Yearly Traffic Safety Analysis

712 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Lee County recorded 712 total crashes, a 6.4% increase from the 669 crashes reported in 2022. While total crashes rose, the number of fatalities decreased from 7 to 5. A notable year-over-year shift was the 81% increase in the count of crashes attributed to running a stop sign, which rose from 16 incidents in 2022 to 29 in 2023.

712

▲ 6.4%was 669

Total Crash Events

5

▼ -28.6%was 7

Persons Killed

144

▲ 0.7%was 143

Persons Injured

4

▼ -42.9%was 7

Fatal Crash Events

Note: "Persons Killed" (5) counts individual fatalities across all crash events. "Fatal" in the severity table below (4) 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 trend in Lee County shows an increase in traffic collisions year-over-year. Total crashes rose by 6.4%, from 669 in 2022 to 712 in 2023. Despite this increase in total incidents, the number of resulting fatalities fell from 7 to 5, and the total number of injuries remained stable at 144 compared to 143 in the prior year.

Vulnerable Road User Casualties

2

Pedestrians Killed

Prior: 1↑100.0%

0

Cyclists Killed

Prior: 1↓-100.0%

3

Motorists Killed

Prior: 5↓-40.0%

4

Pedestrians Injured

Prior: 2↑100.0%

6

Cyclists Injured

Prior: 2↑200.0%

134

Motorists Injured

Prior: 139↓-3.6%

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 temporal patterns of crashes in Lee County remained largely consistent year-over-year. Thursday continued to be the day with the highest number of incidents, with 132 crashes in 2023 compared to 131 in 2022. The peak hour for collisions shifted slightly later, moving from the 5 p.m. hour in 2022 (55 crashes) to the 6 p.m. hour in 2023 (61 crashes). November was the month with the most crashes in both years.

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

While total crashes increased, the severity of those crashes showed a mixed trend. The number of fatal crashes decreased from 7 in 2022 to 4 in 2023, causing the fatal crash rate to fall from 1.05 to 0.56 per 100 crashes. However, the proportion of crashes involving any level of injury increased, rising from 17.9% of all crashes in 2022 to 20.8% in 2023. This was driven by increases in both serious injury crashes (from 16 to 17) and minor injury crashes (from 52 to 62).

Severity is per crash event (most severe injury). 4 fatal crash events resulted in 5 persons killed.

Outcome by Severity (Crash Events)

Fatal4fatal crashes0.6%
↓-42.9%prior 7
Serious Injury17serious injury crashes2.4%
↑6.3%prior 16
Minor Injury62minor injury crashes8.7%
↑19.2%prior 52
Possible Injury69possible injury crashes9.7%
↑32.7%prior 52
No Injury560no injury crashes78.7%
↑3.3%prior 542

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 with animals remained the most common contributing factor in both periods, with counts rising from 256 to 261. The top five factors were largely consistent, but there were significant shifts in the counts for specific driver actions. Crashes attributed to running a stop sign increased by 81%, from 16 incidents in 2022 to 29 in 2023. Similarly, incidents of following too closely rose by 44% in count, from 27 to 39. In contrast, crashes due to a failure to yield from a stop sign remained unchanged at 36 incidents.

Officer-Reported Primary Contributing Cause

Animal261 (36.7%)↑2.0%prior 256
Other (explain in narrative): Other47 (6.6%)↑11.9%prior 42
Lost Control41 (5.8%)↓-2.4%prior 42
Followed too close39 (5.5%)↑44.4%prior 27
FTYROW: From stop sign36 (5.1%)→0.0%prior 36
Ran Stop Sign29 (4.1%)↑81.3%prior 16
Driver Distraction: Other interior distraction27 (3.8%)↓-18.2%prior 33
Ran off road - straight25 (3.5%)↑38.9%prior 18
Ran off road - left20 (2.8%)↓-23.1%prior 26
FTYROW: Making left turn15 (2.1%)↑7.1%prior 14

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

Road & Environmental Conditions

A greater share of crashes in 2023 occurred in clear weather and on dry roads compared to the prior year. In 2023, 80.5% of crashes with known weather data occurred in clear conditions, up from 65.3% in 2022. Similarly, the proportion of crashes on dry road surfaces increased from 74.8% to 85.9%. Conversely, the share of crashes happening in daylight decreased from 70.0% to 64.1%, with a corresponding increase in crashes during dark conditions, particularly on lighted roadways where incidents rose from 27 to 49.

Weather

Clear372 (80.5%)
↑26.1%prior 295
Cloudy59 (12.8%)
↓-39.2%prior 97
Rain15 (3.2%)
↓-42.3%prior 26
Snow9 (1.9%)
↓-47.1%prior 17
Freezing rain/drizzle6 (1.3%)
↓-40.0%prior 10
Fog, smoke, smog1 (0.2%)

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

Lighting

Daylight303 (64.1%)
↓-4.4%prior 317
Dark - roadway not lighted85 (18.0%)
→0.0%prior 85
Dark - roadway lighted49 (10.4%)
↑81.5%prior 27
Dusk21 (4.4%)
↑90.9%prior 11
Dark - unknown roadway lighting8 (1.7%)
Dawn7 (1.5%)
↓-30.0%prior 10

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

Road Surface

Dry398 (86.0%)
↑17.4%prior 339
Wet35 (7.6%)
↓-18.6%prior 43
Gravel11 (2.4%)
↓-8.3%prior 12
Ice/frost8 (1.7%)
↓-60.0%prior 20
Snow7 (1.5%)
↓-75.0%prior 28
Slush3 (0.6%)
↓-57.1%prior 7
Other (explain in narrative)1 (0.2%)

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 stable, with Chevrolet and Ford representing the top two makes in both 2022 and 2023. The total number of vehicles involved increased from 971 to 1,040, in line with the overall increase in crashes. There was a notable shift in the age demographics of people involved in collisions. The 26-34 age group saw its involvement increase from 204 individuals to 240, becoming the most represented group in 2023. In contrast, the 65+ age group, which was the most represented in 2022 with 221 individuals, saw its numbers decrease to 194.

Top Vehicle Makes (1,040 vehicles)

1
FORD169 (16.3%)
↑1.8%prior 166
2
CHEV126 (12.1%)
↓-6.7%prior 135
3
CHEVROLET69 (6.6%)
→0.0%prior 69
4
GMC63 (6.1%)
↑21.2%prior 52
5
JEEP53 (5.1%)
↑76.7%prior 30
6
DODG43 (4.1%)
↓-8.5%prior 47
7
KIA43 (4.1%)
↑48.3%prior 29
8
TOYT35 (3.4%)
↑84.2%prior 19
9
DODGE32 (3.1%)
↓-8.6%prior 35
10
CHRY29 (2.8%)
→0.0%prior 29

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

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

Sex Distribution (921 persons with recorded sex)

Male508 (55.2%)
↑4.1%prior 488
Female413 (44.8%)
↑5.6%prior 391

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: 712
  • Total persons involved: 1,507
  • Total vehicles involved: 1,040

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