Yearly Traffic Safety Analysis

204 CRASHES IN
IOWA, IA
2023

All metrics benchmarked against2022

In 2023, Crawford County recorded 204 total crashes, a 9.7% increase from the 186 crashes reported in 2022. The number of resulting injuries rose by 52.8% from 53 to 81. A significant year-over-year change was the doubling of crashes involving a driver under the influence (DUI), which increased from 8 in 2022 to 16 in 2023.

204

▲ 9.7%was 186

Total Crash Events

3

▲ 50.0%was 2

Persons Killed

81

▲ 52.8%was 53

Persons Injured

3

▲ 50.0%was 2

Fatal Crash Events

Note: "Persons Killed" (3) counts individual fatalities across all crash events. "Fatal" in the severity table below (3) 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 crashes in Crawford County trended upward from 2022 to 2023, with total incidents rising by 9.7% from 186 to 204. This increase was accompanied by a rise in both fatalities, from 2 to 3, and total injuries, which climbed 52.8% from 53 to 81.

Vulnerable Road User Casualties

0

Pedestrians Killed

Prior: 0→0.0%

3

Motorists Killed

Prior: 2↑50.0%

1

Pedestrians Injured

Prior: 0→%

80

Motorists Injured

Prior: 51↑56.9%

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 Friday with 32 incidents, a change from 2022 when Tuesday was the peak day with 34 crashes. The peak hour for collisions also shifted earlier, from the 5 p.m. hour in 2022 (19 crashes) to the 3 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

The number of fatal crashes increased from 2 in 2022 to 3 in 2023, with the fatality rate per 100 crashes rising from 1.08 to 1.47. While the count of serious injury crashes decreased from 7 to 4, crashes resulting in possible injury saw a notable increase, rising from 21 incidents in 2022 to 37 in 2023. Consequently, the proportion of crashes with no injuries decreased from 73.7% of all crashes in 2022 to 68.1% in 2023.

Outcome by Severity (Crash Events)

Fatal3fatal crashes1.5%
↑50.0%prior 2
Serious Injury4serious injury crashes2%
↓-42.9%prior 7
Minor Injury21minor injury crashes10.3%
↑10.5%prior 19
Possible Injury37possible injury crashes18.1%
↑76.2%prior 21
No Injury139no injury crashes68.1%
↑1.5%prior 137

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 an animal remained the leading contributing factor in both periods, with an identical count of 28 crashes. The second-most cited factor in 2023, 'Ran off road - left,' saw its count more than double from 9 to 20 incidents year-over-year. Conversely, crashes attributed to 'Lost Control' decreased substantially, falling from 18 in 2022 to just 5 in 2023. Crashes due to 'Failure to yield from a stop sign' also increased, rising from 9 to 13 incidents.

Officer-Reported Primary Contributing Cause

Animal28 (13.7%)→0.0%prior 28
Ran off road - left20 (9.8%)↑122.2%prior 9
Other (explain in narrative): Other19 (9.3%)→0.0%prior 19
FTYROW: From stop sign13 (6.4%)↑44.4%prior 9
Followed too close12 (5.9%)↓-29.4%prior 17
Ran Stop Sign9 (4.4%)
FTYROW: Making left turn9 (4.4%)↑50.0%prior 6
Driver Distraction: Other interior distraction8 (3.9%)↓-20.0%prior 10
Ran off road - straight7 (3.4%)
Driving too fast for conditions6 (2.9%)

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

Road & Environmental Conditions

In both 2022 and 2023, the majority of crashes occurred in clear weather, during daylight hours, and on dry roads, with the proportion of crashes under these ideal conditions increasing slightly in 2023. However, there was a notable increase in crashes on icy or frosty roads, which rose from 6 incidents in 2022 to 16 in 2023. Similarly, collisions in dark, unlighted conditions increased from 22 to 34 year-over-year.

Weather

Clear144 (76.2%)
↑17.1%prior 123
Cloudy26 (13.8%)
↑36.8%prior 19
Snow4 (2.1%)
↓-63.6%prior 11
Rain4 (2.1%)
↓-33.3%prior 6
Freezing rain/drizzle4 (2.1%)
Fog, smoke, smog3 (1.6%)
Blowing Snow2 (1.1%)
Other (explain in narrative)1 (0.5%)
Sleet, hail1 (0.5%)

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

Lighting

Daylight126 (66.0%)
↑14.5%prior 110
Dark - roadway not lighted34 (17.8%)
↑54.5%prior 22
Dark - roadway lighted20 (10.5%)
↓-20.0%prior 25
Dusk10 (5.2%)
↑100.0%prior 5
Dark - unknown roadway lighting1 (0.5%)

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

Road Surface

Dry147 (77.4%)
↑16.7%prior 126
Ice/frost16 (8.4%)
↑166.7%prior 6
Wet12 (6.3%)
↑20.0%prior 10
Snow9 (4.7%)
↓-40.0%prior 15
Gravel5 (2.6%)
↓-28.6%prior 7
Slush1 (0.5%)

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

Vehicles & Demographics

The most common vehicle makes involved in crashes shifted, with Chevrolet vehicles (recorded as CHEV and CHEVROLET) increasing from 74 in 2022 to 96 in 2023, overtaking Ford, which saw a decrease from 54 to 46 vehicles. The age demographics of persons involved in crashes also changed. The representation of individuals aged 26-34 and 35-44 increased, while the proportion of those in the 16-20 age group decreased from 15.4% of all persons in 2022 to 12.4% in 2023.

Top Vehicle Makes (342 vehicles)

1
CHEV71 (20.8%)
↑36.5%prior 52
2
FORD46 (13.5%)
↓-14.8%prior 54
3
CHEVROLET25 (7.3%)
↑13.6%prior 22
4
JEEP19 (5.6%)
↑90.0%prior 10
5
TOYT15 (4.4%)
↓-6.3%prior 16
6
HOND14 (4.1%)
↑40.0%prior 10
7
GMC12 (3.5%)
↓-20.0%prior 15
8
DODG11 (3.2%)
↑22.2%prior 9
9
NISS9 (2.6%)
↓-18.2%prior 11
10
PETERBILT8 (2.3%)
↑60.0%prior 5

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

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

Sex Distribution (309 persons with recorded sex)

Male194 (62.8%)
↑6.0%prior 183
Female115 (37.2%)
↑22.3%prior 94

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: 204
  • Total persons involved: 467
  • Total vehicles involved: 342

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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