Yearly Traffic Safety Analysis

3,101 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In 2024, Scott County recorded 3,101 traffic crashes, a 3.2% decrease from the 3,202 crashes reported in 2023. Despite the overall reduction in collisions, the number of fatalities increased significantly, rising 43.8% from 16 in the prior year to 23 in the current period. This increase in fatalities occurred across 22 fatal crashes, up from 13 in the previous year.

3,101

▼ -3.2%was 3,202

Total Crash Events

23

▲ 43.8%was 16

Persons Killed

1,036

▼ -3.0%was 1,068

Persons Injured

22

▲ 69.2%was 13

Fatal Crash Events

Note: "Persons Killed" (23) counts individual fatalities across all crash events. "Fatal" in the severity table below (22) counts crash events where at least one fatality occurred. A single crash can result in multiple fatalities.

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Overall traffic crashes in Scott County saw a modest year-over-year decline, falling by 3.2% from 3,202 in 2023 to 3,101 in 2024. Similarly, the total number of injuries decreased by 3.0%, from 1,068 to 1,036. However, this downward trend in crashes and injuries was contrasted by a sharp 43.8% increase in fatalities, which rose from 16 to 23.

Vulnerable Road User Casualties

4

Pedestrians Killed

Prior: 3↑33.3%

0

Cyclists Killed

Prior: 0→0.0%

19

Motorists Killed

Prior: 13↑46.2%

0

Other Killed

Prior: 0→0.0%

27

Pedestrians Injured

Prior: 29↓-6.9%

19

Cyclists Injured

Prior: 35↓-45.7%

989

Motorists Injured

Prior: 997↓-0.8%

1

Other Injured

Prior: 7↓-85.7%

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Mode classified from person records (driver/passenger → motorist; pedestrian; bicyclist → cyclist; in-line skater / unspecified → other)

When Crashes Happen

The temporal patterns of crashes showed some shifts between the two periods. In 2024, the peak day for crashes was Friday with 496 incidents, a change from 2023 when Thursday was the busiest day with 560 crashes. The peak hour also shifted slightly, moving from the 4 p.m. hour in 2023 (267 crashes) to the 3 p.m. hour in 2024 (297 crashes).

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash date field aggregated by weekday

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Crash time field aggregated by hour (0-23)

Crash Severity Breakdown

While the total number of crashes decreased, the severity of those crashes increased year-over-year. The proportion of crashes resulting in a fatality rose from 0.4% in 2023 to 0.7% in 2024, with the number of fatal crashes increasing from 13 to 22. The share of crashes involving serious injuries also saw a slight increase from 1.4% to 1.7%, while the overall proportion of crashes involving any injury remained stable at approximately 31% for both periods.

Severity is per crash event (most severe injury). 22 fatal crash events resulted in 23 persons killed.

Outcome by Severity (Crash Events)

Fatal22fatal crashes0.7%
↑69.2%prior 13
Serious Injury53serious injury crashes1.7%
↑15.2%prior 46
Minor Injury319minor injury crashes10.3%
↑0.3%prior 318
Possible Injury600possible injury crashes19.3%
↓-8.3%prior 654
No Injury2,107no injury crashes67.9%
↓-2.9%prior 2,171

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · KABCO injury classification scale

Severity Distribution (Crash Events)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Most severe injury per crash record

Top Contributing Factors

The primary contributing factors for crashes remained consistent, with 'Followed too close' being the most cited cause in both periods, though its count decreased by 12.8% from 383 to 334. The top five factors were identical in both years, including 'Ran off road - left' (318 to 281) and 'Animal' (212 to 187), both of which also saw a reduction in count. A notable increase was observed in crashes attributed to 'Lost Control,' which rose by 37.2% from 94 incidents in 2023 to 129 in 2024.

Officer-Reported Primary Contributing Cause

Followed too close334 (10.8%)↓-12.8%prior 383
Ran off road - left281 (9.1%)↓-11.6%prior 318
FTYROW: Making left turn189 (6.1%)↓-4.5%prior 198
Animal187 (6%)↓-11.8%prior 212
Ran Traffic Signal186 (6%)↑0.5%prior 185
FTYROW: From stop sign144 (4.6%)↓-7.1%prior 155
Lost Control129 (4.2%)↑37.2%prior 94
Driving too fast for conditions125 (4%)↑35.9%prior 92
Other (explain in narrative): Other117 (3.8%)↓-14.6%prior 137
Ran off road - straight103 (3.3%)↑5.1%prior 98

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Officer-reported primary contributory cause per crash

Road & Environmental Conditions

The distribution of crashes across different environmental conditions remained largely unchanged year-over-year. In both 2024 and 2023, approximately 65% of crashes occurred in daylight and about 70% occurred in clear weather. There was a slight increase in the proportion of crashes on adverse road surfaces like wet, icy, or snowy roads, which accounted for 16.7% of all crashes in 2024, up from 15.2% in 2023. The share of crashes on dry roads decreased from 78.8% to 77.1%.

Weather

Clear2,179 (74.4%)
↓-2.3%prior 2,230
Cloudy447 (15.3%)
↓-12.7%prior 512
Rain137 (4.7%)
↓-1.4%prior 139
Snow90 (3.1%)
↑8.4%prior 83
Freezing rain/drizzle34 (1.2%)
↑3.0%prior 33
Fog, smoke, smog23 (0.8%)
↑9.5%prior 21
Blowing Snow11 (0.4%)
Severe Winds4 (0.1%)
Other (explain in narrative)3 (0.1%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Weather condition at time of crash

Lighting

Daylight2,006 (68.3%)
↓-3.9%prior 2,088
Dark - roadway lighted609 (20.7%)
↓-6.9%prior 654
Dark - roadway not lighted202 (6.9%)
↑21.0%prior 167
Dusk59 (2.0%)
↓-11.9%prior 67
Dawn43 (1.5%)
↓-12.2%prior 49
Dark - unknown roadway lighting20 (0.7%)
↑100.0%prior 10

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Lighting condition field

Road Surface

Dry2,391 (81.6%)
↓-5.2%prior 2,522
Wet310 (10.6%)
↓-10.4%prior 346
Ice/frost99 (3.4%)
↑98.0%prior 50
Snow88 (3.0%)
↑11.4%prior 79
Gravel18 (0.6%)
↑5.9%prior 17
Slush18 (0.6%)
↑80.0%prior 10
Other (explain in narrative)2 (0.1%)
Water (standing or moving)2 (0.1%)
Mud, dirt1 (0.0%)

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Road surface condition field

Vehicles & Demographics

The top five vehicle makes involved in crashes were Ford, Chevrolet, Toyota, Honda, and Jeep in both 2024 and 2023, with their rank order remaining unchanged. The number of crashes involving these top makes decreased, in line with the overall reduction in total collisions. An analysis of persons involved in crashes shows that the 26-34 age group represented the largest share in both years, accounting for 18.0% of individuals in 2024, a slight increase from their 17.3% share in 2023.

Top Vehicle Makes (5,624 vehicles)

1
FORD936 (16.6%)
↓-10.8%prior 1,049
2
CHEV483 (8.6%)
↓-2.2%prior 494
3
CHEVROLET435 (7.7%)
↑12.7%prior 386
4
TOYT294 (5.2%)
↑2.4%prior 287
5
HOND248 (4.4%)
↓-2.0%prior 253
6
NR248 (4.4%)
↑11.2%prior 223
7
JEEP221 (3.9%)
↓-1.8%prior 225
8
GMC217 (3.9%)
↑9.6%prior 198
9
KIA201 (3.6%)
↑19.6%prior 168
10
TOYOTA194 (3.4%)
↓-7.6%prior 210

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · Vehicle unit records

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

Sex Distribution (3,546 persons with recorded sex)

Male2,016 (56.9%)
↓-27.0%prior 2,763
Female1,530 (43.1%)
↓-32.9%prior 2,279

Source: Iowa Crash Data · ArcGIS Open Data · 2024-01-01 to 2024-12-31 · 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: 2024-01-01 through 2024-12-31
  • Report generated: September 9, 2026

Data Coverage

  • Reporting period: 2024-01-01 through 2024-12-31 (366 days)
  • Geographic scope: iowa, IA
  • Total crash records analyzed: 3,101
  • Total persons involved: 5,868
  • Total vehicles involved: 5,624

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: 2024." Published September 9, 2026. Reporting period: 2024-01-01 to 2024-12-31. Data source: Iowa Crash Data, ArcGIS Open Data. Available at: https://thatcarhitme.com/crash-data/iowa/statewide/2024-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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