Yearly Traffic Safety Analysis

319 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Boone County, total traffic crashes decreased from 356 in 2022 to 319 in 2023, a decline of 10.4%. Despite the overall drop in collisions, the human cost of these incidents increased, as the number of fatalities rose from 2 to 7, and total injuries increased from 105 to 126.

319

▼ -10.4%was 356

Total Crash Events

7

▲ 250.0%was 2

Persons Killed

126

▲ 20.0%was 105

Persons Injured

6

▲ 200.0%was 2

Fatal Crash Events

Note: "Persons Killed" (7) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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

Overall traffic collisions in Boone County showed a downward trend year-over-year, with 37 fewer crashes in 2023 compared to 2022, representing a 10.4% decrease. However, the severity of these crashes worsened, as total injuries rose by 20% from 105 to 126, and fatalities increased from 2 to 7.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

7

Motorists Killed

Prior: 2↑250.0%

1

Pedestrians Injured

Prior: 2↓-50.0%

1

Cyclists Injured

Prior: 3↓-66.7%

124

Motorists Injured

Prior: 100↑24.0%

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 timing of crashes in Boone County shifted between the two periods. In 2023, the peak day for crashes was Monday with 56 incidents, a change from 2022 when Wednesday was the peak with 58 crashes. Similarly, the peak hour for collisions moved from the 5 p.m. evening commute in 2022 (34 crashes) to the 7 a.m. morning commute in 2023 (26 crashes).

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 increased in 2023 compared to the prior year. The number of fatal crashes tripled from 2 to 6, with the fatal crash rate rising from 0.56 to 1.88 per 100 crashes. The share of crashes resulting in minor injuries increased from 8.7% to 14.7% of all incidents, while the proportion of no-injury crashes fell from 76.7% in 2022 to 67.1% in 2023.

Severity is per crash event (most severe injury). 6 fatal crash events resulted in 7 persons killed.

Outcome by Severity (Crash Events)

Fatal6fatal crashes1.9%
↑200.0%prior 2
Serious Injury13serious injury crashes4.1%
↓-13.3%prior 15
Minor Injury47minor injury crashes14.7%
↑51.6%prior 31
Possible Injury39possible injury crashes12.2%
↑11.4%prior 35
No Injury214no injury crashes67.1%
↓-21.6%prior 273

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 animals remained the leading contributing factor in both years, with a nearly identical count of 93 crashes in 2023 versus 92 in 2022. 'Failure to yield from a stop sign' also remained a top factor, with its count increasing from 27 to 30 incidents. A notable decrease was observed in crashes attributed to 'Followed too close,' which fell from 24 incidents in 2022 to 13 in 2023.

Officer-Reported Primary Contributing Cause

Animal93 (29.2%)↑1.1%prior 92
FTYROW: From stop sign30 (9.4%)↑11.1%prior 27
Lost Control24 (7.5%)↑14.3%prior 21
Ran off road - left16 (5%)↓-30.4%prior 23
Ran Stop Sign14 (4.4%)↓-26.3%prior 19
Followed too close13 (4.1%)↓-45.8%prior 24
Driving too fast for conditions13 (4.1%)↓-38.1%prior 21
FTYROW: At uncontrolled intersection10 (3.1%)↑100.0%prior 5
Other (explain in narrative): Other10 (3.1%)↓-16.7%prior 12
Ran off road - straight9 (2.8%)↑12.5%prior 8

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

Road & Environmental Conditions

Crashes predominantly occurred on dry roads in both years, with the share of incidents on dry surfaces increasing from 55.6% in 2022 to 64.3% in 2023. There was a significant reduction in crashes under adverse road conditions; incidents on icy or frosty roads decreased from 34 to 14 year-over-year. Similarly, crashes during rainy conditions fell from 20 in 2022 to 9 in 2023.

Weather

Clear183 (69.3%)
↑3.4%prior 177
Cloudy55 (20.8%)
↑12.2%prior 49
Rain9 (3.4%)
↓-55.0%prior 20
Snow8 (3.0%)
↓-20.0%prior 10
Fog, smoke, smog6 (2.3%)
Freezing rain/drizzle2 (0.8%)
↓-81.8%prior 11
Other (explain in narrative)1 (0.4%)

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

Lighting

Daylight184 (69.7%)
↓-7.1%prior 198
Dark - roadway not lighted48 (18.2%)
↑2.1%prior 47
Dark - roadway lighted13 (4.9%)
↓-31.6%prior 19
Dawn8 (3.0%)
Dusk8 (3.0%)
↓-38.5%prior 13
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

Dry205 (77.7%)
↑3.5%prior 198
Wet22 (8.3%)
↓-29.0%prior 31
Ice/frost14 (5.3%)
↓-58.8%prior 34
Snow12 (4.5%)
→0.0%prior 12
Gravel7 (2.7%)
→0.0%prior 7
Slush2 (0.8%)
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

The makes of vehicles involved in crashes remained consistent, with Chevrolet and Ford vehicles being the most numerous in both 2022 and 2023. The total number of vehicles involved in crashes decreased from 544 to 472. Regarding the age of persons involved, the 26-34 age group saw an increase in representation from 105 to 123 individuals, becoming the largest cohort in 2023. Conversely, involvement for the 35-44 age group decreased from 133 people in 2022 to 100 in 2023.

Top Vehicle Makes (472 vehicles)

1
CHEV89 (18.9%)
↑4.7%prior 85
2
FORD88 (18.6%)
↓-7.4%prior 95
3
TOYO24 (5.1%)
↑14.3%prior 21
4
TOYT20 (4.2%)
↑53.8%prior 13
5
RAM20 (4.2%)
↑233.3%prior 6
6
NISS19 (4%)
→0.0%prior 19
7
DODG16 (3.4%)
↓-44.8%prior 29
8
BUIC15 (3.2%)
↑200.0%prior 5
9
CHEVROLET15 (3.2%)
↓-48.3%prior 29
10
JEEP14 (3%)
↓-46.2%prior 26

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

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

Sex Distribution (442 persons with recorded sex)

Male268 (60.6%)
↓-15.2%prior 316
Female174 (39.4%)
↓-14.3%prior 203

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: 319
  • Total persons involved: 685
  • Total vehicles involved: 472

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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