Yearly Traffic Safety Analysis

249 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Delaware County recorded 249 total crashes, a 3.3% increase from the 241 crashes documented in 2022. While overall collisions saw a slight rise, the number of fatalities doubled from one to two. Conversely, the total number of individuals injured in crashes decreased by 19.1%, from 68 in the prior year to 55 in the current period.

249

▲ 3.3%was 241

Total Crash Events

2

▲ 100.0%was 1

Persons Killed

55

▼ -19.1%was 68

Persons Injured

2

▲ 100.0%was 1

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 · 2023-01-01 to 2023-12-31 · Aggregate counts from crash, person, and vehicle records

Trend Summary

Traffic crashes in Delaware County showed a slight upward trend, increasing by 3.3% from 241 in 2022 to 249 in 2023. This increase of 8 crashes was accompanied by a rise in fatalities from one to two. However, total injuries declined from 68 to 55 over the same period.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

0

Cyclists Killed

Prior: 0→0.0%

2

Motorists Killed

Prior: 1↑100.0%

3

Pedestrians Injured

Prior: 1↑200.0%

1

Cyclists Injured

Prior: 2↓-50.0%

51

Motorists Injured

Prior: 65↓-21.5%

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 between the two periods. In 2023, the peak day for crashes was Wednesday with 43 incidents, a change from Friday (41 incidents) in 2022. The peak hour for collisions also shifted significantly later, moving from the 5 p.m. hour in 2022 (23 crashes) to the 9 p.m. hour in 2023 (20 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 mixed but concerning trend, with the fatal crash rate doubling from 0.41% in 2022 to 0.8% in 2023. This reflects an increase from one fatal crash to two. The proportion of crashes resulting in serious injuries also increased from 2.5% to 3.2% of all incidents, while crashes with possible injuries decreased as a share of the total from 11.2% to 8.0%.

Outcome by Severity (Crash Events)

Fatal2fatal crashes0.8%
↑100.0%prior 1
Serious Injury8serious injury crashes3.2%
↑33.3%prior 6
Minor Injury24minor injury crashes9.6%
↑20.0%prior 20
Possible Injury20possible injury crashes8%
↓-25.9%prior 27
No Injury195no injury crashes78.3%
↑4.3%prior 187

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 animals remained the leading contributing factor in both years, with the count of such incidents rising by 15.7% from 89 in 2022 to 103 in 2023. Crashes attributed to 'Lost Control' also saw a slight increase in count from 18 to 20. In contrast, incidents where 'Followed too close' was a factor decreased in count from 14 in the prior period to 9 in the current period.

Officer-Reported Primary Contributing Cause

Animal103 (41.4%)↑15.7%prior 89
Lost Control20 (8%)↑11.1%prior 18
Driving too fast for conditions16 (6.4%)↑6.7%prior 15
FTYROW: From stop sign11 (4.4%)↓-8.3%prior 12
Followed too close9 (3.6%)↓-35.7%prior 14
Other (explain in narrative): Other8 (3.2%)↓-52.9%prior 17
Operating vehicle in an reckless, erratic, careless, negligent manner7 (2.8%)↑16.7%prior 6
Ran off road - left7 (2.8%)
Ran off road - straight6 (2.4%)↓-50.0%prior 12
Improper Backing6 (2.4%)

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

Road & Environmental Conditions

While most crashes in both periods occurred in clear weather and on dry roads, there were notable shifts in adverse conditions. Crashes on roads with ice or frost increased from 8 incidents in 2022 to 14 in 2023. In terms of lighting, crashes during daylight hours decreased from 111 to 102, while collisions in unlit dark conditions saw a slight increase from 30 to 32.

Weather

Clear112 (72.3%)
↓-4.3%prior 117
Cloudy21 (13.5%)
→0.0%prior 21
Snow8 (5.2%)
↓-42.9%prior 14
Freezing rain/drizzle5 (3.2%)
Fog, smoke, smog4 (2.6%)
Blowing Snow2 (1.3%)
Rain2 (1.3%)
↓-60.0%prior 5
Severe Winds1 (0.6%)

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

Lighting

Daylight102 (65.4%)
↓-8.1%prior 111
Dark - roadway not lighted32 (20.5%)
↑6.7%prior 30
Dark - roadway lighted11 (7.1%)
↓-26.7%prior 15
Dawn4 (2.6%)
↓-20.0%prior 5
Dusk4 (2.6%)
Dark - unknown roadway lighting3 (1.9%)

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

Road Surface

Dry108 (69.7%)
↓-5.3%prior 114
Ice/frost14 (9.0%)
↑75.0%prior 8
Gravel13 (8.4%)
↑30.0%prior 10
Snow10 (6.5%)
↓-33.3%prior 15
Wet7 (4.5%)
↓-41.7%prior 12
Slush3 (1.9%)
↓-40.0%prior 5

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

Vehicles & Demographics

Chevrolet and Ford remained the most common vehicle makes involved in crashes, with the number of both makes increasing in 2023 compared to 2022. The most significant demographic change was among persons in the 65+ age group, whose involvement in crashes grew by 54.5% from 55 individuals in 2022 to 85 in 2023. Meanwhile, involvement of the 26-34 age group decreased from 78 to 71 persons.

Top Vehicle Makes (326 vehicles)

1
FORD68 (20.9%)
↑21.4%prior 56
2
CHEV67 (20.6%)
↑17.5%prior 57
3
CHEVROLET18 (5.5%)
↓-10.0%prior 20
4
GMC15 (4.6%)
→0.0%prior 15
5
CHRY13 (4%)
↑85.7%prior 7
6
HOND12 (3.7%)
↑33.3%prior 9
7
JEEP12 (3.7%)
→0.0%prior 12
8
KIA11 (3.4%)
↓-21.4%prior 14
9
DODG11 (3.4%)
↓-47.6%prior 21
10
BUIC10 (3.1%)
↑11.1%prior 9

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

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

Sex Distribution (307 persons with recorded sex)

Male188 (61.2%)
↓-0.5%prior 189
Female119 (38.8%)
↑2.6%prior 116

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: 249
  • Total persons involved: 496
  • Total vehicles involved: 326

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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