Yearly Traffic Safety Analysis

472 CRASHES IN
IOWA, IA
2022

All metrics benchmarked against2021

In 2022, Hamilton County recorded 472 total crashes, a 15.7% increase from the 408 crashes reported in 2021. While the number of fatalities remained unchanged at 3 for both years, the total number of injuries saw a slight decrease from 100 to 95. A notable trend was the increase in crashes attributed to driving under the influence (DUI), which rose from 11 in 2021 to 16 in 2022.

472

▲ 15.7%was 408

Total Crash Events

3

Persons Killed

95

▼ -5.0%was 100

Persons Injured

3

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 · 2022-01-01 to 2022-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash data for Hamilton County indicates a rising trend in the total number of collisions year-over-year. Total crashes increased by 15.7%, from 408 in 2021 to 472 in 2022. Despite this increase in total incidents, the number of resulting fatalities held steady at 3, and the total number of injuries decreased by 5% from 100 to 95.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 3→0.0%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 3↓-66.7%

93

Motorists Injured

Prior: 96↓-3.1%

1

Other Injured

Prior: 0→%

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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 2021 and 2022. The day with the most crashes moved from Thursday (69 incidents) in the prior year to Friday (86 incidents) in the current year. The peak hour for collisions also shifted earlier, from 5 p.m. in 2021 (29 crashes) to 3 p.m. in 2022 (34 crashes). Notably, December 2022 saw a significant spike in crashes, with 102 incidents, more than double the 45 crashes recorded in December 2021.

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the absolute number of fatal crashes remained constant at 3 in both 2021 and 2022, the fatal crash rate decreased from 0.74% to 0.64% due to an increase in total crashes. The proportion of crashes resulting in injury also declined, with crashes involving serious injuries showing a notable drop from 18 incidents in 2021 to 8 in 2022. Crashes with no reported injuries increased from 315 to 381, making up 80.7% of all incidents in 2022 compared to 77.2% in 2021.

Outcome by Severity (Crash Events)

Fatal3fatal crashes0.6%
→0.0%prior 3
Serious Injury8serious injury crashes1.7%
↓-55.6%prior 18
Minor Injury35minor injury crashes7.4%
↑16.7%prior 30
Possible Injury45possible injury crashes9.5%
↑7.1%prior 42
No Injury381no injury crashes80.7%
↑21.0%prior 315

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the leading contributing factor in both periods, with counts increasing from 105 in 2021 to 111 in 2022. The ranking of other top factors shifted, with 'Ran off road - straight' incidents increasing by 58% from 31 to 49, moving it from the fourth to the second most common factor. In contrast, 'Lost Control' incidents decreased from 41 to 38, dropping from second to fourth place. Incidents attributed to 'Driving too fast for conditions' also rose, from 33 in 2021 to 43 in 2022.

Officer-Reported Primary Contributing Cause

Animal111 (23.5%)↑5.7%prior 105
Ran off road - straight49 (10.4%)↑58.1%prior 31
Driving too fast for conditions43 (9.1%)↑30.3%prior 33
Lost Control38 (8.1%)↓-7.3%prior 41
Ran off road - left31 (6.6%)↑72.2%prior 18
Other (explain in narrative): Other28 (5.9%)↑115.4%prior 13
FTYROW: From stop sign21 (4.4%)↑162.5%prior 8
Followed too close13 (2.8%)↑30.0%prior 10
Ran Stop Sign12 (2.5%)→0.0%prior 12
Driver Distraction: Other interior distraction10 (2.1%)→0.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The proportion of crashes occurring in daylight increased, accounting for 52.1% of all incidents in 2022 (246 crashes) compared to 42.2% in 2021 (172 crashes). Regarding weather, crashes during snowy conditions saw a substantial rise, with 'Snow' cited in 44 crashes and 'Blowing Snow' in 42 crashes in 2022, up from 18 and 10 respectively in the prior year. This trend is reflected in road surface conditions, where crashes on snowy or icy surfaces increased from a combined 79 incidents in 2021 to 127 in 2022.

Weather

Clear188 (49.2%)
↑1.6%prior 185
Cloudy71 (18.6%)
↑22.4%prior 58
Snow44 (11.5%)
↑144.4%prior 18
Blowing Snow42 (11.0%)
↑320.0%prior 10
Freezing rain/drizzle14 (3.7%)
↓-50.0%prior 28
Rain10 (2.6%)
↓-16.7%prior 12
Other (explain in narrative)5 (1.3%)
Fog, smoke, smog4 (1.0%)
Severe Winds3 (0.8%)
Sleet, hail1 (0.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Weather condition at time of crash

Lighting

Daylight246 (64.1%)
↑43.0%prior 172
Dark - roadway not lighted82 (21.4%)
↑13.9%prior 72
Dark - roadway lighted29 (7.6%)
↓-37.0%prior 46
Dawn12 (3.1%)
→0.0%prior 12
Dusk12 (3.1%)
↓-20.0%prior 15
Dark - unknown roadway lighting3 (0.8%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Lighting condition field

Road Surface

Dry219 (57.5%)
↑7.9%prior 203
Ice/frost80 (21.0%)
↑29.0%prior 62
Snow47 (12.3%)
↑176.5%prior 17
Wet24 (6.3%)
↓-17.2%prior 29
Gravel6 (1.6%)
Slush5 (1.3%)

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes showed a consistent pattern, with Ford and Chevrolet models being the most frequent in both 2021 and 2022. In 2022, Ford vehicles were involved in 100 crashes, up from 82, while Chevrolet vehicles (listed as 'CHEV' and 'CHEVROLET') were involved in a combined 135 incidents, up from 130 in the prior year. The age distribution of individuals involved in crashes also remained stable; the 26-34 and 35-44 age groups were the largest cohorts in both years, each accounting for approximately 15.7% of all persons in 2022.

Top Vehicle Makes (671 vehicles)

1
FORD100 (14.9%)
↑22.0%prior 82
2
CHEV95 (14.2%)
↑17.3%prior 81
3
CHEVROLET40 (6%)
↓-18.4%prior 49
4
FREIGHTLINER27 (4%)
↑68.8%prior 16
5
GMC27 (4%)
↑50.0%prior 18
6
TOYT26 (3.9%)
↑18.2%prior 22
7
TOYOTA21 (3.1%)
↓-4.5%prior 22
8
HOND18 (2.7%)
↑100.0%prior 9
9
DODGE18 (2.7%)
↑125.0%prior 8
10
DODG18 (2.7%)
↓-28.0%prior 25

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · Vehicle unit records

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

Sex Distribution (622 persons with recorded sex)

Male411 (66.1%)
↑40.3%prior 293
Female211 (33.9%)
↑35.3%prior 156

Source: Iowa Crash Data · ArcGIS Open Data · 2022-01-01 to 2022-12-31 · 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: 2022-01-01 through 2022-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2022-01-01 through 2022-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 472
  • Total persons involved: 902
  • Total vehicles involved: 671

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: 2022." Published September 9, 2026. Reporting period: 2022-01-01 to 2022-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2022-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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