Yearly Traffic Safety Analysis

141 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Fremont County recorded 141 total crashes, a marginal decrease from the 142 crashes recorded in 2022. While overall crash volume remained stable, the number of fatal crashes increased from 3 in the prior year to 5 in the current year. Correspondingly, total fatalities rose from 4 to 5, and total injuries increased slightly from 55 to 57.

141

▼ -0.7%was 142

Total Crash Events

5

▲ 25.0%was 4

Persons Killed

57

▲ 3.6%was 55

Persons Injured

5

▲ 66.7%was 3

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (5) 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 crash volume in Fremont County remained nearly stable year-over-year, with a minor decrease from 142 crashes in 2022 to 141 in 2023. Despite the stable crash total, the number of people injured increased from 55 to 57, and fatalities rose from 4 to 5.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

4

Motorists Killed

Prior: 4→0.0%

0

Pedestrians Injured

Prior: 0→0.0%

57

Motorists Injured

Prior: 55↑3.6%

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 between the two periods. In 2023, Wednesday was the peak day for crashes with 31 incidents, a change from Saturday being the peak day in 2022 with 26 crashes. The peak hour for collisions also moved from the morning commute at 7 a.m. in the prior year (12 crashes) to the early afternoon at 1 p.m. in the current year (11 crashes).

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 increased in 2023, with the number of fatal crashes rising to 5 from 3 in the previous year, representing 3.5% of all crashes compared to 2.1% in 2022. While crashes resulting in serious injuries decreased from 7 to 4, incidents involving minor injuries rose from 17 to 20. The proportion of crashes with no injuries decreased from 71.1% in 2022 to 68.1% in 2023.

Outcome by Severity (Crash Events)

Fatal5fatal crashes3.5%
↑66.7%prior 3
Serious Injury4serious injury crashes2.8%
↓-42.9%prior 7
Minor Injury20minor injury crashes14.2%
↑17.6%prior 17
Possible Injury16possible injury crashes11.3%
↑14.3%prior 14
No Injury96no injury crashes68.1%
↓-5.0%prior 101

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 an animal remained the top contributing factor in both years, with 38 incidents in 2023 compared to 37 in 2022. The number of crashes attributed to 'Lost Control' increased by 86%, rising from 14 incidents to 26 and becoming the second-ranked factor in 2023. Conversely, crashes involving 'Failure to Yield Right of Way from a stop sign' decreased by 60%, falling from 10 incidents in 2022 to 4 in 2023.

Officer-Reported Primary Contributing Cause

Animal38 (27%)↑2.7%prior 37
Lost Control26 (18.4%)↑85.7%prior 14
Ran off road - straight11 (7.8%)
Followed too close10 (7.1%)↑25.0%prior 8
Driving too fast for conditions7 (5%)↑16.7%prior 6
Operating vehicle in an reckless, erratic, careless, negligent manner6 (4.3%)↓-25.0%prior 8
FTYROW: From driveway5 (3.5%)
Ran Stop Sign5 (3.5%)→0.0%prior 5
Made improper turn4 (2.8%)
FTYROW: From stop sign4 (2.8%)↓-60.0%prior 10

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

Road & Environmental Conditions

While clear weather and dry roads were the most common conditions in both years, there was an increase in crashes occurring during adverse conditions in 2023. Crashes on roads with ice, frost, snow, or wet surfaces increased from 23 incidents in 2022 to 32 in 2023. Similarly, crashes during non-clear weather like snow, rain, or fog rose from 9 to 17 incidents year-over-year. The distribution of crashes by lighting conditions remained relatively stable.

Weather

Clear73 (68.2%)
↓-16.1%prior 87
Cloudy17 (15.9%)
↑21.4%prior 14
Snow7 (6.5%)
↑40.0%prior 5
Freezing rain/drizzle5 (4.7%)
Rain3 (2.8%)
Sleet, hail1 (0.9%)
Fog, smoke, smog1 (0.9%)

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

Lighting

Daylight71 (66.4%)
↓-6.6%prior 76
Dark - roadway not lighted23 (21.5%)
↓-8.0%prior 25
Dusk5 (4.7%)
Dawn4 (3.7%)
Dark - roadway lighted4 (3.7%)
↓-33.3%prior 6

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

Road Surface

Dry74 (69.2%)
↓-15.9%prior 88
Ice/frost13 (12.1%)
Wet11 (10.3%)
↑57.1%prior 7
Snow5 (4.7%)
Gravel2 (1.9%)
↓-71.4%prior 7
Other (explain in narrative)1 (0.9%)
Slush1 (0.9%)

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

Vehicles & Demographics

The top vehicle makes involved in crashes remained consistent, with Chevrolet (39 vehicles) and Ford (27 vehicles) being the most common in 2023, similar to the prior year (36 and 26 vehicles, respectively). An analysis of persons involved shows a notable increase in the 16-20 age group, which grew from 41 individuals in 2022 to 54 in 2023. The number of individuals aged 65 and older also saw a slight increase from 31 to 35.

Top Vehicle Makes (187 vehicles)

1
FORD27 (14.4%)
↑3.8%prior 26
2
CHEVROLET26 (13.9%)
↑62.5%prior 16
3
CHEV13 (7%)
↓-35.0%prior 20
4
GMC11 (5.9%)
↑83.3%prior 6
5
FREIGHTLINER8 (4.3%)
↓-42.9%prior 14
6
KENWORTH6 (3.2%)
↑20.0%prior 5
7
KIA6 (3.2%)
↓-14.3%prior 7
8
TOYOTA6 (3.2%)
↓-25.0%prior 8
9
HONDA5 (2.7%)
→0.0%prior 5
10
DODGE5 (2.7%)
↓-61.5%prior 13

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

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

Sex Distribution (180 persons with recorded sex)

Male127 (70.6%)
↓-7.3%prior 137
Female53 (29.4%)
↑3.9%prior 51

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: 141
  • Total persons involved: 287
  • Total vehicles involved: 187

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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