Yearly Traffic Safety Analysis

123 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Kossuth County recorded 123 total crashes, a 23.6% decrease from the 161 crashes reported in 2022. The most significant year-over-year change was the reduction in traffic fatalities, which fell from 3 in 2022 to 0 in 2023. Overall, key metrics including total crashes, injuries, and fatalities all showed a decline.

123

▼ -23.6%was 161

Total Crash Events

0

▼ -100.0%was 3

Persons Killed

51

▼ -25.0%was 68

Persons Injured

0

▼ -100.0%was 3

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

Traffic safety metrics in Kossuth County showed a positive trend, with crashes falling from 161 in 2022 to 123 in 2023. This represents a 23.6% year-over-year decrease in total collisions. Correspondingly, the number of people injured decreased by 25%, from 68 to 51, and fatalities were eliminated, dropping from 3 to 0.

Vulnerable Road User Casualties

0

Cyclists Killed

Prior: 0→0.0%

0

Motorists Killed

Prior: 3↓-100.0%

1

Cyclists Injured

Prior: 0→%

50

Motorists Injured

Prior: 68↓-26.5%

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 slightly between periods. In 2023, Friday was the peak day for crashes with 27 incidents, a change from 2022 when Monday was the peak day with 28 crashes. The afternoon commute remained the most frequent time for collisions, with the peak hour shifting from a tie between 3 p.m. and 4 p.m. in 2022 (15 crashes each) to a more distinct peak at 3 p.m. in 2023 (16 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 improved significantly in 2023 compared to the prior year. The number of fatal crashes dropped from 3 in 2022 to 0 in 2023, and the count of serious injury crashes decreased from 8 to 6. While the total number of injury-related crashes declined, the proportion of crashes resulting in minor injuries increased from 12.4% of all crashes in 2022 to 14.6% in 2023.

Outcome by Severity (Crash Events)

Serious Injury6serious injury crashes4.9%
↓-25.0%prior 8
Minor Injury18minor injury crashes14.6%
↓-10.0%prior 20
Possible Injury15possible injury crashes12.2%
↓-25.0%prior 20
No Injury84no injury crashes68.3%
↓-23.6%prior 110

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 primary contributing factors to crashes showed some consistency and some changes year-over-year. 'Lost Control' was the top-cited factor in 2023 with 14 crashes, a slight decrease from 16 crashes in 2022. 'Failure to yield from a stop sign' was the second-most common factor, holding steady with 12 incidents in both years. Notably, the non-specific 'Other' category, which accounted for 18 crashes in 2022, dropped to 6 crashes in 2023.

Officer-Reported Primary Contributing Cause

Lost Control14 (11.4%)↓-12.5%prior 16
FTYROW: From stop sign12 (9.8%)→0.0%prior 12
Ran Stop Sign8 (6.5%)↓-11.1%prior 9
Driving too fast for conditions8 (6.5%)↓-11.1%prior 9
Animal7 (5.7%)↓-12.5%prior 8
Other (explain in narrative): Other6 (4.9%)↓-66.7%prior 18
Driver Distraction: Other interior distraction6 (4.9%)
Ran off road - left6 (4.9%)↑20.0%prior 5
Operating vehicle in an reckless, erratic, careless, negligent manner5 (4.1%)
Improper Backing5 (4.1%)→0.0%prior 5

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

Road & Environmental Conditions

In 2023, a greater share of crashes occurred in the dark and on dry roads compared to 2022. The proportion of crashes happening in dark conditions (both lighted and unlighted) rose from 16.1% in 2022 to 28.5% in 2023. Crashes on dry road surfaces increased from 60.2% to 69.9% of the total, while incidents on roads with ice, snow, or slush decreased from 22.4% of all crashes in 2022 to 17.1% in 2023.

Weather

Clear79 (66.4%)
↓-17.7%prior 96
Cloudy21 (17.6%)
↓-22.2%prior 27
Rain5 (4.2%)
→0.0%prior 5
Fog, smoke, smog5 (4.2%)
Snow4 (3.4%)
↓-66.7%prior 12
Severe Winds3 (2.5%)
Freezing rain/drizzle1 (0.8%)
Sleet, hail1 (0.8%)

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

Lighting

Daylight78 (65.0%)
↓-34.5%prior 119
Dark - roadway not lighted19 (15.8%)
↑46.2%prior 13
Dark - roadway lighted16 (13.3%)
↑23.1%prior 13
Dusk4 (3.3%)
Dawn3 (2.5%)
↓-40.0%prior 5

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

Road Surface

Dry86 (71.7%)
↓-11.3%prior 97
Ice/frost13 (10.8%)
↓-18.8%prior 16
Wet10 (8.3%)
↓-9.1%prior 11
Snow7 (5.8%)
↓-63.2%prior 19
Gravel2 (1.7%)
↓-75.0%prior 8
Mud, dirt1 (0.8%)
Slush1 (0.8%)

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 saw a shift in ranking between the two years. In 2023, Ford became the most common make with 54 vehicles involved, up from 41 in 2022. Chevrolet, the top make in 2022 with 53 vehicles, saw its involvement decrease to 46 vehicles in 2023. The age demographics of persons involved in crashes also changed, with the proportion of individuals aged 65 and older increasing from 15.5% in 2022 to 18.3% in 2023.

Top Vehicle Makes (207 vehicles)

1
FORD54 (26.1%)
↑31.7%prior 41
2
CHEV38 (18.4%)
↓-5.0%prior 40
3
DODG12 (5.8%)
↑71.4%prior 7
4
JEEP8 (3.9%)
↓-20.0%prior 10
5
CHEVROLET8 (3.9%)
↓-38.5%prior 13
6
GMC7 (3.4%)
↓-61.1%prior 18
7
TOYO7 (3.4%)
8
BUIC5 (2.4%)
↓-54.5%prior 11
9
DODGE5 (2.4%)
↓-37.5%prior 8
10
PONT5 (2.4%)

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

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

Sex Distribution (190 persons with recorded sex)

Male113 (59.5%)
↓-27.1%prior 155
Female77 (40.5%)
↓-15.4%prior 91

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: 123
  • Total persons involved: 273
  • Total vehicles involved: 207

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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