Yearly Traffic Safety Analysis

349 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Iowa County recorded 349 total traffic crashes, a 12.1% decrease from the 397 crashes reported in 2022. Despite the overall reduction in collisions, the number of fatalities resulting from these incidents more than doubled, increasing from two in the prior year to five in the current year.

349

▼ -12.1%was 397

Total Crash Events

5

▲ 150.0%was 2

Persons Killed

94

▲ 2.2%was 92

Persons Injured

5

▲ 150.0%was 2

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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 crashes in Iowa County showed a downward trend year-over-year, decreasing from 397 in 2022 to 349 in 2023. While the total number of injuries remained stable with 94 in 2023 compared to 92 in 2022, traffic fatalities increased from two to five.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 2↑150.0%

2

Cyclists Injured

Prior: 1↑100.0%

92

Motorists Injured

Prior: 91↑1.1%

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 shifted between the two periods. In 2023, the peak day for crashes was Thursday with 72 incidents, a change from Friday (77 incidents) in 2022. The peak hour also shifted earlier, from the 8 a.m. hour in 2022 (26 crashes) to the 6 a.m. hour in 2023 (33 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

While total crashes declined, the severity of crashes worsened in 2023. The number of fatal crashes increased from two to five, raising the fatal crash rate from 0.5% to 1.4% of all incidents. The count of serious injury crashes decreased slightly from seven to five, but crashes involving possible injuries rose from 34 to 42.

Outcome by Severity (Crash Events)

Fatal5fatal crashes1.4%
↑150.0%prior 2
Serious Injury5serious injury crashes1.4%
↓-28.6%prior 7
Minor Injury25minor injury crashes7.2%
↓-21.9%prior 32
Possible Injury42possible injury crashes12%
↑23.5%prior 34
No Injury272no injury crashes77.9%
↓-15.5%prior 322

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 with animals remained the leading contributing factor in both years, with the count increasing from 115 in 2022 to 125 in 2023. 'Ran off road - straight' was the second most common factor, though its frequency decreased from 43 incidents to 33. 'Driving too fast for conditions' held its rank as the third leading cause, with a nearly unchanged count of 31 crashes in 2023 compared to 32 in the prior year.

Officer-Reported Primary Contributing Cause

Animal125 (35.8%)↑8.7%prior 115
Ran off road - straight33 (9.5%)↓-23.3%prior 43
Driving too fast for conditions31 (8.9%)↓-3.1%prior 32
Lost Control29 (8.3%)↑3.6%prior 28
Followed too close24 (6.9%)↑33.3%prior 18
Ran off road - left21 (6%)↓-8.7%prior 23
Operating vehicle in an reckless, erratic, careless, negligent manner10 (2.9%)↓-16.7%prior 12
FTYROW: From stop sign9 (2.6%)↓-10.0%prior 10
Driver Distraction: Other interior distraction6 (1.7%)↓-45.5%prior 11
FTYROW: From parked position5 (1.4%)

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

Road & Environmental Conditions

Year-over-year analysis of crash conditions reveals shifts in weather-related incidents. Crashes occurring in snowy conditions nearly doubled from 15 in 2022 to 29 in 2023. Conversely, collisions on roads with ice or frost were less frequent, decreasing from 38 to 17. The distribution of crashes under different lighting conditions remained largely proportional to the overall decrease in incidents.

Weather

Clear132 (52.4%)
↓-18.5%prior 162
Cloudy63 (25.0%)
↓-4.5%prior 66
Snow29 (11.5%)
↑93.3%prior 15
Rain14 (5.6%)
↓-12.5%prior 16
Fog, smoke, smog7 (2.8%)
Blowing Snow6 (2.4%)
↓-75.0%prior 24
Freezing rain/drizzle1 (0.4%)
↓-83.3%prior 6

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

Lighting

Daylight144 (56.7%)
↓-16.3%prior 172
Dark - roadway not lighted79 (31.1%)
↓-11.2%prior 89
Dark - roadway lighted17 (6.7%)
↓-15.0%prior 20
Dawn7 (2.8%)
↑40.0%prior 5
Dusk7 (2.8%)
↓-22.2%prior 9

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

Road Surface

Dry167 (66.3%)
↓-12.6%prior 191
Wet25 (9.9%)
↑4.2%prior 24
Snow23 (9.1%)
↓-8.0%prior 25
Ice/frost17 (6.7%)
↓-55.3%prior 38
Gravel13 (5.2%)
↓-23.5%prior 17
Slush7 (2.8%)

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

Vehicles & Demographics

The top two vehicle makes involved in crashes, Ford and Chevrolet, remained consistent, though their counts decreased from 102 to 77 and 70 to 59, respectively. A significant demographic shift occurred in the age of persons involved in crashes; the 16-20 age group saw its involvement nearly double from 45 individuals in 2022 to 88 in 2023. In contrast, the number of persons aged 35-44 involved in crashes fell from 145 to 95.

Top Vehicle Makes (463 vehicles)

1
FORD77 (16.6%)
↓-24.5%prior 102
2
CHEV59 (12.7%)
↓-15.7%prior 70
3
DODG24 (5.2%)
↓-4.0%prior 25
4
TOYO21 (4.5%)
↓-16.0%prior 25
5
GMC20 (4.3%)
↑5.3%prior 19
6
FREIGHTLINER19 (4.1%)
↓-26.9%prior 26
7
CHEVROLET17 (3.7%)
↓-26.1%prior 23
8
JEEP16 (3.5%)
→0.0%prior 16
9
HOND16 (3.5%)
↓-20.0%prior 20
10
CHRY15 (3.2%)
↑87.5%prior 8

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

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

Sex Distribution (440 persons with recorded sex)

Male286 (65.0%)
↓-15.6%prior 339
Female154 (35.0%)
↓-10.5%prior 172

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: 349
  • Total persons involved: 678
  • Total vehicles involved: 463

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

ThatCarHitMe.com · An Injuria.ai Company