Yearly Traffic Safety Analysis

197 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Cass County, total traffic crashes decreased from 288 in 2023 to 197 in 2024, a reduction of 31.6%. This downward trend was also reflected in crash outcomes, with total fatalities falling from 5 to 1 and total injuries decreasing from 95 to 57. The most significant contributing factor in both periods was collisions with animals, though the count of such incidents also decreased year-over-year.

197

▼ -31.6%was 288

Total Crash Events

1

▼ -80.0%was 5

Persons Killed

57

▼ -40.0%was 95

Persons Injured

1

▼ -66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (1) counts individual fatalities across all crash events. "Fatal" in the severity table below (1) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic safety trends in Cass County showed significant improvement year-over-year, with total crashes falling by 31.6% from 288 to 197. This positive trend extended to severe outcomes, as total fatalities decreased from 5 in 2023 to 1 in 2024. The number of people injured in crashes also declined by 40%, from 95 to 57.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 5↓-80.0%

1

Pedestrians Injured

Prior: 1→0.0%

1

Cyclists Injured

Prior: 2↓-50.0%

55

Motorists Injured

Prior: 92↓-40.2%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The timing of crashes in Cass County shifted between the two periods. In 2024, Monday was the distinct peak day for crashes with 35 incidents, a change from 2023 which saw a four-way tie for the peak day (Sunday, Thursday, Friday, and Saturday) with 46 crashes each. The peak hour for collisions remained in the afternoon, shifting from 3 p.m. in 2023 (21 crashes) to a tie between 1 p.m. and 3 p.m. in 2024 (15 crashes each).

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

The severity of crashes in Cass County decreased year-over-year. The number of fatal crashes fell from 3 in 2023 to 1 in 2024, and the fatal crash rate was halved from 1.0% to 0.5% of all crashes. The proportion of crashes resulting in any form of injury (serious, minor, or possible) saw a slight decrease from 26.0% in 2023 to 24.9% in 2024. Correspondingly, the share of crashes with no reported injuries increased from 72.9% to 74.6%.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.5%
↓-66.7%prior 3
Serious Injury6serious injury crashes3%
↓-45.5%prior 11
Minor Injury21minor injury crashes10.7%
↓-43.2%prior 37
Possible Injury22possible injury crashes11.2%
↓-18.5%prior 27
No Injury147no injury crashes74.6%
↓-30.0%prior 210

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

Collisions with an animal remained the top contributing factor in both periods, though the count of these incidents fell by 41.7% from 60 in 2023 to 35 in 2024. Crashes attributed to 'Lost Control' saw a notable decrease in count, dropping from 42 incidents in 2023 to 16 in 2024. While most top factors saw a reduction in count, 'Ran off road - left' incidents increased from 15 to 19, moving this factor from the fifth to the second most common cause in 2024.

Officer-Reported Primary Contributing Cause

Animal35 (17.8%)↓-41.7%prior 60
Ran off road - left19 (9.6%)↑26.7%prior 15
Ran off road - straight18 (9.1%)↓-14.3%prior 21
Lost Control16 (8.1%)↓-61.9%prior 42
FTYROW: From stop sign14 (7.1%)↓-6.7%prior 15
Driving too fast for conditions13 (6.6%)→0.0%prior 13
Followed too close11 (5.6%)↓-15.4%prior 13
Driver Distraction: Other interior distraction11 (5.6%)↑22.2%prior 9
Other (explain in narrative): Other7 (3.6%)↓-63.2%prior 19
Made improper turn4 (2%)↓-20.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The majority of crashes in both periods occurred in ideal conditions, with the proportion of such incidents increasing year-over-year. In 2024, 64.5% of crashes happened in clear weather and 71.1% on dry roads, up from 58.7% and 64.2% respectively in 2023. Crashes during daylight hours accounted for 57.4% of the total in 2024, a slight increase from 53.8% in the prior year.

Weather

Clear127 (73.0%)
↓-24.9%prior 169
Cloudy22 (12.6%)
↓-26.7%prior 30
Blowing Snow6 (3.4%)
Rain6 (3.4%)
↓-14.3%prior 7
Snow5 (2.9%)
↓-75.0%prior 20
Fog, smoke, smog3 (1.7%)
Severe Winds2 (1.1%)
Freezing rain/drizzle2 (1.1%)
↓-66.7%prior 6
Other (explain in narrative)1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight113 (64.2%)
↓-27.1%prior 155
Dark - roadway not lighted38 (21.6%)
↓-35.6%prior 59
Dark - roadway lighted11 (6.3%)
↓-15.4%prior 13
Dawn6 (3.4%)
↓-14.3%prior 7
Dusk6 (3.4%)
↓-14.3%prior 7
Dark - unknown roadway lighting2 (1.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry140 (80.5%)
↓-24.3%prior 185
Wet13 (7.5%)
→0.0%prior 13
Snow10 (5.7%)
↓-37.5%prior 16
Ice/frost5 (2.9%)
↓-64.3%prior 14
Gravel3 (1.7%)
↓-57.1%prior 7
Slush2 (1.1%)
Mud, dirt1 (0.6%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent year-over-year, with Ford and Chevrolet models being the most frequently recorded in both periods. Ford vehicles were involved in 51 crashes in 2024, down from 56 in 2023. The age distribution of individuals involved in crashes shifted, with the 26-34 age group becoming the largest cohort in 2024, accounting for 50 people. This is a change from 2023, when the 35-44 age group was the most represented with 100 people.

Top Vehicle Makes (299 vehicles)

1
FORD51 (17.1%)
↓-8.9%prior 56
2
CHEV31 (10.4%)
↓-43.6%prior 55
3
CHEVROLET26 (8.7%)
↑8.3%prior 24
4
FREIGHTLINER18 (6%)
↓-5.3%prior 19
5
JEEP15 (5%)
↑50.0%prior 10
6
DODG11 (3.7%)
↓-45.0%prior 20
7
GMC11 (3.7%)
→0.0%prior 11
8
HONDA10 (3.3%)
↑66.7%prior 6
9
TOYOTA9 (3%)
↓-10.0%prior 10
10
HOND8 (2.7%)
↑60.0%prior 5

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (200 persons with recorded sex)

Male132 (66.0%)
↓-48.2%prior 255
Female68 (34.0%)
↓-38.7%prior 111

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 197
  • Total persons involved: 311
  • Total vehicles involved: 299

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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