Yearly Traffic Safety Analysis

387 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In 2021, Iowa County recorded 387 total crashes, a slight increase of 2.1% from the 379 crashes documented in 2020. Despite the minor rise in total incidents, the number of fatalities saw a significant year-over-year decrease. There were 2 fatalities in 2021, a sharp drop from the 6 fatalities reported in the prior year.

387

▲ 2.1%was 379

Total Crash Events

2

▼ -66.7%was 6

Persons Killed

103

Persons Injured

2

▼ -66.7%was 6

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

Overall crash volume in Iowa County remained relatively stable, increasing by 2.1% from 379 incidents in 2020 to 387 in 2021. While total injuries were unchanged at 103 for both years, there was a notable positive trend in fatal outcomes. Fatalities decreased by 66.7%, from 6 in 2020 to 2 in 2021.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 6↓-66.7%

103

Motorists Injured

Prior: 102↑1.0%

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 in Iowa County showed consistency year-over-year. Friday remained the peak day for crashes in both 2021 (72 crashes) and 2020 (67 crashes). Similarly, the 3 p.m. hour was the most frequent time for incidents in both periods, with 31 crashes in 2021 and 32 in 2020. The overall daily and hourly distributions of crashes did not exhibit significant shifts between the two years.

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 outcomes improved in 2021 compared to 2020. The number of fatal crashes dropped from 6 to 2, and serious injury crashes decreased from 14 to 6. Consequently, the share of fatal crashes fell from 1.6% to 0.5% of all incidents, and the share of serious injury crashes dropped from 3.7% to 1.6%. Conversely, the proportion of crashes resulting in minor injuries increased from 6.9% in 2020 to 9.0% in 2021.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.5%
↓-66.7%prior 6
Serious Injury6serious injury crashes1.6%
↓-57.1%prior 14
Minor Injury35minor injury crashes9%
↑34.6%prior 26
Possible Injury38possible injury crashes9.8%
↑5.6%prior 36
No Injury306no injury crashes79.1%
↑3.0%prior 297

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 leading contributing factor in both periods, though the count of such incidents decreased by 19.3% from 140 in 2020 to 113 in 2021. 'Lost Control' was the second most common factor in 2021 with 36 incidents, a slight increase from 34 in the prior year. Notably, crashes attributed to 'Driving too fast for conditions' saw a 33.3% increase in count, rising from 21 to 28 incidents, while 'Followed too close' incidents increased from 16 to 23.

Officer-Reported Primary Contributing Cause

Animal113 (29.2%)↓-19.3%prior 140
Lost Control36 (9.3%)↑5.9%prior 34
Driving too fast for conditions28 (7.2%)↑33.3%prior 21
Ran off road - straight28 (7.2%)↓-22.2%prior 36
Followed too close23 (5.9%)↑43.8%prior 16
Ran off road - left18 (4.7%)↑80.0%prior 10
FTYROW: From stop sign17 (4.4%)↑112.5%prior 8
Other (explain in narrative): Other17 (4.4%)↑88.9%prior 9
Operating vehicle in an reckless, erratic, careless, negligent manner9 (2.3%)
Driver Distraction: Other interior distraction8 (2.1%)↑33.3%prior 6

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 occurring during daylight hours increased as a proportion of the total, accounting for 47.8% of incidents in 2021 compared to 38.3% in 2020. Similarly, crashes on dry roads rose from 42.5% to 49.9% of the total. While incidents on icy or frosty roads decreased from 30 to 17, crashes occurring on snowy surfaces increased from 14 incidents in 2020 to 35 in 2021.

Weather

Clear158 (54.7%)
↑19.7%prior 132
Cloudy76 (26.3%)
↑26.7%prior 60
Snow26 (9.0%)
↑23.8%prior 21
Rain14 (4.8%)
↑7.7%prior 13
Blowing Snow5 (1.7%)
Freezing rain/drizzle4 (1.4%)
↓-76.5%prior 17
Severe Winds3 (1.0%)
Fog, smoke, smog3 (1.0%)

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

Lighting

Daylight185 (64.2%)
↑27.6%prior 145
Dark - roadway not lighted78 (27.1%)
↓-4.9%prior 82
Dark - roadway lighted10 (3.5%)
↑100.0%prior 5
Dawn8 (2.8%)
↑33.3%prior 6
Dusk7 (2.4%)
↓-22.2%prior 9

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

Road Surface

Dry193 (66.8%)
↑19.9%prior 161
Snow35 (12.1%)
↑150.0%prior 14
Wet27 (9.3%)
→0.0%prior 27
Ice/frost17 (5.9%)
↓-43.3%prior 30
Gravel10 (3.5%)
↓-28.6%prior 14
Slush7 (2.4%)

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

Vehicles & Demographics

The ranking of top vehicle makes involved in crashes shifted between periods; Ford became the most common make in 2021 with 114 vehicles, up from 81 in 2020, overtaking Chevrolet (109 combined 'CHEV' and 'CHEVROLET' vehicles in 2021 vs. 100 in 2020). Analysis of persons involved shows the 26-34 age group remained the largest cohort in both years, though their count decreased from 157 to 125. Conversely, the number of individuals in the 55-64 age group involved in crashes increased from 93 to 117.

Top Vehicle Makes (562 vehicles)

1
FORD114 (20.3%)
↑40.7%prior 81
2
CHEV67 (11.9%)
↓-6.9%prior 72
3
CHEVROLET42 (7.5%)
↑50.0%prior 28
4
DODG22 (3.9%)
→0.0%prior 22
5
GMC21 (3.7%)
↑50.0%prior 14
6
FREIGHTLINER20 (3.6%)
↑33.3%prior 15
7
TOYO16 (2.8%)
↓-42.9%prior 28
8
HOND15 (2.7%)
↑50.0%prior 10
9
TOYT14 (2.5%)
10
TOYOTA14 (2.5%)
↑75.0%prior 8

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

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

Sex Distribution (463 persons with recorded sex)

Male288 (62.2%)
↓-3.7%prior 299
Female175 (37.8%)
↑1.7%prior 172

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: 387
  • Total persons involved: 731
  • Total vehicles involved: 562

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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