Yearly Traffic Safety Analysis

123 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Humboldt County recorded 123 total crashes, a 22.6% decrease from the 159 crashes reported in 2023. Despite the overall reduction in collisions, the number of fatalities increased from one in the prior period to three in the current period.

123

▼ -22.6%was 159

Total Crash Events

3

▲ 200.0%was 1

Persons Killed

36

▼ -26.5%was 49

Persons Injured

2

▲ 100.0%was 1

Fatal Crash Events

Note: "Persons Killed" (3) 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

Crash volumes in Humboldt County saw a notable year-over-year decline, falling from 159 incidents in 2023 to 123 in 2024, representing a 22.6% reduction. The number of injuries also decreased by 26.5%, from 49 to 36. However, fatalities rose from one in the prior period to three in the current period.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 1↑200.0%

1

Cyclists Injured

Prior: 1→0.0%

35

Motorists Injured

Prior: 48↓-27.1%

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 temporal patterns of crashes shifted slightly between the two periods. In 2024, the peak day for crashes was Friday with 28 incidents, whereas in 2023 it was Thursday with 31 incidents. The peak hour for collisions also shifted earlier, from the 5 p.m. hour (15 crashes) in the prior period to the 4 p.m. hour (14 crashes) in the current period.

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

While total crashes decreased, the severity of incidents increased year-over-year. The number of fatal crashes rose from one in 2023 to two in 2024, and the corresponding fatal crash rate increased from 0.63 to 1.63 per 100 crashes. The proportion of crashes resulting in any injury decreased from 24.5% to 22.0%. Crashes resulting in no injury made up a slightly larger share of the total, increasing from 74.8% in 2023 to 76.4% in 2024.

Severity is per crash event (most severe injury). 2 fatal crash events resulted in 3 persons killed.

Outcome by Severity (Crash Events)

Fatal2fatal crashes1.6%
↑100.0%prior 1
Minor Injury20minor injury crashes16.3%
↑33.3%prior 15
Possible Injury7possible injury crashes5.7%
↓-63.2%prior 19
No Injury94no injury crashes76.4%
↓-21.0%prior 119

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 involving an animal remained the top contributing factor in both periods, though the count decreased by 49.2% from 59 crashes in 2023 to 30 in 2024. Several factors saw an increase in crash counts, including 'Made improper turn' (from 1 to 7 crashes), 'Followed too close' (from 2 to 7 crashes), and 'FTYROW: Making left turn' (from 3 to 7 crashes). Conversely, crashes attributed to 'FTYROW: From stop sign' decreased from 12 to 8, and those from 'Ran off road - straight' fell from 10 to 4.

Officer-Reported Primary Contributing Cause

Animal30 (24.4%)↓-49.2%prior 59
Driving too fast for conditions8 (6.5%)→0.0%prior 8
FTYROW: From stop sign8 (6.5%)↓-33.3%prior 12
Followed too close7 (5.7%)
Made improper turn7 (5.7%)
Ran off road - left7 (5.7%)
FTYROW: Making left turn7 (5.7%)
Driver Distraction: Other interior distraction6 (4.9%)
Other (explain in narrative): Other5 (4.1%)
Ran off road - straight4 (3.3%)↓-60.0%prior 10

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

Road & Environmental Conditions

Crashes in 2024 occurred more frequently in ideal conditions compared to 2023. The share of crashes on dry roads increased from 43.4% to 61.8%, and those in daylight rose from 42.1% to 57.7%. Similarly, the proportion of crashes happening in clear weather grew from 40.3% in the prior period to 57.7% in the current period. Crashes on icy or frosty roads accounted for 7.3% of the total in 2024, a slight increase in proportion from 6.9% in 2023.

Weather

Clear71 (74.0%)
↑10.9%prior 64
Cloudy16 (16.7%)
↓-5.9%prior 17
Freezing rain/drizzle3 (3.1%)
Rain3 (3.1%)
Snow2 (2.1%)
↓-77.8%prior 9
Blowing Snow1 (1.0%)

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

Lighting

Daylight71 (74.0%)
↑6.0%prior 67
Dark - roadway not lighted13 (13.5%)
↓-35.0%prior 20
Dark - roadway lighted10 (10.4%)
→0.0%prior 10
Dusk2 (2.1%)

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

Road Surface

Dry76 (79.2%)
↑10.1%prior 69
Ice/frost9 (9.4%)
↓-18.2%prior 11
Snow5 (5.2%)
Wet5 (5.2%)
↓-54.5%prior 11
Sand1 (1.0%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes shifted year-over-year. In 2024, Chevrolet (CHEV) was the most common make with 36 vehicles, followed by Ford with 26. In the prior period, Ford was the top make with 41 vehicles, followed by Chevrolet with 38. The age distribution of persons involved in crashes also changed, with the 65+ age group's representation increasing from 10.6% of all persons in 2023 to 19.6% in 2024. Conversely, the share of persons aged 16-20 decreased from 18.5% to 13.6%.

Top Vehicle Makes (193 vehicles)

1
CHEV36 (18.7%)
↓-5.3%prior 38
2
FORD26 (13.5%)
↓-36.6%prior 41
3
DODG12 (6.2%)
↑20.0%prior 10
4
GMC11 (5.7%)
↓-47.6%prior 21
5
JEEP10 (5.2%)
↑66.7%prior 6
6
BUIC9 (4.7%)
↓-10.0%prior 10
7
CHEVROLET9 (4.7%)
↓-18.2%prior 11
8
TOYT8 (4.1%)
↑60.0%prior 5
9
CHRY7 (3.6%)
↓-22.2%prior 9
10
RAM7 (3.6%)

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

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

Sex Distribution (121 persons with recorded sex)

Male68 (56.2%)
↓-43.3%prior 120
Female53 (43.8%)
↓-42.4%prior 92

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: 123
  • Total persons involved: 199
  • Total vehicles involved: 193

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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