Yearly Traffic Safety Analysis

288 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Cass County recorded 288 total crashes, a minimal increase from the 287 crashes reported in 2022. While the overall crash volume remained stable, the most notable year-over-year shift was a 150% increase in traffic fatalities, which rose from 2 to 5. The total number of injuries remained nearly unchanged, with 95 in 2023 compared to 96 in the prior year.

288

▲ 0.3%was 287

Total Crash Events

5

▲ 150.0%was 2

Persons Killed

95

▼ -1.0%was 96

Persons Injured

3

▲ 50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (5) 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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crash volume in Cass County was stable year-over-year, increasing by just one incident from 287 in 2022 to 288 in 2023. The number of injuries also held steady, decreasing by one from 96 to 95. However, the severity of crashes worsened, as fatalities more than doubled, increasing from 2 to 5.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 2↑150.0%

1

Pedestrians Injured

Prior: 1→0.0%

2

Cyclists Injured

Prior: 2→0.0%

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 peak hour for crashes was consistent at 3 p.m. in both 2023 and 2022, with 21 and 26 crashes respectively. The peak day of the week showed a notable change; while Friday was the clear peak in 2022 with 57 crashes, 2023 saw a four-way tie between Sunday, Thursday, Friday, and Saturday, each with 46 crashes. This suggests a more even distribution of crash occurrences across the week in the current period.

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, with the number of fatal crashes rising to 3 from 2 in the prior year, and the fatal crash rate increasing from 0.7% to 1.0%. In contrast, the count of serious injury crashes decreased from 15 in 2022 to 11 in 2023. The proportion of crashes resulting in no injuries increased slightly, from 71.8% of all crashes in 2022 to 72.9% in 2023.

Severity is per crash event (most severe injury). 3 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1%
↑50.0%prior 2
Serious Injury11serious injury crashes3.8%
↓-26.7%prior 15
Minor Injury37minor injury crashes12.8%
↑2.8%prior 36
Possible Injury27possible injury crashes9.4%
↓-3.6%prior 28
No Injury210no injury crashes72.9%
↑1.9%prior 206

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 periods, with the count increasing by 27.7% from 47 incidents in 2022 to 60 in 2023. 'Lost Control' became the second most-cited factor in 2023 with 42 crashes, up from 36 in the prior year. Conversely, crashes attributed to 'Ran off road - straight' decreased by 41.7%, falling from 36 incidents in 2022 to 21 in 2023.

Officer-Reported Primary Contributing Cause

Animal60 (20.8%)↑27.7%prior 47
Lost Control42 (14.6%)↑16.7%prior 36
Ran off road - straight21 (7.3%)↓-41.7%prior 36
Other (explain in narrative): Other19 (6.6%)↑11.8%prior 17
Ran off road - left15 (5.2%)↓-11.8%prior 17
FTYROW: From stop sign15 (5.2%)↓-16.7%prior 18
Followed too close13 (4.5%)↑30.0%prior 10
Driving too fast for conditions13 (4.5%)↓-23.5%prior 17
Driver Distraction: Other interior distraction9 (3.1%)↑28.6%prior 7
Driver Distraction: Inattentive/lost in thought9 (3.1%)

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

Road & Environmental Conditions

Crash conditions were largely consistent year-over-year, with the majority of incidents in both periods occurring in clear weather, during daylight hours, and on dry roads. A significant change was observed in road surface conditions, where crashes on roads with ice or frost dropped by 44%, from 25 incidents in 2022 to 14 in 2023. Other adverse condition proportions remained relatively stable.

Weather

Clear169 (70.7%)
↓-1.7%prior 172
Cloudy30 (12.6%)
↓-18.9%prior 37
Snow20 (8.4%)
↓-13.0%prior 23
Rain7 (2.9%)
↓-36.4%prior 11
Freezing rain/drizzle6 (2.5%)
Fog, smoke, smog2 (0.8%)
Severe Winds2 (0.8%)
Sleet, hail2 (0.8%)
Blowing Snow1 (0.4%)
↓-88.9%prior 9

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

Lighting

Daylight155 (64.0%)
↓-1.3%prior 157
Dark - roadway not lighted59 (24.4%)
↑1.7%prior 58
Dark - roadway lighted13 (5.4%)
↓-45.8%prior 24
Dawn7 (2.9%)
↓-22.2%prior 9
Dusk7 (2.9%)
→0.0%prior 7
Dark - unknown roadway lighting1 (0.4%)

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

Road Surface

Dry185 (77.1%)
↑1.6%prior 182
Snow16 (6.7%)
↓-11.1%prior 18
Ice/frost14 (5.8%)
↓-44.0%prior 25
Wet13 (5.4%)
↓-38.1%prior 21
Gravel7 (2.9%)
↓-22.2%prior 9
Slush3 (1.3%)
Mud, dirt2 (0.8%)

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

Vehicles & Demographics

Ford and Chevrolet vehicles were the most frequently involved makes in crashes across both years. A significant demographic shift occurred in the 16-20 age group, where the number of persons involved in crashes increased by 78.8% from 52 individuals in 2022 to 93 in 2023. The distribution of other age groups involved in crashes remained comparatively stable between the two periods.

Top Vehicle Makes (396 vehicles)

1
FORD56 (14.1%)
↓-18.8%prior 69
2
CHEV55 (13.9%)
↓-23.6%prior 72
3
CHEVROLET24 (6.1%)
↓-11.1%prior 27
4
DODG20 (5.1%)
→0.0%prior 20
5
FREIGHTLINER19 (4.8%)
↓-29.6%prior 27
6
BUIC12 (3%)
↓-7.7%prior 13
7
TOYO11 (2.8%)
↑37.5%prior 8
8
GMC11 (2.8%)
↑22.2%prior 9
9
NISS10 (2.5%)
→0.0%prior 10
10
TOYOTA10 (2.5%)
↑11.1%prior 9

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

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

Sex Distribution (366 persons with recorded sex)

Male255 (69.7%)
↓-4.5%prior 267
Female111 (30.3%)
↓-12.6%prior 127

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: 288
  • Total persons involved: 580
  • Total vehicles involved: 396

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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