Yearly Traffic Safety Analysis

506 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Sioux County recorded 506 total crashes, a 5.2% increase from the 481 crashes reported in 2022. While total fatalities decreased from 8 to 6 and injuries fell from 211 to 187, one of the most notable shifts was a 33.3% increase in crashes involving a driver under the influence, which rose from 15 incidents in 2022 to 20 in 2023.

506

▲ 5.2%was 481

Total Crash Events

6

▼ -25.0%was 8

Persons Killed

187

▼ -11.4%was 211

Persons Injured

6

Fatal Crash Events

Note: "Persons Killed" (6) counts individual fatalities across all crash events. "Fatal" in the severity table below (6) 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, the total number of crashes in Sioux County increased by 5.2% in 2023, rising from 481 to 506. Despite the rise in crash volume, the severity of outcomes saw a reduction, with total fatalities decreasing by 25% from 8 to 6 and total injuries declining by 11.4% from 211 to 187.

Vulnerable Road User Casualties

1

Pedestrians Killed

Prior: 0→%

0

Cyclists Killed

Prior: 0→0.0%

5

Motorists Killed

Prior: 8↓-37.5%

0

Other Killed

Prior: 0→0.0%

1

Pedestrians Injured

Prior: 2↓-50.0%

2

Cyclists Injured

Prior: 3↓-33.3%

181

Motorists Injured

Prior: 205↓-11.7%

3

Other Injured

Prior: 1↑200.0%

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, Friday was the peak day for crashes with 86 incidents, a change from 2022 when Monday saw the most crashes at 91. The peak hour for collisions also moved later in the day, from 3 PM in 2022 (45 crashes) to the 5 PM rush hour in 2023 (47 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

The number of fatal crashes remained unchanged at 6 in both 2023 and 2022, representing 1.2% of total crashes each year. However, the overall severity of crashes appears to have lessened, with the proportion of crashes resulting in any level of injury (serious, minor, or possible) decreasing from 30.9% of all crashes in 2022 to 26.1% in 2023. Correspondingly, the share of crashes with no reported injuries increased from 67.8% to 72.7%.

Outcome by Severity (Crash Events)

Fatal6fatal crashes1.2%
→0.0%prior 6
Serious Injury12serious injury crashes2.4%
↓-29.4%prior 17
Minor Injury68minor injury crashes13.4%
↓-12.8%prior 78
Possible Injury52possible injury crashes10.3%
↓-3.7%prior 54
No Injury368no injury crashes72.7%
↑12.9%prior 326

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 the count increasing from 97 in 2022 to 106 in 2023. While the top three primary factors were consistent across both years, their counts shifted; crashes attributed to 'Followed too close' decreased from 57 to 51, and 'Driving too fast for conditions' fell from 56 to 51. Conversely, crashes due to 'Lost Control' saw an increase in count from 28 to 33.

Officer-Reported Primary Contributing Cause

Animal106 (20.9%)↑9.3%prior 97
Driving too fast for conditions51 (10.1%)↓-8.9%prior 56
Followed too close51 (10.1%)↓-10.5%prior 57
FTYROW: From stop sign34 (6.7%)↓-20.9%prior 43
Lost Control33 (6.5%)↑17.9%prior 28
Ran off road - left25 (4.9%)↑8.7%prior 23
Ran off road - straight21 (4.2%)↑16.7%prior 18
Improper Backing16 (3.2%)↑45.5%prior 11
FTYROW: Making left turn12 (2.4%)↓-14.3%prior 14
Ran Stop Sign12 (2.4%)↓-40.0%prior 20

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

Road & Environmental Conditions

Crash conditions remained broadly consistent year-over-year, with the majority of incidents in both periods occurring in daylight on dry roads. In 2023, 56.1% of crashes happened in daylight, compared to 58.0% in 2022. Crashes on dry road surfaces accounted for 54.9% of the total in 2023, a slight increase from 53.2% in the prior year. The proportion of crashes occurring on adverse road surfaces like ice, snow, or wet pavement saw a small decrease from 27.0% in 2022 to 24.3% in 2023.

Weather

Clear274 (65.2%)
↑13.7%prior 241
Cloudy94 (22.4%)
↑20.5%prior 78
Snow20 (4.8%)
↓-4.8%prior 21
Rain10 (2.4%)
↓-44.4%prior 18
Fog, smoke, smog10 (2.4%)
↑100.0%prior 5
Blowing Snow8 (1.9%)
↓-57.9%prior 19
Severe Winds2 (0.5%)
Sleet, hail1 (0.2%)
Freezing rain/drizzle1 (0.2%)
↓-91.7%prior 12

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

Lighting

Daylight284 (67.3%)
↑1.8%prior 279
Dark - roadway not lighted74 (17.5%)
↑25.4%prior 59
Dark - roadway lighted42 (10.0%)
↑13.5%prior 37
Dusk12 (2.8%)
↓-7.7%prior 13
Dawn9 (2.1%)
↓-30.8%prior 13
Dark - unknown roadway lighting1 (0.2%)

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

Road Surface

Dry278 (65.9%)
↑8.6%prior 256
Ice/frost52 (12.3%)
↑13.0%prior 46
Snow37 (8.8%)
↓-14.0%prior 43
Wet27 (6.4%)
↓-22.9%prior 35
Gravel20 (4.7%)
↑42.9%prior 14
Slush7 (1.7%)
↑16.7%prior 6
Sand1 (0.2%)

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

Vehicles & Demographics

Chevrolet and Ford vehicles were the most common makes involved in crashes during both periods. In 2023, a combined 207 Chevrolet vehicles were involved (summing 'CHEV' and 'CHEVROLET'), up from 184 in 2022, while the count for Ford vehicles decreased from 152 to 140. Examining the demographics of people involved, the 16-20 age group remained the largest cohort in both years, with 217 individuals in 2023. Notably, the number of persons aged 21-25 involved in crashes increased from 114 in 2022 to 150 in 2023.

Top Vehicle Makes (777 vehicles)

1
CHEV144 (18.5%)
↑5.1%prior 137
2
FORD140 (18%)
↓-7.9%prior 152
3
CHEVROLET63 (8.1%)
↑34.0%prior 47
4
GMC37 (4.8%)
↑27.6%prior 29
5
JEEP28 (3.6%)
↓-12.5%prior 32
6
BUIC23 (3%)
↓-17.9%prior 28
7
CHRY20 (2.6%)
↑25.0%prior 16
8
DODG19 (2.4%)
↓-17.4%prior 23
9
HOND16 (2.1%)
↑23.1%prior 13
10
PETERBILT16 (2.1%)
↑128.6%prior 7

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

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

Sex Distribution (727 persons with recorded sex)

Male449 (61.8%)
↑6.7%prior 421
Female278 (38.2%)
↓-10.0%prior 309

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: 506
  • Total persons involved: 1,089
  • Total vehicles involved: 777

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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