Yearly Traffic Safety Analysis

408 CRASHES IN
IOWA, IA
2021

All metrics benchmarked against2020

In Hamilton County, traffic crashes increased by 33.8% from 305 in 2020 to 408 in 2021. This rise was accompanied by an increase in total fatalities from one to three. The most notable shift in contributing factors was a 59% increase in the count of crashes involving an animal, which rose from 66 in 2020 to 105 in 2021.

408

▲ 33.8%was 305

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

100

▲ 6.4%was 94

Persons Injured

3

▲ 200.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 data for Hamilton County indicates a rising trend in collisions year-over-year. Total crashes increased from 305 in 2020 to 408 in 2021, a 33.8% rise. Concurrently, the number of persons injured increased from 94 to 100, and fatalities rose from one to three.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

3

Pedestrians Injured

Prior: 0→%

1

Cyclists Injured

Prior: 1→0.0%

96

Motorists Injured

Prior: 93↑3.2%

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 showed some shifts between the two periods. While the peak hour for collisions remained the 5 p.m. hour in both years, the number of crashes during this hour increased from 22 to 29. The peak day for crashes shifted from Friday in 2020 (61 crashes) to Thursday in 2021 (69 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 worsened year-over-year, with the number of fatal crashes increasing from one in 2020 to three in 2021, and the fatal crash rate more than doubling from 0.3% to 0.7%. While the number of serious injury crashes increased from 12 to 18, the overall proportion of crashes involving any level of injury (fatal, serious, minor, or possible) decreased slightly from 26.6% in 2020 to 22.8% in 2021, as crashes with no injuries increased from 224 to 315.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.7%
↑200.0%prior 1
Serious Injury18serious injury crashes4.4%
↑50.0%prior 12
Minor Injury30minor injury crashes7.4%
↑20.0%prior 25
Possible Injury42possible injury crashes10.3%
↓-2.3%prior 43
No Injury315no injury crashes77.2%
↑40.6%prior 224

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 with animals remained the top contributing factor in both periods, with the count increasing by 59% from 66 crashes in 2020 to 105 in 2021. 'Lost Control' became the second-leading factor in 2021 with 41 incidents, a 46% increase in count from 28 incidents in the prior year. Conversely, crashes attributed to 'Failure to Yield Right of Way from a stop sign' saw a significant decrease, falling from 20 incidents in 2020 to 8 in 2021.

Officer-Reported Primary Contributing Cause

Animal105 (25.7%)↑59.1%prior 66
Lost Control41 (10%)↑46.4%prior 28
Driving too fast for conditions33 (8.1%)↑13.8%prior 29
Ran off road - straight31 (7.6%)↓-13.9%prior 36
Ran off road - left18 (4.4%)↑200.0%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner14 (3.4%)↑133.3%prior 6
Other (explain in narrative): Other13 (3.2%)↓-31.6%prior 19
Ran Stop Sign12 (2.9%)↑9.1%prior 11
Failed to keep in proper lane11 (2.7%)
Other (explain in narrative): No improper action11 (2.7%)→0.0%prior 11

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

Road & Environmental Conditions

Comparatively, there was a significant increase in crashes occurring on adverse road surfaces. Collisions on roads with ice or frost more than tripled, rising from 17 incidents in 2020 to 62 in 2021. The proportion of crashes happening in darkness (either lighted or unlighted roadways) also grew, accounting for 24.6% of crashes in 2020 and increasing to 28.9% in 2021. Crashes in clear weather increased in count from 147 to 185, remaining the most common condition.

Weather

Clear185 (58.4%)
↑25.9%prior 147
Cloudy58 (18.3%)
↑13.7%prior 51
Freezing rain/drizzle28 (8.8%)
Snow18 (5.7%)
↓-25.0%prior 24
Rain12 (3.8%)
↓-7.7%prior 13
Blowing Snow10 (3.2%)
↑100.0%prior 5
Fog, smoke, smog3 (0.9%)
Other (explain in narrative)2 (0.6%)
Severe Winds1 (0.3%)

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

Lighting

Daylight172 (54.1%)
↑12.4%prior 153
Dark - roadway not lighted72 (22.6%)
↑44.0%prior 50
Dark - roadway lighted46 (14.5%)
↑84.0%prior 25
Dusk15 (4.7%)
Dawn12 (3.8%)
↓-29.4%prior 17
Dark - unknown roadway lighting1 (0.3%)

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

Road Surface

Dry203 (64.2%)
↑23.8%prior 164
Ice/frost62 (19.6%)
↑264.7%prior 17
Wet29 (9.2%)
↑11.5%prior 26
Snow17 (5.4%)
↓-15.0%prior 20
Gravel4 (1.3%)
↓-63.6%prior 11
Mud, dirt1 (0.3%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Chevrolet and Ford models being the most frequent in both 2020 and 2021. The age demographics of persons involved in crashes also showed stability, with the 26-34 age group being the largest in both years (110 people in 2020 and 119 in 2021). However, the number of individuals in the 55-64 age group involved in crashes saw a notable increase from 45 in 2020 to 87 in 2021.

Top Vehicle Makes (585 vehicles)

1
FORD82 (14%)
↑9.3%prior 75
2
CHEV81 (13.8%)
↑5.2%prior 77
3
CHEVROLET49 (8.4%)
↑69.0%prior 29
4
DODG25 (4.3%)
↑127.3%prior 11
5
TOYT22 (3.8%)
↑29.4%prior 17
6
TOYOTA22 (3.8%)
↑175.0%prior 8
7
GMC18 (3.1%)
↑5.9%prior 17
8
NR18 (3.1%)
↑100.0%prior 9
9
FREIGHTLINER16 (2.7%)
↑77.8%prior 9
10
JEEP13 (2.2%)
↑8.3%prior 12

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

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

Sex Distribution (449 persons with recorded sex)

Male293 (65.3%)
↑11.4%prior 263
Female156 (34.7%)
↑22.8%prior 127

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: 408
  • Total persons involved: 768
  • Total vehicles involved: 585

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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