Yearly Traffic Safety Analysis

246 CRASHES IN
IOWA, IA
2024

All metrics benchmarked against2023

In Delaware County, total traffic crashes remained relatively stable year-over-year, decreasing slightly from 249 in the prior period to 246 in the current period, a 1.2% reduction. Despite this stability in crash volume, the number of people injured increased significantly by 36.4%, rising from 55 to 75. The number of fatalities was unchanged at 2 for both periods.

246

▼ -1.2%was 249

Total Crash Events

2

Persons Killed

75

▲ 36.4%was 55

Persons Injured

2

Fatal Crash Events

Note: "Persons Killed" (2) counts individual fatalities across all crash events. "Fatal" in the severity table below (2) 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 crash trends in Delaware County were stable, with total incidents decreasing by just 3 from 249 to 246 year-over-year. However, the severity of outcomes worsened, as the total number of injuries increased by 36.4% from 55 to 75. The number of fatalities remained constant at 2.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 2→0.0%

1

Pedestrians Injured

Prior: 3↓-66.7%

2

Cyclists Injured

Prior: 1↑100.0%

72

Motorists Injured

Prior: 51↑41.2%

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 shifted between the two periods. The peak day for collisions moved from Wednesday (43 crashes) in the prior year to Monday (45 crashes) in the current year. Similarly, the peak hour for crashes occurred earlier, shifting from 9 p.m. (20 crashes) in the prior period to 7 p.m. (22 crashes) in the current period.

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

The number of fatal crashes (2) and serious injury crashes (8) was identical in both periods. However, the total number of individuals injured rose from 55 to 75. This increase was primarily seen in the 'Possible Injury' category, where the number of persons injured grew from 20 to 35, while the number of persons with minor injuries increased slightly from 27 to 28.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.8%
→0.0%prior 2
Serious Injury8serious injury crashes3.3%
→0.0%prior 8
Minor Injury22minor injury crashes8.9%
↓-8.3%prior 24
Possible Injury22possible injury crashes8.9%
↑10.0%prior 20
No Injury192no injury crashes78%
↓-1.5%prior 195

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

Collisions involving an animal remained the leading contributing factor but decreased in count by 7.8% from 103 to 95 incidents. The second-ranked factor, "Lost Control," saw a 10% increase in count from 20 to 22 crashes. A notable change was observed in crashes attributed to "Ran off road - straight," which more than doubled in count from 6 to 13. Conversely, incidents involving "Driving too fast for conditions" fell by 37.5%, from 16 to 10.

Officer-Reported Primary Contributing Cause

Animal95 (38.6%)↓-7.8%prior 103
Lost Control22 (8.9%)↑10.0%prior 20
Ran off road - straight13 (5.3%)↑116.7%prior 6
FTYROW: From stop sign11 (4.5%)→0.0%prior 11
Driving too fast for conditions10 (4.1%)↓-37.5%prior 16
Followed too close9 (3.7%)→0.0%prior 9
Ran Stop Sign7 (2.8%)
Ran off road - left7 (2.8%)→0.0%prior 7
Driver Distraction: Inattentive/lost in thought6 (2.4%)
Driver Distraction: Other interior distraction6 (2.4%)

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

Road & Environmental Conditions

Crashes in clear weather and on dry roads remained the most frequent scenario in both years. However, there was a significant increase in crashes occurring in adverse weather; incidents in the rain rose from 2 to 12, and collisions on wet road surfaces doubled from 7 to 14. Crashes on icy or frosty surfaces saw a decrease from 14 to 9 incidents year-over-year.

Weather

Clear103 (66.0%)
↓-8.0%prior 112
Cloudy26 (16.7%)
↑23.8%prior 21
Rain12 (7.7%)
Snow5 (3.2%)
↓-37.5%prior 8
Fog, smoke, smog4 (2.6%)
Freezing rain/drizzle3 (1.9%)
↓-40.0%prior 5
Severe Winds2 (1.3%)
Blowing Snow1 (0.6%)

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

Lighting

Daylight104 (64.6%)
↑2.0%prior 102
Dark - roadway not lighted29 (18.0%)
↓-9.4%prior 32
Dusk11 (6.8%)
Dark - roadway lighted7 (4.3%)
↓-36.4%prior 11
Dawn6 (3.7%)
Dark - unknown roadway lighting4 (2.5%)

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

Road Surface

Dry111 (70.7%)
↑2.8%prior 108
Wet14 (8.9%)
↑100.0%prior 7
Snow10 (6.4%)
→0.0%prior 10
Ice/frost9 (5.7%)
↓-35.7%prior 14
Gravel9 (5.7%)
↓-30.8%prior 13
Slush3 (1.9%)
Other (explain in narrative)1 (0.6%)

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

Vehicles & Demographics

Ford and Chevrolet were the top two vehicle makes involved in crashes in both periods. The number of Fords involved increased from 68 to 73, while the number of Chevrolets (combining 'CHEV' and 'CHEVROLET') decreased from 85 to 61. The proportional age distribution of persons involved in crashes was largely consistent, with the 65+ age group representing 18.8% of persons in the current period versus 18.4% in the prior period.

Top Vehicle Makes (319 vehicles)

1
FORD73 (22.9%)
↑7.4%prior 68
2
CHEV50 (15.7%)
↓-25.4%prior 67
3
GMC21 (6.6%)
↑40.0%prior 15
4
JEEP16 (5%)
↑33.3%prior 12
5
DODG13 (4.1%)
↑18.2%prior 11
6
NISS11 (3.4%)
↑57.1%prior 7
7
CHEVROLET11 (3.4%)
↓-38.9%prior 18
8
RAM10 (3.1%)
9
BUIC9 (2.8%)
↓-10.0%prior 10
10
FREIGHTLINER7 (2.2%)
↓-12.5%prior 8

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

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

Sex Distribution (155 persons with recorded sex)

Male106 (68.4%)
↓-43.6%prior 188
Female49 (31.6%)
↓-58.8%prior 119

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: 246
  • Total persons involved: 337
  • Total vehicles involved: 319

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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