Yearly Traffic Safety Analysis

144 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In O'Brien County, total traffic crashes remained relatively stable, with 144 incidents in 2023 compared to 142 in 2022, a slight increase of 1.4%. The most significant year-over-year change was a substantial improvement in crash outcomes, as fatalities dropped from five in the prior period to zero in the current period. Concurrently, total injuries decreased from 72 to 60.

144

▲ 1.4%was 142

Total Crash Events

0

▼ -100.0%was 5

Persons Killed

60

▼ -16.7%was 72

Persons Injured

0

▼ -100.0%was 5

Fatal Crash Events

Note: "Persons Killed" (0) counts individual fatalities across all crash events. "Fatal" in the severity table below (0) 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 trends in O'Brien County show a stable volume of incidents but a significant decrease in severity year-over-year. While total crashes increased by just two incidents (from 142 to 144), the number of fatal crashes fell from five to zero. Similarly, the total number of people injured in crashes declined by 16.7%, from 72 in 2022 to 60 in 2023.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 5↓-100.0%

3

Pedestrians Injured

Prior: 2↑50.0%

57

Motorists Injured

Prior: 70↓-18.6%

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, the peak day for crashes was Tuesday, with 31 incidents, a change from Monday (26 crashes) in the prior year. The peak hour also moved significantly, from the 7 a.m. morning commute hour in 2022 (14 crashes) to the 3 p.m. afternoon hour in 2023 (20 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 markedly decreased in 2023 compared to the previous year. Fatal crashes were eliminated entirely, falling from five incidents in 2022 to zero in 2023. Crashes resulting in serious injuries also declined, from seven to five. While the count of crashes with possible injuries increased from 18 to 29, the most severe outcomes saw a clear reduction.

Outcome by Severity (Crash Events)

Serious Injury5serious injury crashes3.5%
↓-28.6%prior 7
Minor Injury17minor injury crashes11.8%
↓-15.0%prior 20
Possible Injury29possible injury crashes20.1%
↑61.1%prior 18
No Injury93no injury crashes64.6%
↑1.1%prior 92

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 leading contributing factors showed some shifts between periods, though failure to yield remained a primary concern. "FTYROW: From stop sign" was the top factor in both years, with its count decreasing from 19 crashes in 2022 to 17 in 2023. Crashes attributed to "Followed too close" saw a notable reduction, falling from 17 incidents to 11. Meanwhile, crashes involving "Driving too fast for conditions" remained unchanged at 12 incidents in both years.

Officer-Reported Primary Contributing Cause

FTYROW: From stop sign17 (11.8%)↓-10.5%prior 19
Driving too fast for conditions12 (8.3%)→0.0%prior 12
Followed too close11 (7.6%)↓-35.3%prior 17
Lost Control10 (6.9%)↓-16.7%prior 12
Animal9 (6.3%)↑28.6%prior 7
FTYROW: At uncontrolled intersection9 (6.3%)
Other (explain in narrative): Other7 (4.9%)
Ran Stop Sign6 (4.2%)↓-14.3%prior 7
Driver Distraction: Other interior distraction6 (4.2%)
Ran off road - left6 (4.2%)↓-14.3%prior 7

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 most environmental conditions remained proportionally similar, there was a notable shift in road surface conditions between the two periods. Crashes on dry roads decreased from 107 in 2022 to 91 in 2023. Conversely, collisions on wet roads more than tripled, increasing from 3 to 11 incidents. Crashes in daylight conditions remained the majority in both years, increasing slightly from 101 to 105.

Weather

Clear93 (68.4%)
↑3.3%prior 90
Cloudy27 (19.9%)
↓-12.9%prior 31
Snow5 (3.7%)
↓-16.7%prior 6
Fog, smoke, smog5 (3.7%)
Rain4 (2.9%)
Freezing rain/drizzle1 (0.7%)
Blowing Snow1 (0.7%)

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

Lighting

Daylight105 (76.6%)
↑4.0%prior 101
Dark - roadway lighted14 (10.2%)
→0.0%prior 14
Dark - roadway not lighted14 (10.2%)
↓-26.3%prior 19
Dawn3 (2.2%)
Dusk1 (0.7%)

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

Road Surface

Dry91 (66.4%)
↓-15.0%prior 107
Snow14 (10.2%)
↓-6.7%prior 15
Ice/frost12 (8.8%)
↑33.3%prior 9
Wet11 (8.0%)
Gravel7 (5.1%)
Slush2 (1.5%)

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

Vehicles & Demographics

The makes of vehicles involved in crashes remained consistent, with Chevrolet and Ford models collectively accounting for the highest number of vehicles in both 2022 and 2023. An analysis of the age of persons involved shows a shift in demographics. The number of individuals in the 16-20 age group involved in crashes increased from 46 to 53, and those in the 65+ group rose from 45 to 51. In contrast, involvement for the 35-44 age group decreased from 56 to 44 persons.

Top Vehicle Makes (247 vehicles)

1
CHEV49 (19.8%)
↑11.4%prior 44
2
FORD48 (19.4%)
↑9.1%prior 44
3
CHEVROLET16 (6.5%)
↑23.1%prior 13
4
GMC15 (6.1%)
↓-16.7%prior 18
5
JEEP12 (4.9%)
↑140.0%prior 5
6
DODG12 (4.9%)
→0.0%prior 12
7
BUIC7 (2.8%)
↓-22.2%prior 9
8
DODGE6 (2.4%)
→0.0%prior 6
9
NISS5 (2%)
10
TOYT5 (2%)

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

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

Sex Distribution (227 persons with recorded sex)

Male137 (60.4%)
↓-6.2%prior 146
Female90 (39.6%)
↑13.9%prior 79

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: 144
  • Total persons involved: 333
  • Total vehicles involved: 247

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

ThatCarHitMe.com · An Injuria.ai Company