Yearly Traffic Safety Analysis

120 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Hancock County recorded 120 total crashes, a 7.1% increase from the 112 crashes reported in 2022. While total fatalities remained unchanged at one, the most significant year-over-year change was in crashes involving a driver under the influence (DUI), which more than doubled from 7 to 17 incidents.

120

▲ 7.1%was 112

Total Crash Events

1

Persons Killed

44

▲ 15.8%was 38

Persons Injured

1

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

Overall traffic crash trends in Hancock County showed an increase from 2022 to 2023. Total crashes rose by 7.1%, from 112 to 120 incidents. The number of people injured in these crashes also increased by 15.8%, from 38 to 44, while fatalities remained stable with one person killed in each period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

1

Motorists Killed

Prior: 1→0.0%

1

Pedestrians Injured

Prior: 0→%

43

Motorists Injured

Prior: 38↑13.2%

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 temporal patterns of crashes shifted year-over-year. In 2023, the peak days for crashes were Thursday (21 incidents) and Friday (22 incidents), a change from 2022 when Monday was the clear peak with 26 incidents. The most common time for a crash remained consistent, with the 3 p.m. hour being the peak in both periods, recording 17 crashes each year.

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

Crash severity distributions saw some changes between the two periods. The number of fatal crashes was unchanged at one, and the fatal crash rate per 100 crashes decreased slightly from 0.89% in 2022 to 0.83% in 2023. While serious injury crashes were also stable at four incidents, minor injury crashes increased from 13 to 19. Conversely, crashes resulting in possible injury decreased from 20 to 16.

Outcome by Severity (Crash Events)

Fatal1fatal crashes0.8%
→0.0%prior 1
Serious Injury4serious injury crashes3.3%
→0.0%prior 4
Minor Injury19minor injury crashes15.8%
↑46.2%prior 13
Possible Injury16possible injury crashes13.3%
↓-20.0%prior 20
No Injury80no injury crashes66.7%
↑8.1%prior 74

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

The most frequently cited contributing factor in both periods was 'Lost Control,' with the count of these incidents rising from 11 in 2022 to 15 in 2023. 'Driving too fast for conditions,' the second-leading factor in 2022 with 10 incidents, decreased to 7 incidents in 2023. Notably, crashes attributed to 'Ran off road - straight' tripled in count from 3 to 9, and incidents involving a failure to yield while making a left turn increased from 1 to 5.

Officer-Reported Primary Contributing Cause

Lost Control15 (12.5%)↑36.4%prior 11
Other (explain in narrative): Other10 (8.3%)↑25.0%prior 8
Ran off road - straight9 (7.5%)
Driver Distraction: Other interior distraction9 (7.5%)↑12.5%prior 8
Animal8 (6.7%)→0.0%prior 8
Driving too fast for conditions7 (5.8%)↓-30.0%prior 10
Ran off road - left6 (5%)↓-33.3%prior 9
Operating vehicle in an reckless, erratic, careless, negligent manner5 (4.2%)
FTYROW: At uncontrolled intersection5 (4.2%)→0.0%prior 5
FTYROW: Making left turn5 (4.2%)

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

Road & Environmental Conditions

Most crashes in both years occurred in clear weather on dry roads. In 2023, the proportion of crashes on dry surfaces increased to 70.8% from 60.7% in 2022. Correspondingly, crashes on roads with snow or ice decreased significantly, accounting for 12.5% of crashes in 2023 compared to 24.1% in 2022. There was also a shift in lighting conditions, with the count of crashes in the dark on unlit roadways increasing from 14 to 22 incidents.

Weather

Clear83 (72.8%)
↑13.7%prior 73
Cloudy19 (16.7%)
↑18.8%prior 16
Snow4 (3.5%)
↓-20.0%prior 5
Fog, smoke, smog2 (1.8%)
Rain2 (1.8%)
Severe Winds2 (1.8%)
Freezing rain/drizzle2 (1.8%)

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

Lighting

Daylight74 (64.3%)
↓-2.6%prior 76
Dark - roadway not lighted22 (19.1%)
↑57.1%prior 14
Dark - roadway lighted9 (7.8%)
↑80.0%prior 5
Dusk7 (6.1%)
↑16.7%prior 6
Dawn3 (2.6%)

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

Road Surface

Dry85 (73.9%)
↑25.0%prior 68
Gravel9 (7.8%)
Ice/frost9 (7.8%)
↓-30.8%prior 13
Wet6 (5.2%)
→0.0%prior 6
Snow6 (5.2%)
↓-57.1%prior 14

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

Vehicles & Demographics

Chevrolet and Ford were the two most common vehicle makes involved in crashes in both years, though both saw their counts decrease in 2023. The number of GMC vehicles involved in crashes doubled from 7 to 14, while Jeep involvement increased from 2 to 11 vehicles. An analysis of person demographics shows a shift in age group involvement; the number of persons aged 55-64 in crashes rose from 23 to 39, while involvement for those aged 16-20 and 65+ decreased from 39 to 30 and 41 to 28, respectively.

Top Vehicle Makes (181 vehicles)

1
CHEV36 (19.9%)
↓-10.0%prior 40
2
FORD32 (17.7%)
↓-15.8%prior 38
3
GMC14 (7.7%)
↑100.0%prior 7
4
JEEP11 (6.1%)
5
DODG10 (5.5%)
↑11.1%prior 9
6
BUIC8 (4.4%)
7
HOND7 (3.9%)
8
NISS6 (3.3%)
9
TOYOTA5 (2.8%)
10
RAM5 (2.8%)

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

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

Sex Distribution (171 persons with recorded sex)

Male109 (63.7%)
↑14.7%prior 95
Female62 (36.3%)
↓-7.5%prior 67

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: 120
  • Total persons involved: 243
  • Total vehicles involved: 181

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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