Yearly Traffic Safety Analysis

159 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Humboldt County recorded 159 total crashes, an increase of 5.3% from the 151 crashes reported in 2022. While overall crashes rose, the number of fatalities decreased significantly from 4 in the prior year to 1 in 2023. The most notable shift in contributing factors was a 47.5% increase in crashes involving animals, which rose from 40 to 59 incidents.

159

▲ 5.3%was 151

Total Crash Events

1

▼ -75.0%was 4

Persons Killed

49

▼ -2.0%was 50

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Crash volume in Humboldt County showed a slight upward trend, increasing by 5.3% from 151 incidents in 2022 to 159 in 2023. Despite the rise in total crashes, outcomes improved, with total fatalities decreasing from 4 to 1. The number of injuries remained stable, with 49 recorded in 2023 compared to 50 in the prior year.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 4↓-75.0%

1

Cyclists Injured

Prior: 0→%

48

Motorists Injured

Prior: 49↓-2.0%

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 timing of crashes shifted year-over-year, with the peak day for collisions moving from Monday (29 crashes) in 2022 to Thursday (31 crashes) in 2023. The peak hour remained consistent at 5 p.m. for both periods, though the crash count during this hour increased from 13 to 15. Notably, the 6 a.m. hour saw a significant increase in incidents, rising from 6 crashes in 2022 to 14 in 2023.

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

Overall crash severity decreased in 2023 compared to the previous year. The number of fatal crashes dropped from 3 in 2022 to 1 in 2023, and serious injury crashes also fell from 8 to 5. In contrast, crashes resulting in minor injuries increased from 11 to 15, and possible injury crashes rose from 15 to 19. The proportion of non-injury crashes remained stable at approximately 75% for both periods.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.6%
↓-66.7%prior 3
Serious Injury5serious injury crashes3.1%
↓-37.5%prior 8
Minor Injury15minor injury crashes9.4%
↑36.4%prior 11
Possible Injury19possible injury crashes11.9%
↑26.7%prior 15
No Injury119no injury crashes74.8%
↑4.4%prior 114

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 animals were the leading contributing factor in both periods, with the count increasing by 47.5% from 40 crashes in 2022 to 59 in 2023. This factor's share of all crashes grew from 26.5% in 2022 to 37.1% in 2023. Crashes attributed to 'Failure to yield from a stop sign' also increased from 9 to 12 incidents. Meanwhile, crashes due to 'Ran off road - straight' and 'Lost Control' both saw a decrease in count, falling from 12 to 10 and 11 to 9, respectively.

Officer-Reported Primary Contributing Cause

Animal59 (37.1%)↑47.5%prior 40
FTYROW: From stop sign12 (7.5%)↑33.3%prior 9
Ran off road - straight10 (6.3%)↓-16.7%prior 12
Lost Control9 (5.7%)↓-18.2%prior 11
Driving too fast for conditions8 (5%)
FTYROW: From driveway4 (2.5%)
Driver Distraction: Other interior distraction4 (2.5%)
Ran off road - left3 (1.9%)↓-62.5%prior 8
FTYROW: Other (explain in narrative)3 (1.9%)
Ran Stop Sign3 (1.9%)

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

Road & Environmental Conditions

Crashes in clear weather and on dry roads were less frequent in 2023, decreasing from 76 to 64 and 79 to 69, respectively. The number of crashes in daylight conditions was identical at 67 for both years. Collisions on dark, unlighted roadways saw a notable drop from 27 incidents in 2022 to 20 in 2023, while crashes on dark, lighted roads increased from 7 to 10.

Weather

Clear64 (64.6%)
↓-15.8%prior 76
Cloudy17 (17.2%)
↓-5.6%prior 18
Snow9 (9.1%)
↑50.0%prior 6
Blowing Snow3 (3.0%)
↓-40.0%prior 5
Rain3 (3.0%)
Fog, smoke, smog2 (2.0%)
Freezing rain/drizzle1 (1.0%)

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

Lighting

Daylight67 (65.7%)
→0.0%prior 67
Dark - roadway not lighted20 (19.6%)
↓-25.9%prior 27
Dark - roadway lighted10 (9.8%)
↑42.9%prior 7
Dawn3 (2.9%)
Dusk1 (1.0%)
↓-80.0%prior 5
Dark - unknown roadway lighting1 (1.0%)

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

Road Surface

Dry69 (69.7%)
↓-12.7%prior 79
Wet11 (11.1%)
→0.0%prior 11
Ice/frost11 (11.1%)
↓-8.3%prior 12
Snow4 (4.0%)
↓-55.6%prior 9
Slush3 (3.0%)
Gravel1 (1.0%)

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

Vehicles & Demographics

The top three vehicle makes involved in crashes—Ford, Chevrolet, and GMC—all saw their numbers increase in 2023 compared to 2022. The demographic of persons involved in crashes shifted toward younger age groups; the 16-20 age group grew from 53 to 63 individuals and the 26-34 group increased from 44 to 57. Conversely, involvement decreased for older age groups, with the 35-44 group dropping from 58 to 48 and the 65+ group falling from 45 to 36.

Top Vehicle Makes (225 vehicles)

1
FORD41 (18.2%)
↑5.1%prior 39
2
CHEV38 (16.9%)
↑22.6%prior 31
3
GMC21 (9.3%)
↑40.0%prior 15
4
CHEVROLET11 (4.9%)
→0.0%prior 11
5
BUIC10 (4.4%)
↑11.1%prior 9
6
DODG10 (4.4%)
↓-41.2%prior 17
7
CHRY9 (4%)
↓-18.2%prior 11
8
JEEP6 (2.7%)
→0.0%prior 6
9
KIA5 (2.2%)
10
TOYT5 (2.2%)
↓-54.5%prior 11

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

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

Sex Distribution (212 persons with recorded sex)

Male120 (56.6%)
↑3.4%prior 116
Female92 (43.4%)
↑7.0%prior 86

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: 159
  • Total persons involved: 340
  • Total vehicles involved: 225

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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