Yearly Traffic Safety Analysis

78 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In Pocahontas County, total vehicle crashes increased by 13% from 69 in 2022 to 78 in 2023. While total injuries decreased slightly and fatalities fell from one to zero, the most notable year-over-year shift was a significant rise in specific driver behaviors. Crashes attributed to drivers losing control or running stop signs both more than doubled, and incidents involving a DUI rose from 3 to 7.

78

▲ 13.0%was 69

Total Crash Events

0

▼ -100.0%was 1

Persons Killed

30

▼ -11.8%was 34

Persons Injured

0

▼ -100.0%was 1

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 traffic crash trends in Pocahontas County were mixed. The total number of crashes rose from 69 in 2022 to 78 in 2023, marking a 13% increase in incidents. However, the severity of these crashes lessened, with total injuries decreasing from 34 to 30 and the single fatality from the prior year not being repeated in 2023.

Vulnerable Road User Casualties

0

Motorists Killed

Prior: 1↓-100.0%

30

Motorists Injured

Prior: 34↓-11.8%

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, Monday was the peak day for crashes with 17 incidents, a change from 2022 when Thursday was the peak with 18 crashes. The most common time for a crash also shifted earlier, from the 5 p.m. hour in the prior year (8 crashes) to the 3 p.m. hour 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 decreased in 2023 compared to the prior year. The county recorded zero fatal crashes, down from one in 2022. The number of serious injury crashes also fell from 6 to 2, representing a drop from 8.7% to 2.6% of all crashes. In contrast, crashes resulting in minor or possible injuries increased in both count and proportion, rising from a combined 16 incidents to 22.

Outcome by Severity (Crash Events)

Serious Injury2serious injury crashes2.6%
↓-66.7%prior 6
Minor Injury12minor injury crashes15.4%
↑33.3%prior 9
Possible Injury10possible injury crashes12.8%
↑42.9%prior 7
No Injury54no injury crashes69.2%
↑17.4%prior 46

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 periods, with 15 crashes in 2023 compared to 14 in 2022. Significant changes were observed in other driver-related factors; crashes attributed to 'Lost Control' more than doubled from 6 to 13 incidents, and 'Ran Stop Sign' crashes also increased from 4 to 9. Conversely, crashes where a vehicle 'Ran off road - straight' saw a notable decrease from 9 incidents to 2.

Officer-Reported Primary Contributing Cause

Animal15 (19.2%)↑7.1%prior 14
Lost Control13 (16.7%)↑116.7%prior 6
Ran Stop Sign9 (11.5%)
Ran off road - left6 (7.7%)
Driver Distraction: Other interior distraction5 (6.4%)→0.0%prior 5
Driving too fast for conditions5 (6.4%)↓-16.7%prior 6
Followed too close3 (3.8%)
FTYROW: From parked position2 (2.6%)
FTYROW: From stop sign2 (2.6%)
Made improper turn2 (2.6%)

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 the raw number of crashes in daylight increased, the proportion of crashes occurring in unlit dark roadways grew from 15.9% (11 crashes) in 2022 to 23.1% (18 crashes) in 2023. Regarding road surface conditions, crashes on dry roads increased from 40 to 49, but incidents on gravel surfaces more than doubled from 3 to 7 year-over-year. Weather conditions remained a relatively consistent factor across both periods.

Weather

Clear49 (71.0%)
↑25.6%prior 39
Cloudy14 (20.3%)
↑7.7%prior 13
Freezing rain/drizzle2 (2.9%)
Rain2 (2.9%)
Severe Winds1 (1.4%)
Blowing Snow1 (1.4%)

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

Lighting

Daylight44 (63.8%)
↑15.8%prior 38
Dark - roadway not lighted18 (26.1%)
↑63.6%prior 11
Dark - roadway lighted4 (5.8%)
Dawn2 (2.9%)
Dusk1 (1.4%)

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

Road Surface

Dry49 (71.0%)
↑22.5%prior 40
Ice/frost7 (10.1%)
→0.0%prior 7
Gravel7 (10.1%)
Wet3 (4.3%)
Snow2 (2.9%)
Slush1 (1.4%)

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

Vehicles & Demographics

The makes of vehicles most frequently involved in crashes shifted significantly year-over-year. Ford-made vehicles involved in crashes increased from 17 to 32, making it the top make, while Chevrolet-involved vehicles decreased from 22 to 10. Demographically, the number of persons aged 26-34 involved in crashes increased from 13 to 20. In contrast, the number of people involved from the 21-25, 35-44, and 65+ age groups all decreased.

Top Vehicle Makes (110 vehicles)

1
FORD32 (29.1%)
↑88.2%prior 17
2
CHEV10 (9.1%)
↓-54.5%prior 22
3
CHRY6 (5.5%)
4
JEEP5 (4.5%)
5
BUIC5 (4.5%)
↓-44.4%prior 9
6
TOYT4 (3.6%)
7
DODG4 (3.6%)
↓-42.9%prior 7
8
TOYO4 (3.6%)
9
PONT3 (2.7%)
10
NISS3 (2.7%)

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

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

Sex Distribution (100 persons with recorded sex)

Male68 (68.0%)
↓-17.1%prior 82
Female32 (32.0%)
↑52.4%prior 21

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: 78
  • Total persons involved: 154
  • Total vehicles involved: 110

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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