.8%prior 42
Snow31 (6.0%)
↑55.0%prior 20
Ice/frost21 (4.0%)
↑133.3%prior 9
Gravel13 (2.5%)
↑160.0%prior 5
Slush5 (1.0%)
↓-28.6%prior 7
Mud, dirt1 (0.2%)
Other (explain in narrative)1 (0.2%)

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

Vehicles & Demographics

The number of persons involved in crashes increased across all reported age groups, with the 16-20 age group experiencing a 40% increase in involvement from 107 individuals in 2020 to 150 in 2021. Regarding vehicle makes, Ford and Chevrolet were the most common in crashes for both periods. After combining naming variations, Chevrolet-branded vehicles were involved in 235 crashes in 2021, up from 164 in 2020, making it the most frequent make in the current period.

Top Vehicle Makes (1,155 vehicles)

1
FORD196 (17%)
↑19.5%prior 164
2
CHEVROLET121 (10.5%)
↑70.4%prior 71
3
CHEV114 (9.9%)
↑22.6%prior 93
4
GMC59 (5.1%)
↑59.5%prior 37
5
DODG51 (4.4%)
↑30.8%prior 39
6
DODGE50 (4.3%)
↑42.9%prior 35
7
KIA42 (3.6%)
↑35.5%prior 31
8
TOYT34 (2.9%)
↑30.8%prior 26
9
TOYOTA34 (2.9%)
↑88.9%prior 18
10
HOND32 (2.8%)
↑100.0%prior 16

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

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

Sex Distribution (910 persons with recorded sex)

Male505 (55.5%)
↑13.5%prior 445
Female405 (44.5%)
↑31.5%prior 308

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: 764
  • Total persons involved: 1,555
  • Total vehicles involved: 1,155

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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