Yearly Traffic Safety Analysis

3,202 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Scott County recorded 3,202 total crashes, a slight decrease of 0.8% from the 3,228 crashes reported in 2022. While overall crash volume remained stable, there was a notable 12.2% decrease in total injuries, which fell from 1,216 to 1,068. The most significant proportional change was a 133.3% increase in the number of cyclists injured, which rose from 15 in 2022 to 35 in 2023.

3,202

▼ -0.8%was 3,228

Total Crash Events

16

▼ -5.9%was 17

Persons Killed

1,068

▼ -12.2%was 1,216

Persons Injured

13

▼ -13.3%was 15

Fatal Crash Events

Note: "Persons Killed" (16) counts individual fatalities across all crash events. "Fatal" in the severity table below (13) 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 volume in Scott County remained relatively stable, with a slight year-over-year decrease of 0.8%, from 3,228 incidents in 2022 to 3,202 in 2023. This stability in total crashes was accompanied by a positive trend in outcomes, as total injuries declined by 12.2% and fatalities decreased from 17 to 16.

Vulnerable Road User Casualties

3

Pedestrians Killed

Prior: 3→0.0%

0

Cyclists Killed

Prior: 0→0.0%

13

Motorists Killed

Prior: 14↓-7.1%

0

Other Killed

Prior: 0→0.0%

29

Pedestrians Injured

Prior: 31↓-6.5%

35

Cyclists Injured

Prior: 15↑133.3%

997

Motorists Injured

Prior: 1,166↓-14.5%

7

Other Injured

Prior: 4↑75.0%

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 saw minor shifts between the two periods. The peak day for crashes moved from Friday (598 crashes) in 2022 to Thursday (560 crashes) in 2023. The afternoon commute remained the most frequent time for incidents, with the peak hour shifting slightly later from 3 p.m. in 2022 to 4 p.m. in 2023, which recorded 267 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 metrics showed a slight improvement in 2023 compared to the prior year. The number of fatal crashes decreased from 15 to 13, and their share of all crashes fell from 0.5% to 0.4%. Crashes resulting in serious injuries also declined in count from 56 to 46, as did minor injury crashes, which fell from 366 to 318. Correspondingly, the share of crashes with no reported injuries increased from 67.2% to 67.8%.

Severity is per crash event (most severe injury). 13 fatal crash events resulted in 16 persons killed.

Outcome by Severity (Crash Events)

Fatal13fatal crashes0.4%
↓-13.3%prior 15
Serious Injury46serious injury crashes1.4%
↓-17.9%prior 56
Minor Injury318minor injury crashes9.9%
↓-13.1%prior 366
Possible Injury654possible injury crashes20.4%
↑5.0%prior 623
No Injury2,171no injury crashes67.8%
↑0.1%prior 2,168

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 for crashes remained largely consistent year-over-year, with 'Followed too close' being the top factor in both periods, increasing its count slightly from 378 to 383. Crashes involving animals saw a notable rise, with the count increasing from 177 to 212, moving this factor from fifth to third rank. Conversely, incidents attributed to 'Ran Traffic Signal' decreased from 205 to 185, and 'Ran off road - left' incidents declined from 351 to 318.

Officer-Reported Primary Contributing Cause

Followed too close383 (12%)↑1.3%prior 378
Ran off road - left318 (9.9%)↓-9.4%prior 351
Animal212 (6.6%)↑19.8%prior 177
FTYROW: Making left turn198 (6.2%)↑0.5%prior 197
Ran Traffic Signal185 (5.8%)↓-9.8%prior 205
FTYROW: From stop sign155 (4.8%)↑3.3%prior 150
Other (explain in narrative): Other137 (4.3%)↓-17.0%prior 165
Made improper turn123 (3.8%)↑38.2%prior 89
Operating vehicle in an reckless, erratic, careless, negligent manner99 (3.1%)↑4.2%prior 95
Ran off road - straight98 (3.1%)↑18.1%prior 83

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

Road & Environmental Conditions

Crashes were less likely to occur in adverse conditions in 2023 compared to 2022. The number of crashes on wet, snowy, or icy road surfaces decreased from a combined 573 incidents to 495. Similarly, crashes during dark conditions (both lighted and unlighted roadways) saw a reduction, falling from 949 to 831 year-over-year. This corresponds with a decrease in crashes reported during rain or snow, which collectively fell from 272 to 222.

Weather

Clear2,230 (73.6%)
↑1.7%prior 2,192
Cloudy512 (16.9%)
↑2.4%prior 500
Rain139 (4.6%)
↓-12.6%prior 159
Snow83 (2.7%)
↓-26.5%prior 113
Freezing rain/drizzle33 (1.1%)
↓-10.8%prior 37
Fog, smoke, smog21 (0.7%)
↑61.5%prior 13
Blowing Snow4 (0.1%)
↓-90.5%prior 42
Severe Winds3 (0.1%)
↓-82.4%prior 17
Sleet, hail2 (0.1%)
Blowing sand, soil, dirt1 (0.0%)

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

Lighting

Daylight2,088 (68.8%)
↑4.7%prior 1,995
Dark - roadway lighted654 (21.5%)
↓-11.7%prior 741
Dark - roadway not lighted167 (5.5%)
↓-17.7%prior 203
Dusk67 (2.2%)
↓-20.2%prior 84
Dawn49 (1.6%)
↑8.9%prior 45
Dark - unknown roadway lighting10 (0.3%)
↑100.0%prior 5

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

Road Surface

Dry2,522 (83.2%)
↑4.7%prior 2,409
Wet346 (11.4%)
↓-13.3%prior 399
Snow79 (2.6%)
↓-40.6%prior 133
Ice/frost50 (1.7%)
↓-53.3%prior 107
Gravel17 (0.6%)
→0.0%prior 17
Slush10 (0.3%)
↓-28.6%prior 14
Other (explain in narrative)3 (0.1%)
Water (standing or moving)2 (0.1%)
Mud, dirt1 (0.0%)

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 Ford, Chevrolet, and Toyota being the most common in both 2023 and 2022. An analysis of persons involved in crashes shows a general decrease across most age demographics. The number of persons in the 16-20 age group involved in crashes decreased from 1,019 to 903, and the 26-34 age group saw a decline from 1,195 to 1,118.

Top Vehicle Makes (5,859 vehicles)

1
FORD1,049 (17.9%)
↓-0.4%prior 1,053
2
CHEV494 (8.4%)
↓-3.9%prior 514
3
CHEVROLET386 (6.6%)
↓-14.0%prior 449
4
TOYT287 (4.9%)
↓-2.0%prior 293
5
HOND253 (4.3%)
↓-1.2%prior 256
6
JEEP225 (3.8%)
↑5.1%prior 214
7
NR223 (3.8%)
↓-0.9%prior 225
8
TOYOTA210 (3.6%)
↓-0.9%prior 212
9
GMC198 (3.4%)
↓-7.0%prior 213
10
HONDA169 (2.9%)
↓-18.0%prior 206

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

1,416 persons with unknown or unrecorded age excluded from age chart.

Sex Distribution (5,042 persons with recorded sex)

Male2,763 (54.8%)
↓-4.3%prior 2,886
Female2,279 (45.2%)
↑1.7%prior 2,241

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: 3,202
  • Total persons involved: 7,862
  • Total vehicles involved: 5,859

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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