Yearly Traffic Safety Analysis

98 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Worth County, total traffic crashes remained relatively stable, increasing slightly from 96 in 2023 to 98 in 2024, a change of approximately 2.1%. While total injuries decreased from 39 to 34, the most significant year-over-year shift was the introduction of 4 fatalities resulting from 2 fatal crashes in 2024, compared to zero in the prior year.

98

▲ 2.1%was 96

Total Crash Events

4

Persons Killed

34

▼ -12.8%was 39

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (4) 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 · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall crash volume in Worth County saw a minor increase of 2.1% from 96 incidents in 2023 to 98 in 2024. Despite this relative stability in crash numbers, the severity of outcomes worsened, with total fatalities rising from 0 to 4. Conversely, the number of people injured in crashes decreased by 12.8%, from 39 to 34.

Vulnerable Road User Casualties

4

Motorists Killed

Prior: 0→%

34

Motorists Injured

Prior: 39↓-12.8%

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 shifted between the two periods. While the peak hour for crashes was consistent at 5 p.m. in both years (8 crashes in 2023, 9 in 2024), the peak day for incidents moved from Friday (18 crashes) in 2023 to Sunday (24 crashes) in 2024. Crashes on Sunday increased by 60% year-over-year, from 15 to 24.

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

Crash severity notably increased in 2024 compared to 2023. The county recorded 2 fatal crashes, accounting for 2% of all incidents, whereas there were no fatal crashes in the prior year. The proportion of crashes resulting in serious injuries decreased from 3.1% (3 crashes) in 2023 to 1.0% (1 crash) in 2024. Similarly, minor injury crashes fell from 16.7% to 13.3% of the total.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 4 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes2%
Serious Injury1serious injury crashes1%
↓-66.7%prior 3
Minor Injury13minor injury crashes13.3%
↓-18.8%prior 16
Possible Injury12possible injury crashes12.2%
↑100.0%prior 6
No Injury70no injury crashes71.4%
↓-1.4%prior 71

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 leading contributing factor in both periods, though the count of these incidents decreased by 20% from 40 in 2023 to 32 in 2024. The number of crashes attributed to 'Ran off road - left' more than doubled, increasing from 3 to 7 incidents. Conversely, crashes involving 'Followed too close' and 'FTYROW: From stop sign' saw significant decreases, falling from 6 incidents each in 2023 to 2 and 3 incidents, respectively, in 2024.

Officer-Reported Primary Contributing Cause

Animal32 (32.7%)↓-20.0%prior 40
Lost Control8 (8.2%)→0.0%prior 8
Ran off road - straight7 (7.1%)→0.0%prior 7
Ran off road - left7 (7.1%)
Driving too fast for conditions6 (6.1%)
Driver Distraction: Other interior distraction3 (3.1%)
FTYROW: From stop sign3 (3.1%)↓-50.0%prior 6
Made improper turn3 (3.1%)
Driver Distraction: Inattentive/lost in thought2 (2%)
Driver Distraction: Manual operation of an electronic communication device2 (2%)

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

Road & Environmental Conditions

Year-over-year, driving conditions for crashes showed some shifts. Crashes during daylight hours increased from 37 in 2023 to 46 in 2024, while those in darkness on unlighted roadways decreased from 26 to 19. The number of crashes on dry road surfaces was identical at 49 for both years. Crashes occurring on icy or frosty roads increased from 4 to 7 incidents.

Weather

Clear45 (67.2%)
↓-10.0%prior 50
Cloudy7 (10.4%)
→0.0%prior 7
Freezing rain/drizzle4 (6.0%)
Rain3 (4.5%)
Fog, smoke, smog3 (4.5%)
Snow2 (3.0%)
Sleet, hail1 (1.5%)
Blowing Snow1 (1.5%)
Severe Winds1 (1.5%)

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

Lighting

Daylight46 (67.6%)
↑24.3%prior 37
Dark - roadway not lighted19 (27.9%)
↓-26.9%prior 26
Dark - roadway lighted2 (2.9%)
Dusk1 (1.5%)

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

Road Surface

Dry49 (72.1%)
→0.0%prior 49
Ice/frost7 (10.3%)
Wet4 (5.9%)
Slush3 (4.4%)
Gravel3 (4.4%)
↓-40.0%prior 5
Snow2 (2.9%)

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

Vehicles & Demographics

The total number of persons involved in crashes decreased from 203 in 2023 to 137 in 2024, with notable reductions in the 16-20 age group (from 22 to 9 persons) and the 35-44 age group (from 45 to 26 persons). In terms of vehicle makes, Chevrolet and Ford were the most frequently involved in both years. In 2024, Chevrolet-branded vehicles (CHEV/CHEVROLET) were involved in 28 crashes, the same as in 2023, while Ford vehicles were involved in 16 crashes, down from 19 in the prior year.

Top Vehicle Makes (128 vehicles)

1
CHEV19 (14.8%)
→0.0%prior 19
2
FORD16 (12.5%)
↓-15.8%prior 19
3
JEEP9 (7%)
4
CHEVROLET9 (7%)
→0.0%prior 9
5
TOYO5 (3.9%)
6
FREIGHTLINER5 (3.9%)
7
GMC5 (3.9%)
↓-16.7%prior 6
8
HOND4 (3.1%)
9
TOYOTA4 (3.1%)
10
NR4 (3.1%)

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

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

Sex Distribution (63 persons with recorded sex)

Male43 (68.3%)
↓-53.8%prior 93
Female20 (31.7%)
↓-41.2%prior 34

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: 98
  • Total persons involved: 137
  • Total vehicles involved: 128

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

ThatCarHitMe.com · An Injuria.ai Company