Yearly Traffic Safety Analysis

341 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Hamilton County, total traffic crashes decreased by 27.8% from 472 in 2022 to 341 in 2023. This overall reduction was accompanied by a decrease in fatalities from 3 to 2 and a slight drop in injuries from 95 to 89. The most notable year-over-year shift was a significant reduction in crashes occurring during adverse winter conditions, with collisions on icy or frosty roads declining from 80 to 39.

341

▼ -27.8%was 472

Total Crash Events

2

▼ -33.3%was 3

Persons Killed

89

▼ -6.3%was 95

Persons Injured

2

▼ -33.3%was 3

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic safety trends in Hamilton County showed a significant improvement from 2022 to 2023. The total number of crashes fell by 131, from 472 to 341, representing a 27.8% decrease. This downward trend was also reflected in crash outcomes, with total fatalities dropping from 3 to 2 and total injuries decreasing from 95 to 89.

Vulnerable Road User Casualties

2

Motorists Killed

Prior: 3↓-33.3%

89

Motorists Injured

Prior: 93↓-4.3%

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some changes between the two periods. The peak day for crashes shifted from Friday in 2022 (86 crashes) to Thursday in 2023 (58 crashes). However, the peak hour for collisions remained consistent at 3 p.m. in both years, though the volume of crashes during that hour decreased from 34 to 27.

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes saw mixed changes year-over-year. The number of fatal crashes decreased from 3 to 2, with the corresponding fatal crash rate declining slightly from 0.64 to 0.59 per 100 crashes. While total injuries decreased, the number of crashes resulting in a serious injury increased from 8 in 2022 to 11 in 2023, raising their share of total crashes from 1.7% to 3.2%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.6%
↓-33.3%prior 3
Serious Injury11serious injury crashes3.2%
↑37.5%prior 8
Minor Injury26minor injury crashes7.6%
↓-25.7%prior 35
Possible Injury32possible injury crashes9.4%
↓-28.9%prior 45
No Injury270no injury crashes79.2%
↓-29.1%prior 381

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions involving an animal remained the top contributing factor in both years, although the count decreased from 111 in 2022 to 87 in 2023. Crashes attributed to 'Driving too fast for conditions' fell from 43 to 31, and incidents where a driver 'Ran off road - straight' dropped from 49 to 28. 'Lost Control' moved from the fourth-ranked factor (38 crashes) to the second (32 crashes), despite a decrease in its total count.

Officer-Reported Primary Contributing Cause

Animal87 (25.5%)↓-21.6%prior 111
Lost Control32 (9.4%)↓-15.8%prior 38
Driving too fast for conditions31 (9.1%)↓-27.9%prior 43
Ran off road - straight28 (8.2%)↓-42.9%prior 49
Other (explain in narrative): Other26 (7.6%)↓-7.1%prior 28
FTYROW: From stop sign16 (4.7%)↓-23.8%prior 21
Ran off road - left13 (3.8%)↓-58.1%prior 31
Followed too close12 (3.5%)↓-7.7%prior 13
Driver Distraction: Other interior distraction10 (2.9%)→0.0%prior 10
Ran Stop Sign7 (2.1%)↓-41.7%prior 12

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

There was a substantial decrease in crashes related to adverse conditions from 2022 to 2023. Collisions on roads with ice or frost dropped from 80 to 39, and crashes occurring in snowy weather fell from 44 to 16. Crashes under clear weather conditions also decreased from 188 to 169, while those on dry road surfaces declined from 219 to 174.

Weather

Clear169 (63.1%)
↓-10.1%prior 188
Cloudy46 (17.2%)
↓-35.2%prior 71
Snow16 (6.0%)
↓-63.6%prior 44
Freezing rain/drizzle12 (4.5%)
↓-14.3%prior 14
Blowing Snow11 (4.1%)
↓-73.8%prior 42
Rain10 (3.7%)
→0.0%prior 10
Severe Winds2 (0.7%)
Other (explain in narrative)1 (0.4%)
↓-80.0%prior 5
Fog, smoke, smog1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Weather condition at time of crash

Lighting

Daylight170 (62.3%)
↓-30.9%prior 246
Dark - roadway not lighted64 (23.4%)
↓-22.0%prior 82
Dark - roadway lighted18 (6.6%)
↓-37.9%prior 29
Dawn13 (4.8%)
↑8.3%prior 12
Dusk5 (1.8%)
↓-58.3%prior 12
Dark - unknown roadway lighting3 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Lighting condition field

Road Surface

Dry174 (64.7%)
↓-20.5%prior 219
Ice/frost39 (14.5%)
↓-51.2%prior 80
Wet22 (8.2%)
↓-8.3%prior 24
Snow20 (7.4%)
↓-57.4%prior 47
Gravel9 (3.3%)
↑50.0%prior 6
Slush3 (1.1%)
↓-40.0%prior 5
Mud, dirt1 (0.4%)
Other (explain in narrative)1 (0.4%)

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Road surface condition field

Vehicles & Demographics

Ford and Chevrolet remained the top two vehicle makes involved in collisions, with both seeing a reduction in crash counts. The number of Fords in crashes fell from 100 to 74, while Chevrolets (combining 'CHEV' and 'CHEVROLET' records) decreased from 135 to 105. Among persons involved in crashes, there was a notable drop in the 21-25 age group, from 116 individuals in 2022 to 67 in 2023.

Top Vehicle Makes (486 vehicles)

1
CHEV76 (15.6%)
↓-20.0%prior 95
2
FORD74 (15.2%)
↓-26.0%prior 100
3
CHEVROLET29 (6%)
↓-27.5%prior 40
4
GMC24 (4.9%)
↓-11.1%prior 27
5
DODG20 (4.1%)
↑11.1%prior 18
6
FREIGHTLINER19 (3.9%)
↓-29.6%prior 27
7
TOYT16 (3.3%)
↓-38.5%prior 26
8
JEEP16 (3.3%)
↓-5.9%prior 17
9
DODGE14 (2.9%)
↓-22.2%prior 18
10
TOYOTA13 (2.7%)
↓-38.1%prior 21

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · Vehicle unit records

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

Sex Distribution (428 persons with recorded sex)

Male285 (66.6%)
↓-30.7%prior 411
Female143 (33.4%)
↓-32.2%prior 211

Source: Iowa Crash Data · ArcGIS Open Data · 2023-01-01 to 2023-12-31 · 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: 2023-01-01 through 2023-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2023-01-01 through 2023-12-31 (365 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 341
  • Total persons involved: 696
  • Total vehicles involved: 486

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: 2023." Published September 9, 2026. Reporting period: 2023-01-01 to 2023-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2023-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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